{"id":"https://openalex.org/W2095592305","doi":"https://doi.org/10.1109/ijcnn.2004.1381133","title":"Visual comparison of performance for different activation functions in MLP networks","display_name":"Visual comparison of performance for different activation functions in MLP networks","publication_year":2005,"publication_date":"2005-02-28","ids":{"openalex":"https://openalex.org/W2095592305","doi":"https://doi.org/10.1109/ijcnn.2004.1381133","mag":"2095592305"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2004.1381133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021535335","display_name":"Filip Pi\u0229kniewski","orcid":null},"institutions":[{"id":"https://openalex.org/I3019271933","display_name":"Nicolaus Copernicus University","ror":"https://ror.org/0102mm775","country_code":"PL","type":"education","lineage":["https://openalex.org/I3019271933"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"F. Piekniewski","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland","Fac. of Math. & Comput. Sci., Nicolaus Copernicus Univ., Torun\u0301, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland","institution_ids":["https://openalex.org/I3019271933"]},{"raw_affiliation_string":"Fac. of Math. & Comput. Sci., Nicolaus Copernicus Univ., Torun\u0301, Poland","institution_ids":["https://openalex.org/I3019271933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067482168","display_name":"Leszek Rybicki","orcid":null},"institutions":[{"id":"https://openalex.org/I3019271933","display_name":"Nicolaus Copernicus University","ror":"https://ror.org/0102mm775","country_code":"PL","type":"education","lineage":["https://openalex.org/I3019271933"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"L. Rybicki","raw_affiliation_strings":["Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland","Fac. of Math. & Comput. Sci., Nicolaus Copernicus Univ., Torun\u0301, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland","institution_ids":["https://openalex.org/I3019271933"]},{"raw_affiliation_string":"Fac. of Math. & Comput. Sci., Nicolaus Copernicus Univ., Torun\u0301, Poland","institution_ids":["https://openalex.org/I3019271933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5021535335"],"corresponding_institution_ids":["https://openalex.org/I3019271933"],"apc_list":null,"apc_paid":null,"fwci":0.8775,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.80565366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"4","issue":null,"first_page":"2947","last_page":"2952"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/activation-function","display_name":"Activation function","score":0.9279785752296448},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.7606970071792603},{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.7560967206954956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7164307832717896},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5700480341911316},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5296292901039124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.474710613489151},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4722413718700409},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.47107258439064026},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42237481474876404},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32115596532821655}],"concepts":[{"id":"https://openalex.org/C38365724","wikidata":"https://www.wikidata.org/wiki/Q4677469","display_name":"Activation function","level":3,"score":0.9279785752296448},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.7606970071792603},{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.7560967206954956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7164307832717896},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5700480341911316},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5296292901039124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.474710613489151},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4722413718700409},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.47107258439064026},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42237481474876404},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32115596532821655},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2004.1381133","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2004.1381133","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1523750850","https://openalex.org/W1968621731","https://openalex.org/W2002011878","https://openalex.org/W2124776405","https://openalex.org/W2153255036","https://openalex.org/W2164016411","https://openalex.org/W2490948353","https://openalex.org/W3203117653","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3024979424","https://openalex.org/W4283785902","https://openalex.org/W2895192346","https://openalex.org/W3032499992","https://openalex.org/W2041004593","https://openalex.org/W3134817226","https://openalex.org/W3110577345","https://openalex.org/W2103292044","https://openalex.org/W2053362666","https://openalex.org/W4205825681"],"abstract_inverted_index":{"Multi":[0],"layer":[1],"perceptron":[2],"networks":[3],"have":[4,23,47],"been":[5,24],"successful":[6],"in":[7,16],"many":[8,13],"applications,":[9],"yet":[10],"there":[11],"are":[12],"unsolved":[14],"problems":[15],"the":[17,58],"theory.":[18],"Commonly,":[19],"sigmoidal":[20],"activation":[21,37,54],"functions":[22,55],"used,":[25],"giving":[26],"good":[27],"results.":[28],"The":[29],"backpropagation":[30],"algorithm":[31],"might":[32],"work":[33],"with":[34],"any":[35],"other":[36],"function":[38],"on":[39,62],"one":[40],"condition":[41],"though":[42],"-":[43],"it":[44],"has":[45],"to":[46],"a":[48],"differential.":[49],"We":[50],"investigate":[51],"some":[52,63],"possible":[53],"and":[56],"compare":[57],"results":[59],"they":[60],"give":[61],"sample":[64],"data":[65],"sets.":[66]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":4},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}