{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T14:35:56Z","timestamp":1725978956612},"reference-count":23,"publisher":"Cambridge University Press (CUP)","issue":"5","license":[{"start":{"date-parts":[[2014,9,4]],"date-time":"2014-09-04T00:00:00Z","timestamp":1409788800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Math. Struct. Comp. Sci."],"published-print":{"date-parts":[[2014,10]]},"abstract":"<jats:p>Wind power projects face an uncertain external environment, they are complex projects in themselves and the capabilities of the designers, erectors and operators are limited. All this makes the identification of investment risks for wind power projects extremely complicated. In this paper, we propose a method for identifying the investment risk scientifically and accurately using a back propagation (BP) neural network. Specifically, we propose a hybrid wavelet transform fuzzy BP neural network (WT-FBPNN) optimisation model based on the construction of a risk evaluating index system. This improved model can not only exploit the time frequency localisation characteristic of wavelet transforms (WT), but also enhance the fit precision and algorithm convergence speed. The simulation results show that this model is reliable, and that this method of identifying the investment risk of wind power projects is feasible.<\/jats:p>","DOI":"10.1017\/s0960129513000832","type":"journal-article","created":{"date-parts":[[2014,9,4]],"date-time":"2014-09-04T20:08:51Z","timestamp":1409861331000},"source":"Crossref","is-referenced-by-count":1,"title":["A hybrid WT-FBPNN optimisation algorithm to identify the investment risk of wind power projects"],"prefix":"10.1017","volume":"24","author":[{"given":"ZHIBIN","family":"LIU","sequence":"first","affiliation":[]},{"given":"AISHENG","family":"REN","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2014,9,4]]},"reference":[{"key":"S0960129513000832_ref22","first-page":"43","article-title":"Risk assessment of information security using fuzzy wavelet neural network","volume":"37","author":"Zhao","year":"2009","journal-title":"Journal Huazhong University of Science and Technology (Natural Science Edition)"},{"key":"S0960129513000832_ref10","unstructured":"Li X. and Xu W. (2006) The model and application about the enterprise payoff ability evaluation based on the improved BP neural network. Industrial Technology Economy 92\u201396."},{"key":"S0960129513000832_ref20","first-page":"78","article-title":"Traffic pattern identification of elevator group control system based on GA-BP fuzzy neural network","author":"Zhang","year":"2008","journal-title":"Micromachine"},{"key":"S0960129513000832_ref8","first-page":"96","article-title":"Application of F-ANP in risk evaluation of offshore wind power projects","volume":"30","author":"Li","year":"2001","journal-title":"Journal of Liaoning Technical University (Natural Science)"},{"key":"S0960129513000832_ref1","first-page":"84","article-title":"Research on investment risk of electricity generation project in electricity market","volume":"23","author":"Ding","year":"2006","journal-title":"Modern Electric Power"},{"key":"S0960129513000832_ref18","first-page":"43","article-title":"Research of fuzzy wavelet neural network and its application","author":"Wang","year":"2008","journal-title":"Industry and Mine Automation"},{"key":"S0960129513000832_ref15","doi-asserted-by":"publisher","DOI":"10.1109\/72.554194"},{"key":"S0960129513000832_ref12","doi-asserted-by":"publisher","DOI":"10.1109\/59.708643"},{"key":"S0960129513000832_ref23","first-page":"102","article-title":"The application research and improvement of the enterprise comprehensive performance evaluation based on BP neural network","author":"Zhao","year":"2005","journal-title":"Industrial Engineering Journal"},{"key":"S0960129513000832_ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TCS.1986.1085953"},{"key":"S0960129513000832_ref21","first-page":"62","article-title":"The project investment risk evaluation based on the BP neural network","author":"Zhao","year":"2006","journal-title":"Construction Economy"},{"key":"S0960129513000832_ref19","first-page":"34","article-title":"Fuzzy synthetic evaluation for technological innovation capability of an enterprise based on wavelet neural network","volume":"26","author":"Wang","year":"2007","journal-title":"Technology Economics"},{"key":"S0960129513000832_ref2","first-page":"84","article-title":"Application of neuro-fuzzy network forecasting with wavelet theory","volume":"28","author":"Dong","year":"2000","journal-title":"Journal of Henan Normal University (Natural Science)"},{"key":"S0960129513000832_ref13","first-page":"188","article-title":"Neural network application to state estimation computation","volume":"9","author":"Nakagawa","year":"1991","journal-title":"IEEE Transactions on Circuits and Systems"},{"key":"S0960129513000832_ref16","first-page":"24","article-title":"New short-term load forecasting principle with the wavelet transform fuzzy neural network for the power systems","volume":"24","author":"Tai","year":"2004","journal-title":"Proceedings of the CSEE"},{"key":"S0960129513000832_ref7","doi-asserted-by":"publisher","DOI":"10.1109\/72.572090"},{"key":"S0960129513000832_ref3","first-page":"918","article-title":"Observer-participant model of neural processing","volume":"16","author":"Fry","year":"1997","journal-title":"IEEE Transactions on Neural Networks"},{"key":"S0960129513000832_ref11","doi-asserted-by":"publisher","DOI":"10.1007\/BF00871937"},{"key":"S0960129513000832_ref5","first-page":"605","article-title":"The credit evaluation system research based on improved BP neural network","volume":"27","author":"He","year":"2006","journal-title":"Computer Engineering and Design"},{"key":"S0960129513000832_ref4","first-page":"130","article-title":"Study on hydrological forecasting based on wavelet-fuzzy neural networks","volume":"33","author":"Guo","year":"2005","journal-title":"Journal of Tongji University (Natural Science)"},{"key":"S0960129513000832_ref6","doi-asserted-by":"publisher","DOI":"10.1016\/0169-2070(94)90045-0"},{"key":"S0960129513000832_ref9","first-page":"55","article-title":"Evaluation of project investment risk based on BP neural network","author":"Li","year":"2005","journal-title":"Journal of Hohai University Changzhou"},{"key":"S0960129513000832_ref14","first-page":"80","article-title":"Comprehensive evaluation on sustainable development for electric power industry based on improved BP neural network model","volume":"33","author":"Ren","year":"2006","journal-title":"Journal of North China Electric Power University"}],"container-title":["Mathematical Structures in Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0960129513000832","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,21]],"date-time":"2019-04-21T20:22:08Z","timestamp":1555878128000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0960129513000832\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9,4]]},"references-count":23,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2014,10]]}},"alternative-id":["S0960129513000832"],"URL":"https:\/\/doi.org\/10.1017\/s0960129513000832","relation":{},"ISSN":["0960-1295","1469-8072"],"issn-type":[{"value":"0960-1295","type":"print"},{"value":"1469-8072","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,9,4]]},"article-number":"e240503"}}