Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387216956> ?p ?o ?g. }
Showing items 1 to 61 of
61
with 100 items per page.
- W4387216956 abstract "In computer science, non-deterministic polynomialtime
 (NP) denotes the set of problems for which a
 solution might or might not be found quickly but can
 be checked quickly. We also call the set of problems
 in NP that are at least as hard as any other NP problem
 non-deterministic polynomial-time complete (NPcomplete).
 Although not known if they can be solved
 quickly, NP-complete problems can be converted
 into one another quickly. A prominent and practical
 example is the protein folding problem, which is a
 problem of determining the shape and function of
 proteins. In this paper, we discovered and provided
 a mathematical proof of a new NP-complete problem,
 that we named 3-Grid Pattern Decision Problem (3-
 GPDP). 3-GPDP is a decision problem that asks if a
 specific kind of pattern exists or not on a grid/matrix
 of numbers consisting of zeros and ones, much like
 image recognition. We hypothesized that a neural net
 would be able to solve 3-GPDP problems with high
 accuracy and low loss when trained. In support of
 our hypothesis, our experiment resulted in a neural
 net that performed with 84% accuracy and 0.14 loss
 without underfitting or overfitting. Moreover, there
 was also an increase in accuracy and decrease in
 loss with more training data. As a result, since neural
 networks are effective at solving 3-GPDP problems,
 which are NP-complete, then we can convert important
 NP-complete problems into 3-GPDP problems, solve
 the 3-GPDP problems using neural networks, and
 convert the solution back to the solution of the initial
 problem, quickly." @default.
- W4387216956 created "2023-10-01" @default.
- W4387216956 creator A5007174775 @default.
- W4387216956 creator A5047918186 @default.
- W4387216956 date "2023-01-01" @default.
- W4387216956 modified "2023-10-01" @default.
- W4387216956 title "Solving a new NP-Complete problem that resembles image pattern recognition using deep learning" @default.
- W4387216956 doi "https://doi.org/10.59720/21-014" @default.
- W4387216956 hasPublicationYear "2023" @default.
- W4387216956 type Work @default.
- W4387216956 citedByCount "0" @default.
- W4387216956 crossrefType "journal-article" @default.
- W4387216956 hasAuthorship W4387216956A5007174775 @default.
- W4387216956 hasAuthorship W4387216956A5047918186 @default.
- W4387216956 hasBestOaLocation W43872169561 @default.
- W4387216956 hasConcept C11413529 @default.
- W4387216956 hasConcept C115961682 @default.
- W4387216956 hasConcept C14036430 @default.
- W4387216956 hasConcept C153180895 @default.
- W4387216956 hasConcept C154945302 @default.
- W4387216956 hasConcept C177264268 @default.
- W4387216956 hasConcept C187691185 @default.
- W4387216956 hasConcept C199360897 @default.
- W4387216956 hasConcept C22019652 @default.
- W4387216956 hasConcept C2524010 @default.
- W4387216956 hasConcept C33923547 @default.
- W4387216956 hasConcept C41008148 @default.
- W4387216956 hasConcept C50644808 @default.
- W4387216956 hasConcept C78458016 @default.
- W4387216956 hasConcept C86803240 @default.
- W4387216956 hasConceptScore W4387216956C11413529 @default.
- W4387216956 hasConceptScore W4387216956C115961682 @default.
- W4387216956 hasConceptScore W4387216956C14036430 @default.
- W4387216956 hasConceptScore W4387216956C153180895 @default.
- W4387216956 hasConceptScore W4387216956C154945302 @default.
- W4387216956 hasConceptScore W4387216956C177264268 @default.
- W4387216956 hasConceptScore W4387216956C187691185 @default.
- W4387216956 hasConceptScore W4387216956C199360897 @default.
- W4387216956 hasConceptScore W4387216956C22019652 @default.
- W4387216956 hasConceptScore W4387216956C2524010 @default.
- W4387216956 hasConceptScore W4387216956C33923547 @default.
- W4387216956 hasConceptScore W4387216956C41008148 @default.
- W4387216956 hasConceptScore W4387216956C50644808 @default.
- W4387216956 hasConceptScore W4387216956C78458016 @default.
- W4387216956 hasConceptScore W4387216956C86803240 @default.
- W4387216956 hasLocation W43872169561 @default.
- W4387216956 hasOpenAccess W4387216956 @default.
- W4387216956 hasPrimaryLocation W43872169561 @default.
- W4387216956 hasRelatedWork W2372980479 @default.
- W4387216956 hasRelatedWork W2742991909 @default.
- W4387216956 hasRelatedWork W2767651786 @default.
- W4387216956 hasRelatedWork W2950186470 @default.
- W4387216956 hasRelatedWork W2989932438 @default.
- W4387216956 hasRelatedWork W3099765033 @default.
- W4387216956 hasRelatedWork W3110382310 @default.
- W4387216956 hasRelatedWork W3110700750 @default.
- W4387216956 hasRelatedWork W3165925361 @default.
- W4387216956 hasRelatedWork W4387162238 @default.
- W4387216956 isParatext "false" @default.
- W4387216956 isRetracted "false" @default.
- W4387216956 workType "article" @default.