DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on August 29, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner.
Response to Amendment
The amendment filed October 14, 2025 has been entered. Claims 1-18 remain pending in the instant application. Applicant’s amendments to the claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed July 16, 2025. The replacement drawings have overcome the objections previously set forth in the Non-Final Office Action. Applicant’s amendments to Claims 1-7, 13, and 14 have overcome their respective rejections under 35 U.S.C 112(b).
Applicant’s amendments to the claims have not overcome rejections under 35 U.S.C 112(b) regarding limitations interpreted under 35 U.S.C 112(f). Applicant has not made clear whether the instant claims are still intended to invoke 35 U.S.C 112(f). Nevertheless, the limitation “a computer program executable by a processor,” as amended by Applicant, does not provide sufficient structure to avoid invoking 35 U.S.C 112(f). The recited computer program would not be recognized by one of ordinary skill in the art as normally comprising the claimed modules or performing the claimed functions when claimed generally, without a specific structure or algorithm.
Applicant further points to pages 26 and 27 of the instant specification as providing support for the limitations invoking 35 U.S.C 112(f). Pages 26 and 27 of the instant specification merely describe a general-purpose computer as implementing the claimed invention; “For a computer-implemented 35 U.S.C. 112(f) claim limitation, the specification must disclose an algorithm for performing the claimed specific computer function, or else the claim is indefinite under 35 U.S.C. 112(b) […] The corresponding structure is not simply a general purpose computer by itself but the special purpose computer as programmed to perform the disclosed algorithm,” see MPEP § 2181(II)(B). The instant specification discloses the functions performed by the modules, but does not provide the specific algorithms necessary to implement said functions on a computer. Thus, Claims 8-12 remain rejected under 35 U.S.C 112(b).
Response to Arguments
Applicant’s arguments, filed October 14, 2025, regarding rejections under 35 U.S.C 101 have been fully considered, but they are not persuasive.
Applicant argues that the claimed invention is integrated into a practical application by providing an improvement to the functioning of a computer or other technology under step 2A prong II of the abstract idea analysis. Specifically, Applicant argues that the segmented linearization technique used to process nonlinear models improves computer simulation of physical equipment because linear models run faster than nonlinear models.
Regarding Applicant’s argument that independent Claim 1 integrates the judicial exception(s) into a practical application by providing an improvement in technology, the Examiner notes that “the judicial exception alone cannot provide the improvement,” see MPEP § 2106.05(a) referenced by MPEP § 2106.04(d)(1). The claim limitations “determining a value range,” “dividing the value range,” “determining a plurality of input sample values,” “traversing input sample value combinations,” “using all the input sample value combinations,” and “performing interpolation” constitute mental processes and/or mathematical concepts. While the improvement can be provided by one or more additional element(s) in combination with the judicial exception(s), the additional elements in the instant claims merely recite generic computer components as instructions to apply the abstract idea(s) on a computer, insignificant extra-solution activity, and/or a general field of use and technological environment, see MPEP § 2106.05(f)-(h).
Furthermore, the claims must reflect the particular way of achieving the technological improvement described in the specification. The instant claims do not expressly recite steps to perform a simulation using the linear models, nor do the claims describe the models in any way in which one of ordinary skill in the art would recognize the linear models as having improved performance on a general-purpose computer. Broadly claiming that linear models run faster than non-linear models, without any express definition of either, is merely an idea of a solution or improvement. Therefore, the claims are ineligible under 35 U.S.C 101.
Applicant’s arguments regarding rejections under 35 U.S.C 103 have been fully considered, but they are not persuasive.
Applicant argues that Eryilmaz does not teach performing interpolation of the tensor table, as amended into instant Claim 1. Specifically, applicant argues that interpolation is only used to initialize the lookup table in Eryilmaz, and the adaptation algorithms used on the initialized tensor table are not interpolation.
Regarding Applicant’s argument that the adaptation algorithms of Eryilmaz are not interpolation, the Examiner disagrees. Under a broadest reasonable interpretation, the claimed interpolation performs the same function as the adaptation algorithms of Eryilmaz, wherein unknown values are interpolated from known values. The claims do not define interpolation in a specific way that differentiates the claimed interpolation from the adaptation algorithm of Eryilmaz, and the specification does not appear to provide an express definition of interpolation that is different from its plain meaning.
The Examiner also notes that Eryilmaz does teach interpolation of a tensor table, “FIG. 6 shows an example of a two-dimensional point-based lookup 150, where each dot represents a point 152. In the point-based embodiment, each point has an adaptation weight, which depends on the specific adaptation algorithm used. If the current operating point (xi, x2) lies within a cell, the points that define the boundaries of that cell are adapted(adapted point values 134) according to where the operating point is located relative to the measured data, shown in the example as d=l.09. The particular cell is located by comparing the input data 64 with the breakpoints 94 of the corresponding indexing variables. In the example shown, a pair of input data (x1 =2400, x2=47) 64 and the adapted points around this operating point 134 are shown in the figure. The value of the "adapted" operating point 76 (y=l .142), which is found by interpolation of the adapted (neighboring) table points.”
An updated rejection under 35 U.S.C 103, necessitated by Applicant’s amendment, is provided below.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
First processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a first processing module used to determine…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
Second processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a second processing module dividing…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
Third processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a third processing module determining…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
Fourth processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a fourth processing module traversing…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
Fifth processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a fifth processing module using…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
Sixth processing module in claim 8. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a sixth processing module […] to perform interpolation…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation processing module could be software, hardware, or any combination thereof.
First modeling module in claim 12. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a first modeling module programmed to: determine…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation module could be software, hardware, or any combination thereof.
Second modeling module in claim 12. This limitation is analyzed according to the three prong test for invoking 35 U.S.C 112(f) below:
The claim uses the generic placeholder “module” as a substitute for “means.”
The term “module is modified by functional language, e.g., a second modelling module programmed to […] obtain…
The term “module” is not modified by sufficient structure, material, or acts for performing the claimed function. The limitation module could be software, hardware, or any combination thereof.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 and 8-12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding Claim 2, the claim recites “wherein the dividing the value range of each input parameter into the plurality of subintervals based on the plurality of interpolation points is based on the balancing criterion.” The limitation “the balancing criterion” lacks antecedent basis. For the purposes of compact prosecution, “the balancing criterion” will be interpreted as “a balancing criterion.”
Regarding Claim 8, the limitations “first processing module,” “second processing module,” “third processing module,” “fourth processing module,” “fifth processing module,” and “sixth processing module” invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed functions and to clearly link the structure, material, or acts to the functions. The specification is further devoid of any physical structures or algorithms which may perform the claimed functions beyond merely reciting the functions as in the claims. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Regarding Claims 9-11, the claims require the limitations of claim 8, on which these claims depend, and the claims are rejected under 35 U.S.C 112(b) for the same reasons.
Regarding Claim 12, the limitations “first modeling module” and “second modeling module” which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed functions and to clearly link the structure, material, or acts to the functions. The specification is further devoid of any physical structures or algorithms which may perform the claimed functions beyond merely reciting the functions as in the claims. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental processes and/or mathematical concepts without significantly more.
The following is an analysis of independent claim 1 based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG).
Step 1, Statutory Category:
Yes: Claims 1-7 are directed to a method.
Step 2A Prong I, judicial Exception:
The Examiner submits that the foregoing claim limitations constitute mental processes, as the claims cover the performance of the limitations of the human mind, given their broadest reasonable interpretation. Abstract ideas are bolded.
Claim 1 recites the limitations:
1. (Currently Amended) A linearization processing method for nonlinear models, the method comprising:
for a nonlinear model of each piece of physical equipment, determining a value range of each input parameter of the model;
dividing the value range of each input parameter into a plurality of subintervals based on a plurality of interpolation points;
determining a plurality of input sample values in each subinterval by using equal division;
traversing input sample value combinations of each input parameter of the model, and using the nonlinear model to obtain an output sample value combination corresponding to each input sample value combination;
using all the input sample value combinations and the corresponding output sample value combinations to generate a tensor table; and
performing interpolation of the tensor table according to a current value of each input parameter to obtain a corresponding output value.
The limitations determining a value range, dividing the value range, determining a plurality of input sample values, traversing input sample value combinations, obtain an output sample value combination, generate a tensor table, and performing interpolation are abstract ideas because they are directed to mathematical concepts and/or mental processes, observations, evaluations, judgements, and opinions. A user can perform the mental evaluations of determining a value range, dividing the value range, determining input values, traversing combinations, obtaining a combination using a model, and generating a tensor table. A user may use pen and paper to perform the necessary calculations.
Step 2A Prong II, Integration into a Practical Application:
Claim 1 recites the following additional claim limitations outside the abstract idea which only present general fields of use, mere instructions to apply an exception, and/or insignificant extra-solution activity:
A linearization processing method for nonlinear models (general field of use, see MPEP § 2106.05(h)).
Step 2B, Significantly More:
When considered individually or in combination, the additional limitations and elements of claim 1 do not amount to significantly more than the judicial exceptions for the same reasons above as to why the additional limitations do not integrate the abstract idea into a practical application.
The additional limitations identified as mere instructions to apply an exception, insignificant extra-solution activity, or general field of use above are carried over and also do not provide significantly more than the abstract idea. See MPEP § 2106.04(d) referencing MPEP § 2106.05(f), MPEP § 2106.05(g), and MPEP § 2106.05(h).
Considering the claim limitations in combination and the claims as a whole does not change this conclusion, and claim 1 is ineligible under 35 U.S.C 101.
Regarding Claim 2, the claim recites The linearization processing method for nonlinear models as claimed in claim 1, wherein the dividing the value range of each input parameter into the plurality of subintervals based on the plurality of interpolation points is based on the balancing criterion dividing the value range of each input parameter into the plurality of subintervals based on the plurality of interpolation points; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 2 is ineligible under 35 U.S.C 101.
Regarding Claim 3, the claim recites The linearization processing method for nonlinear models as claimed in claim 1, wherein the determining the plurality of input sample values in each subinterval by using equal division comprises determining the plurality of input sample values in each subinterval by using equal division based on a balancing criterion; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of determining a plurality of determining input sample values based on a balancing criterion. A user may use pen and paper to perform the determination.
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 3 is ineligible under 35 U.S.C 101.
Regarding Claim 4, the claim recites The linearization processing method for nonlinear models as claimed in claim 1, wherein the performing the interpolation of the tensor table according to the current value of each input parameter to obtain the corresponding output value is performed during simulation; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 4 is ineligible under 35 U.S.C 101.
Regarding Claim 5, the claim recites The linearization processing method for nonlinear models as claimed in claim 1, wherein the nonlinear model of each piece of physical equipment is obtained by: determining complete design point data for each target nonlinear underlying process of each type of physical equipment; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental observation of determining design point data. A user may use pen and paper to record the data.
establishing a descriptive formula of the nonlinear underlying process by use of a ratio of similarity parameter supported by a similarity criterion to a similarity parameter based on design point data, to obtain a universal model of the nonlinear underlying process; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of establishing a descriptive formula. A user may use pen and paper to perform the required calculations.
wherein the universal model comprises a variable parameter that changes as a parameter of an actual working condition changes; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
constructing a machine learning algorithm between the parameter of the actual working condition and the variable parameter; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of constructing an algorithm. Furthermore, this limitation recites the further additional element “machine learning,” which is a high level recitation of generic computer components, computer elements used as a tool, and represents mere instructions to apply the abstract idea on a computer under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(f).
and establishing a correlation between the machine learning algorithm and the universal model; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of correlating an algorithm and a model. A user may use pen and paper to calculate the correlation.
taking the universal models of all the target nonlinear underlying processes of each type of physical equipment and the correlated machine learning algorithms as a universal model of the type of physical equipment; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental observation of taking models and algorithms as a universal model. A user may use pen and paper to record the universal model.
for each target nonlinear underlying process of one specific piece of physical equipment of the type of equipment, obtaining historical data of the parameter of the actual working condition and the variable parameter corresponding to the target nonlinear underlying process of the specific piece of physical equipment; this limitation is considered to be insignificant extra-solution activity under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(g). The insignificant extra-solution activity of, for each target […] obtaining historical data is further well-understood, routine conventional activity under step 2B of the abstract idea analysis, see MPEP § 2106.05(d)(II); “The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity […] i. Receiving or transmitting data over a network […] ii. Performing repetitive calculations […] iv. Storing and retrieving information in memory.”
and using the historical data to train the machine learning algorithm, to obtain a training model of the variable parameter of the target nonlinear underlying process; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of training an algorithm. A user may use pen and paper to calculate the algorithm weights.
substituting the training model of the variable parameter of the target nonlinear underlying process into the universal model of the target nonlinear underlying process, to obtain a trained model of the target nonlinear underlying process of the specific piece of physical equipment; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental evaluation of substituting a model into another model. A user may use pen and paper to perform the substitution.
taking the trained models of all the target nonlinear underlying processes of the specific piece of physical equipment as a universal model of the specific piece of equipment; this limitation is considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). A user can perform the mental observation of taking the trained models as a universal model. A user may use pen and paper to record the universal model.
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations are considered to constitute additional mental processes under step 2A prong I of the abstract idea analysis, see MPEP § 2106.04(a)(2)(III). The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 5 is ineligible under 35 U.S.C 101.
Regarding Claim 6, the claim recites The linearization processing method for nonlinear models as claimed in claim 5, wherein the variable parameter has a preset default value; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 6 is ineligible under 35 U.S.C 101.
Regarding Claim 7, the claim recites The linearization processing method for nonlinear models as claimed in claim 5, wherein the physical equipment includes: gas turbines, heat pumps, internal combustion engines, steam turbines, waste heat boilers, absorption refrigerators, heating machines, multi-effect evaporators, water electrolyzers for hydrogen production, equipment for producing chemicals from hydrogen, reverse osmosis devices, fuel cells, and boilers; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
the target nonlinear underlying processes of each type of physical equipment include one or more of the following processes: a heat transfer process, a process of converting thermal energy to kinetic energy, a process of pipeline resistance, a process related to flow and pressure, a process of converting electrical energy to cold or heat energy, a rectification process, an evaporation process, and a filtration process; this limitation is considered to merely link the judicial exception to a particular field of use and/or technological environment under step 2A prong II of the abstract idea analysis, see MPEP § 2106.05(h).
These limitations have been considered in combination with the limitations required by the claim(s) from which this claim depends. The additional limitations and/or additional elements do not integrate the claim limitations into a practical application (step 2A prong II), or recite significantly more than the abstract idea (step 2B). Therefore, claim 7 is ineligible under 35 U.S.C 101.
Regarding Claims 8-12, the claims recites substantially similar limitations to claims 1-5, respectively, and the claims are ineligible under 35 U.S.C 101 for the same reasons. The additional elements “first processing module,” “second processing module,” “third processing module,” “fourth processing module,” “fifth processing module,” “sixth processing module,” “first modeling module,” and “second modeling module” represent mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f), and the additional elements do not integrate the recited abstract idea into a practical application.
Regarding Claim 13, the claim recites substantially similar limitations to claim 1, and the claim is ineligible under 35 U.S.C 101 for the same reasons. The additional elements “memory,” “processor,” and “computer program” represent mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f), and the additional elements do not integrate the recited abstract idea into a practical application.
The following is an analysis of independent claim 14 based on the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG).
Step 1, Statutory Category:
No: Claim 14 is not directed to a patent eligible statutory category.
Claim 14 is directed to “computer-readable storage medium.” Under step 1 of the 35 U.S.C 101 analysis determining statutory category, the claim does not fall within at least one of the four categories of patent eligible subject matter, see MPEP § 2106.03. The claim is directed to a product lacking a physical or tangible structure in the form of an organizational structure, such as a computer program per se (often referred to as “software per se”). “Computer-readable storage medium” could be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. Therefore, the claim is ineligible under 35 U.S.C 101. Applicant may amend the claim to “A non-transitory computer-readable storage medium” to ensure that the claim is eligible under step 1. The claim otherwise recites substantially similar limitations to claim 1, and the claim is ineligible under 35 U.S.C 101 for the same reasons. The additional elements “computer-readable storage medium,” “computer program,” and “processor” represent mere instructions to apply the abstract idea on a computer as in MPEP § 2106.05(f), and the additional elements do not integrate the recited abstract idea into a practical application.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-4, 8-11, 13, and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (U.S. Pub. No. 2020/0247971 A1, filed June 15, 2019), hereinafter Yang, in view of Gallego et al. (Gallego, Guillermo, Daniel Berjón, and Narciso García. "Optimal polygonal L1 linearization and fast interpolation of nonlinear systems." IEEE Transactions on Circuits and Systems I: Regular Papers 61, no. 11 (2014): 3225-3234.), hereinafter Gallego, further in view of Eryilmaz et al. (U.S. Pub. No. 2007/0225951 A1), hereinafter Eryilmaz.
Regarding Claim 1, Yang teaches A linearization processing method for nonlinear models (“The present invention relates to the technical field of economic and optimized calculation of power systems, and in particular to a full-linear model for the optimal power flow of an integrated power and natural-gas system based on a deep learning method.”) (e.g., paragraph [0002]).
the method comprising: for a nonlinear model of each piece of physical equipment, determining a value range of each input parameter of the model (“Constraints for a power system are set, mainly including an electric power balance constraint, an active power constraint for a gas generator set, an active power constraint for a non-gas generator set and a power transmission line constraint.”) (e.g., paragraph [0044]).
and using the nonlinear model to obtain an output sample value combination corresponding to each input sample value combination (“A deep neural network, i.e., a Stacked Denoising automatic Encoder (SDAE) is established, as shown in FIG. 3 […] The electrical load and the gas load are input into the SDAE to obtain an output t.” Figure 3 discloses the output of the SDAE t as a vector, thus t is interpreted as an output sample value combination.) (e.g., figure 3 and paragraphs [0037] and [0040]).
However, Yang does not appear to specifically teach the method comprising dividing the value range of each input parameter into a plurality of subintervals based on a plurality of interpolation points; determining a plurality of input sample values in each subinterval by using equal division; traversing input sample value combinations of each input parameter of the model, […] and using all the input sample value combinations and the corresponding output sample value combinations to generate a tensor table.
On the other hand, Gallego, which relates similarly to nonlinear model linearization, does teach a method comprising dividing the value range of each input parameter into a plurality of subintervals based on a plurality of interpolation points (“In general, a piecewise function over an interval I=[a,b] is specified by two elements: a set of control or nodal points {xi}Ni=0, also called knots, that determine a partition T = {Ii}Ni=1 ] of I into a set of N (disjoint) subintervals Ii = [xi-1, xi].” The determined partitions are subintervals and the knots are interpolation points.) (e.g., page 2, column 1, paragraph 2).
determining a plurality of input sample values in each subinterval by using equal division(“A useful basis for vector space VT is formed by the set of nodal basis or hat functions {φi}Ni=0, where φi, displayed in Fig. 2, is the piecewise linear function in VT whose value is 1 at xi and zero at all other control points xj, [where j does not equal i].” Function φi(x) is interpreted as a plurality of input sample values within each subinterval i.) (e.g., page 2, column 1, paragraph 3).
traversing input sample value combinations of each input parameter of the model (“The polygonal interpolant πTf [included in] VT of a continuous function f (possibly not in VT) over the interval I linearly interpolates the samples of f at the control points.” Interpolating the continuous function f using the interpolant πTf is interpreted as traversing input sample value combinations. Further, “the previous method may be extended to handle vector valued nonlinear functions, i.e., functions with multiple values for the same x,” that is, multiple input sample value combinations of input parameters.) (e.g., page 2, column 3, paragraph 3).
However, neither Yang nor Gallego appears to teach using all the input sample value combinations and the corresponding output sample value combinations to generate a tensor table; and performing interpolation of the tensor table according to a current value of each input parameter to obtain a corresponding output value.
On the other hand, Eryilmaz, which relates to look-up table based simulation, does teach using all the input sample value combinations and the corresponding output sample value combinations to generate a tensor table (“The adaptive lookup table block 38 uses the input and output measurements of the plant behavior to create and update the contents of an underlying lookup table.” The lookup table is interpreted as a tensor table, wherein the input and output measurements may be the electrical/gas loads and SDAE vector output t from Yang.) (e.g., paragraph [0025]).
and performing interpolation of the tensor table according to a current value of each input parameter to obtain a corresponding output value (“The execution of the model during simulation causes adaptation algorithms defined for the block to begin learning the unknown values of the lookup table elements. These algorithms use the input and output measurements of the plant behavior to dynamically create and update the contents of the lookup table.” Learning the unknown output values is interpreted as interpolating output values.) (e.g., paragraph [0046]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine Yang with Gallego. The claimed invention is considered to be merely applying a known technique to a known method (device or product) ready for improvement to yield predictable results, see MPEP § 2143(I)(D). Yang teaches a method for building a constrained linear model for a power and natural-gas system using machine learning. However, Yang does not appear to specifically teach performing piecewise linearization that balances accuracy and complexity. On the other hand, Gallego does teach a method for piecewise linearization that balances accuracy and complexity. Furthermore, Yang discloses that a segmented linearization method is a conventional method to linearize nonlinear natural gas models to improve precision (e.g., Yang, paragraph [0043]). Thus, one of ordinary skill in the art would have recognized the method of Gallego as applicable to the method of Yang, and one of ordinary skill in the art would have been able to apply the linearization method of Gallego to the method of Yang to yield a predictable improvement in model accuracy. Therefore, it would have been obvious to a person of ordinary skill in the art to combine the piecewise linearization of Gallego with the power system model of Yang in order to optimize the complexity and error of the full linear model of Yang.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the Applicant's claimed invention to combine Yang with Eryilmaz. The claimed invention is considered to be merely combining prior art elements according to known methods to yield predictable results, see MPEP § 2143(I)(A). Yang teaches a method for modeling a power system. However, Yang does not appear to specifically teach creating a tensor table to correlate model inputs and outputs. On the other hand, Eryilmaz, which relates