Novel back propagation optimization by Cuckoo Search algorithm.
The traditional Back Propagation (BP) has some significant disadvantages, such as training too slowly, easiness to fall into local minima, and sensitivity of the initial weights and bias. In order to overcome these shortcomings, an improved BP network that is optimized by Cuckoo Search (CS), called...
| Publicado en: | Scientific World Journal pp. 878262 - 878263 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103834300&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103834300 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1537744X 1BX5 jtl: Scientific World Journal issn: 1537744X maglogo: N pubinfo: dt: 2014 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 103834300 103834300 NLM25028682 2012650695 10.1155/2014/878262 NLM25028682 PMC3980988 103834300 ppf: 878262 ppct: 1 formats: tig: atl: Novel back propagation optimization by Cuckoo Search algorithm. aug: au: Yi, Jiao-Hong Xu, Wei-Hong Chen, Yuan-Tao affil: School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, Hunan 410014, China. sug: subj: Algorithms Models, Theoretical Neural Networks (Computer) ab: The traditional Back Propagation (BP) has some significant disadvantages, such as training too slowly, easiness to fall into local minima, and sensitivity of the initial weights and bias. In order to overcome these shortcomings, an improved BP network that is optimized by Cuckoo Search (CS), called CSBP, is proposed in this paper. In CSBP, CS is used to simultaneously optimize the initial weights and bias of BP network. Wine data is adopted to study the prediction performance of CSBP, and the proposed method is compared with the basic BP and the General Regression Neural Network (GRNN). Moreover, the parameter study of CSBP is conducted in order to make the CSBP implement in the best way. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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