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Run your analysis now →https://eureka.patsnap.com/resources/blog/rd-blog/evolutionary-algorithm-based-neural-network-weight-optimization-patent-landscape/ · Patsnap · data cut-off 2026-10-27 · downloaded from the live page
Patent Landscape · AI & Machine LearningEvolutionary Algorithm Based Neural Network Weight Optimization Patents
961 patent families and 1,333 records cover evolutionary and genetic algorithms tuning neural network weights and topology, led by one filer at 1.9% share.
1,333
Published Records
961
Simple Patent Families
2%
Families Naming the Largest Filer
30%
In Force at Cut-off
1,333 published records collapse into 961 simple (DOCDB) families; the difference is the same invention filed in more than one country. STATE GRID CORPORATION OF CHINA is named on 18 of the 961 patent families in scope. One patent family can name several filers, so these figures are not slices of a divided whole and do not add up. In force = 396 of 1,333 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
- 961 simple patent families and 1,333 published records sit inside this search. No date limit was applied, so this is every matching record the search string returned.
- State Grid Corporation of China is named on the most families here. 18 of 961 families (1.9%), with 30 of the 98 listed filers holding 2 or fewer families each.
- G06N carries the largest share of the technology split. 707 of 961 families (73.6%) classify under G06N, AI-model computing.
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview
What this search covers
This landscape pulls every record matching evolutionary algorithm or genetic algorithm combined with neural network or artificial neural network and weight or topology in the title, abstract or claims. No filing-date limit was applied, so the 961 simple patent families and 1,333 published records in scope span the full set the search string returns, not a fixed window of years. The filing-trend chart that follows shows a recent window only, and recent years are understated because of publication lag.
Across this pool, 396 of the 1,333 records (30%) were granted and still in force at the point of retrieval. The remainder are pending, withdrawn, refused, lapsed or not determinable, and that breakdown is not separated out further here.
Scope at a glance
Counted over all 1,333 published records, including filings from before 2007; the filing-trend chart below covers only the 1,184 records from 2007 onward, so the two charts are not the same set of documents. Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (2 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 30 of the 98 filers returned for this search; the data endpoint returns at most 100 entities, so even that 98 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.
Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
The Numbers
Filing activity and technology split
Two views of the same 961 families: how the filing record has moved over time, and which IPC subclasses the families classify under.
Filing trend by earliest filing year (1,184 of 1,333 published records)
Published records rose from 7 in 2007 to a peak of 149 in 2025, with filings of 89 in 2018 growing to 118 by 2021 (+33% over that span). 2022 onward is still filling in as records continue to publish, so that stretch should not be read as a decline.
Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two. This chart covers 2007-2026 (1,184 records); the 1,333 total quoted above includes earlier filings outside the window.
Technology composition by IPC subclass
G06N (AI-model computing) appears on 707 of 961 families (73.6%), G06F (digital data processing) on 381 (39.6%), and G06Q (business/admin data processing) on 228 (23.7%). Families can carry more than one subclass, so these shares add to more than 100%.
Shares are the percentage of the 961 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.
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A record from the result set
As Filed
Method for training a neural network
TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)
The disclosure relates to a computer-implemented method, system, apparatus and non-transitory computer readable media for training an artificial neural network (ANN). The method comprises defining an energy function, for the ANN and a dataset, in terms of quantum objects and simulating a quantum system, using the quantum objects, to reduce the energy function and obtain a trained ANN. The method may further comprise using the reduced energy function as an input to a genetic algorithm for refining the reduced energy function.This is the first record returned by the search under the database's default order, not a ranking by citations, breadth or date. It is shown to illustrate what a matching filing looks like, not as representative of the field.
Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.
Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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What the figures show
Three findings drawn directly from the filer list, the technology split and the legal-status snapshot.
Filer concentration
1.9%
largest single-row share
State Grid Corporation of China holds 18 of 961 families
State Grid Corporation of China is named on 18 of the 961 simple patent families in scope, a 1.9% share. 30 of the 98 listed filers hold 2 or fewer families each. Filer rows are not mutually exclusive, a family can name more than one filer, so these counts cannot be added together into a combined share.
Based on the 98 listed filers, ranked by family count.
Technology split
73.6%
of 961 families classify under G06N
G06N carries the largest share of the IPC mix
707 of the 961 families (73.6%) carry a G06N classification, covering AI-model computing. G06F follows at 381 families (39.6%) and G06Q at 228 families (23.7%). Families can carry several IPC subclasses at once, so these shares add to more than 100% and do not partition the dataset.
Counted across all 961 simple patent families in scope.
Legal status
30%
of 1,333 records granted and in force
396 of 1,333 records were in force at retrieval
396 of the 1,333 published records (30%) were granted and still in force at the point of data retrieval on 2026-10-27. The remaining 70% are pending, withdrawn, refused, lapsed or not determinable, and that split is not broken out further in this dataset. In-force status reflects a single point in time and changes continuously.
Status as recorded at retrieval; not a measure of claim strength.
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Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to evolutionary algorithm based neural network weight optimization patent landscape, with the prior art for and against each one.
Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Where To Go From Here
Next steps for a deeper read
The figures above describe what this search returned. Going further means reading specific families and claim sets rather than counts.
Read the granted claims that matter to you
A family count or an abstract cannot establish what a granted claim covers. Pull the claim set directly for any family that is close to a design under consideration.
Open Patsnap Eureka →Track the filers with the most families
Filer rows here are ordered by volume only and are not summed into a combined share. Following individual filers over time, rather than totals, is the way to see how any one of them is moving.
Explore filer activity in Patsnap Eureka →Watch how recent filings fill in
2022 onward is still publishing in, so the most useful recheck of this landscape is a repeat search run against a later retrieval date.
Set up monitoring in Patsnap Eureka →Source: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
Questions & Answers
Frequently asked questions
This search returns 961 simple patent families and 1,333 published records matching evolutionary or genetic algorithms combined with neural networks and weight or topology terms. The family count de-duplicates the same invention filed in multiple countries, while the record count counts each publication separately, so the two numbers measure different things. No date limit was applied to the search, so this set spans whatever years the matching records fall in, not a fixed window. Readers should treat the family figure as the closer proxy for distinct inventions and the record figure as a measure of publishing activity.
State Grid Corporation of China is named on 18 of the 961 families in scope, a 1.9% share, the largest single-row figure in the filer list. Below that, the list runs into a long tail: 30 of the 98 listed filers hold 2 or fewer families each. The filer list only contains organisations, counted separately with no roll-up to a parent corporate group, and because one family can name several filers, the rows cannot be summed into a combined concentration figure.
The largest IPC subclass is G06N, covering AI-model computing, which appears on 707 of 961 families (73.6%). G06F, digital data processing, follows at 381 families (39.6%), and G06Q, business and administrative data processing, at 228 families (23.7%). Because a single family can carry more than one classification, these shares add to more than 100% and should be read as overlapping coverage rather than a split of the whole set. The dataset includes 100 IPC subclasses in total, with these three carrying the largest shares by a wide margin over the rest.
Published records grew from 89 in 2018 to 118 in 2021, a 33% increase over that span, and the chart shows a peak of 149 records in 2025. Records from 2022 onward are still filling in because of publication lag, up to 18 months for most filing routes and up to 30 months where an application enters national phase via the PCT, so any apparent flattening or drop in those years reflects incomplete data, not an actual slowdown. 2021 is the most recent year that can be treated as reasonably complete for trend-reading purposes.
396 of the 1,333 published records (30%) were granted and still in force at the retrieval date of 2026-10-27. The remaining 70% fall into pending, withdrawn, refused, lapsed or not-determinable status, and this dataset does not break that remainder down further. In-force status is a snapshot at a single point in time, changes continuously as patents are maintained, abandoned or expire, and should not be read as any kind of success or quality rate.
Answers are grounded in the same dataset. Derived from one Patsnap search for Evolutionary Algorithm Based Neural Network Weight Optimization Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-27. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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How this page was built, and what the numbers do and do not mean
Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:
TAC:(("evolutionary algorithm" OR "genetic algorithm") AND ("neural network" OR "artificial neural network") AND (weight OR topology))Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06N) carries 73.6% of the patent families, so this search returned a classification-tight set.
What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 1,333 records and 961 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.
Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (2 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 30 of the 98 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 98 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included
Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in, and the growth figure stops at 2021. The data behind this page was retrieved on 2026-10-27.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (396 of 1,333). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka
Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level
Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.