FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1674847193> ?p ?o ?g. }

• W1674847193 endingPage "15" @default.
• W1674847193 startingPage "1" @default.
• W1674847193 abstract "Optimizing a neural network's topology is a difficult problem for at least two reasons: the topology space is discrete, and the quality of any given topology must be assessed by assigning many different sets of weights to its connections. These two characteristics tend to cause very rough. objective functions. Here we demonstrate how self-assembly (SA) and particle swarm optimization (PSO) can be integrated to provide a novel and effective means of concurrently optimizing a neural network's weights and topology. Combining SA and PSO addresses two key challenges. First, it creates a more integrated representation of neural network weights and topology so that we have just a single, continuous search domain that permits smoother objective functions. Second, it extends the traditional focus of self-assembly, from the growth of predefined target structures, to functional self-assembly, in which growth is driven by optimality criteria defined in terms of the performance of emerging structures on predefined computational problems. Our model incorporates a new way of viewing PSO that involves a population of growing, interacting networks, as opposed to particles. The effectiveness of our method for optimizing echo state network weights and topologies is demonstrated through its performance on a number of challenging benchmark problems." @default.
• W1674847193 created "2016-06-24" @default.
• W1674847193 creator A5050009555 @default.
• W1674847193 creator A5079841116 @default.
• W1674847193 date "2015-01-01" @default.
• W1674847193 modified "2023-09-27" @default.
• W1674847193 title "Fusing Swarm Intelligence and Self-Assembly for Optimizing Echo State Networks" @default.
• W1674847193 cites W1888172398 @default.
• W1674847193 cites W1914190815 @default.
• W1674847193 cites W1978126533 @default.
• W1674847193 cites W1981429743 @default.
• W1674847193 cites W1981533780 @default.
• W1674847193 cites W1985123443 @default.
• W1674847193 cites W1995764737 @default.
• W1674847193 cites W1997007369 @default.
• W1674847193 cites W2002861841 @default.
• W1674847193 cites W2015304908 @default.
• W1674847193 cites W2022175477 @default.
• W1674847193 cites W2024805871 @default.
• W1674847193 cites W2030775133 @default.
• W1674847193 cites W2031645826 @default.
• W1674847193 cites W2033752463 @default.
• W1674847193 cites W2034424493 @default.
• W1674847193 cites W2041091946 @default.
• W1674847193 cites W2044459470 @default.
• W1674847193 cites W2050546928 @default.
• W1674847193 cites W2051680981 @default.
• W1674847193 cites W2066377545 @default.
• W1674847193 cites W2069507241 @default.
• W1674847193 cites W2091380950 @default.
• W1674847193 cites W2097490641 @default.
• W1674847193 cites W2099251346 @default.
• W1674847193 cites W2102236449 @default.
• W1674847193 cites W2102506086 @default.
• W1674847193 cites W2105563853 @default.
• W1674847193 cites W2110935965 @default.
• W1674847193 cites W2118051273 @default.
• W1674847193 cites W2118706537 @default.
• W1674847193 cites W2125314042 @default.
• W1674847193 cites W2127826644 @default.
• W1674847193 cites W2128033389 @default.
• W1674847193 cites W2135951444 @default.
• W1674847193 cites W2142668830 @default.
• W1674847193 cites W2144317842 @default.
• W1674847193 cites W2148111848 @default.
• W1674847193 cites W2149156031 @default.
• W1674847193 cites W2154788940 @default.
• W1674847193 cites W2155084532 @default.
• W1674847193 cites W2156023754 @default.
• W1674847193 cites W2164531580 @default.
• W1674847193 cites W2172120796 @default.
• W1674847193 doi "https://doi.org/10.1155/2015/642429" @default.
• W1674847193 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4539438" @default.
• W1674847193 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26346488" @default.
• W1674847193 hasPublicationYear "2015" @default.
• W1674847193 type Work @default.
• W1674847193 sameAs 1674847193 @default.
• W1674847193 citedByCount "4" @default.
• W1674847193 countsByYear W16748471932016 @default.
• W1674847193 countsByYear W16748471932018 @default.
• W1674847193 countsByYear W16748471932019 @default.
• W1674847193 countsByYear W16748471932020 @default.
• W1674847193 crossrefType "journal-article" @default.
• W1674847193 hasAuthorship W1674847193A5050009555 @default.
• W1674847193 hasAuthorship W1674847193A5079841116 @default.
• W1674847193 hasBestOaLocation W16748471931 @default.
• W1674847193 hasConcept C111919701 @default.
• W1674847193 hasConcept C11413529 @default.
• W1674847193 hasConcept C114614502 @default.
• W1674847193 hasConcept C119487961 @default.
• W1674847193 hasConcept C120665830 @default.
• W1674847193 hasConcept C121332964 @default.
• W1674847193 hasConcept C127413603 @default.
• W1674847193 hasConcept C13280743 @default.
• W1674847193 hasConcept C134306372 @default.
• W1674847193 hasConcept C135628077 @default.
• W1674847193 hasConcept C154945302 @default.
• W1674847193 hasConcept C17744445 @default.
• W1674847193 hasConcept C181335050 @default.
• W1674847193 hasConcept C184720557 @default.
• W1674847193 hasConcept C185798385 @default.
• W1674847193 hasConcept C189216461 @default.
• W1674847193 hasConcept C192209626 @default.
• W1674847193 hasConcept C199539241 @default.
• W1674847193 hasConcept C199845137 @default.
• W1674847193 hasConcept C205649164 @default.
• W1674847193 hasConcept C26517878 @default.
• W1674847193 hasConcept C2776359362 @default.
• W1674847193 hasConcept C33923547 @default.
• W1674847193 hasConcept C36503486 @default.
• W1674847193 hasConcept C38652104 @default.
• W1674847193 hasConcept C41008148 @default.
• W1674847193 hasConcept C50644808 @default.
• W1674847193 hasConcept C66938386 @default.
• W1674847193 hasConcept C85617194 @default.
• W1674847193 hasConcept C94625758 @default.
• W1674847193 hasConceptScore W1674847193C111919701 @default.
• W1674847193 hasConceptScore W1674847193C11413529 @default.

• next