Automatic generation of neural network architecture using evolutionary computation:
This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network archi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Singapore
World Scientific Pub. Co.
c1997
|
| Schriftenreihe: | Advances in fuzzy systems--Applications and theory
v. 14 |
| Schlagworte: | |
| Online-Zugang: | FHN01 URL des Erstveroeffentlichers |
| Zusammenfassung: | This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation. An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated |
| Beschreibung: | x, 182 p. ill |
| ISBN: | 9789814366441 |
Internformat
MARC
| LEADER | 00000nmm a2200000zcb4500 | ||
|---|---|---|---|
| 001 | BV044638709 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 171120s1997 |||| o||u| ||||||eng d | ||
| 020 | |a 9789814366441 |9 978-981-4366-44-1 | ||
| 024 | 7 | |a 10.1142/3449 |2 doi | |
| 035 | |a (ZDB-124-WOP)00004957 | ||
| 035 | |a (OCoLC)1012659047 | ||
| 035 | |a (DE-599)BVBBV044638709 | ||
| 040 | |a DE-604 |b ger |e aacr | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-92 | ||
| 082 | 0 | |a 006.3/2 |2 22 | |
| 084 | |a ST 285 |0 (DE-625)143648: |2 rvk | ||
| 100 | 1 | |a Vonk, E. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Automatic generation of neural network architecture using evolutionary computation |c E. Vonk, L.C. Jain, R.P. Johnson |
| 264 | 1 | |a Singapore |b World Scientific Pub. Co. |c c1997 | |
| 300 | |a x, 182 p. |b ill | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 490 | 0 | |a Advances in fuzzy systems--Applications and theory |v v. 14 | |
| 520 | |a This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation. An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated | ||
| 650 | 4 | |a Neural networks (Computer science) | |
| 650 | 4 | |a Computer architecture | |
| 650 | 4 | |a Evolutionary computation | |
| 650 | 0 | 7 | |a Neuronales Netz |0 (DE-588)4226127-2 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Neuronales Netz |0 (DE-588)4226127-2 |D s |
| 689 | 0 | |8 1\p |5 DE-604 | |
| 700 | 1 | |a Jain, L. C. |e Sonstige |4 oth | |
| 700 | 1 | |a Johnson, R. P. |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9789810231064 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 9810231067 |
| 856 | 4 | 0 | |u http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc |x Verlag |z URL des Erstveroeffentlichers |3 Volltext |
| 912 | |a ZDB-124-WOP | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-030036682 | ||
| 883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
| 966 | e | |u http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc |l FHN01 |p ZDB-124-WOP |q FHN_PDA_WOP |x Verlag |3 Volltext | |
Datensatz im Suchindex
| _version_ | 1804178055882604544 |
|---|---|
| any_adam_object | |
| author | Vonk, E. |
| author_facet | Vonk, E. |
| author_role | aut |
| author_sort | Vonk, E. |
| author_variant | e v ev |
| building | Verbundindex |
| bvnumber | BV044638709 |
| classification_rvk | ST 285 |
| collection | ZDB-124-WOP |
| ctrlnum | (ZDB-124-WOP)00004957 (OCoLC)1012659047 (DE-599)BVBBV044638709 |
| dewey-full | 006.3/2 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/2 |
| dewey-search | 006.3/2 |
| dewey-sort | 16.3 12 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03037nmm a2200493zcb4500</leader><controlfield tag="001">BV044638709</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">171120s1997 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9789814366441</subfield><subfield code="9">978-981-4366-44-1</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1142/3449</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-124-WOP)00004957</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1012659047</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV044638709</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-92</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">006.3/2</subfield><subfield code="2">22</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 285</subfield><subfield code="0">(DE-625)143648:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Vonk, E.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Automatic generation of neural network architecture using evolutionary computation</subfield><subfield code="c">E. Vonk, L.C. Jain, R.P. Johnson</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Singapore</subfield><subfield code="b">World Scientific Pub. Co.</subfield><subfield code="c">c1997</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">x, 182 p.</subfield><subfield code="b">ill</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Advances in fuzzy systems--Applications and theory</subfield><subfield code="v">v. 14</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation. An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Neural networks (Computer science)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer architecture</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Evolutionary computation</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Neuronales Netz</subfield><subfield code="0">(DE-588)4226127-2</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Neuronales Netz</subfield><subfield code="0">(DE-588)4226127-2</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Jain, L. C.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Johnson, R. P.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9789810231064</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">9810231067</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveroeffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-124-WOP</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-030036682</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-124-WOP</subfield><subfield code="q">FHN_PDA_WOP</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV044638709 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:57:54Z |
| institution | BVB |
| isbn | 9789814366441 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030036682 |
| oclc_num | 1012659047 |
| open_access_boolean | |
| owner | DE-92 |
| owner_facet | DE-92 |
| physical | x, 182 p. ill |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 1997 |
| publishDateSearch | 1997 |
| publishDateSort | 1997 |
| publisher | World Scientific Pub. Co. |
| record_format | marc |
| series2 | Advances in fuzzy systems--Applications and theory |
| spelling | Vonk, E. Verfasser aut Automatic generation of neural network architecture using evolutionary computation E. Vonk, L.C. Jain, R.P. Johnson Singapore World Scientific Pub. Co. c1997 x, 182 p. ill txt rdacontent c rdamedia cr rdacarrier Advances in fuzzy systems--Applications and theory v. 14 This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation. An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated Neural networks (Computer science) Computer architecture Evolutionary computation Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 s 1\p DE-604 Jain, L. C. Sonstige oth Johnson, R. P. Sonstige oth Erscheint auch als Druck-Ausgabe 9789810231064 Erscheint auch als Druck-Ausgabe 9810231067 http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc Verlag URL des Erstveroeffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Vonk, E. Automatic generation of neural network architecture using evolutionary computation Neural networks (Computer science) Computer architecture Evolutionary computation Neuronales Netz (DE-588)4226127-2 gnd |
| subject_GND | (DE-588)4226127-2 |
| title | Automatic generation of neural network architecture using evolutionary computation |
| title_auth | Automatic generation of neural network architecture using evolutionary computation |
| title_exact_search | Automatic generation of neural network architecture using evolutionary computation |
| title_full | Automatic generation of neural network architecture using evolutionary computation E. Vonk, L.C. Jain, R.P. Johnson |
| title_fullStr | Automatic generation of neural network architecture using evolutionary computation E. Vonk, L.C. Jain, R.P. Johnson |
| title_full_unstemmed | Automatic generation of neural network architecture using evolutionary computation E. Vonk, L.C. Jain, R.P. Johnson |
| title_short | Automatic generation of neural network architecture using evolutionary computation |
| title_sort | automatic generation of neural network architecture using evolutionary computation |
| topic | Neural networks (Computer science) Computer architecture Evolutionary computation Neuronales Netz (DE-588)4226127-2 gnd |
| topic_facet | Neural networks (Computer science) Computer architecture Evolutionary computation Neuronales Netz |
| url | http://www.worldscientific.com/worldscibooks/10.1142/3449#t=toc |
| work_keys_str_mv | AT vonke automaticgenerationofneuralnetworkarchitectureusingevolutionarycomputation AT jainlc automaticgenerationofneuralnetworkarchitectureusingevolutionarycomputation AT johnsonrp automaticgenerationofneuralnetworkarchitectureusingevolutionarycomputation |