000752881 000__ 02827cam\a2200493Mi\4500 000752881 001__ 752881 000752881 005__ 20230306141439.0 000752881 006__ m\\\\\o\\d\\\\\\\\ 000752881 007__ cr\nn\nnnunnun 000752881 008__ 151122s2016\\\\gw\\\\\\od\\\\000\0\eng\d 000752881 019__ $$a932002885 000752881 020__ $$a9783319262932$$q(electronic book) 000752881 020__ $$a3319262939$$q(electronic book) 000752881 020__ $$z9783319262925 000752881 020__ $$z3319262920 000752881 0247_ $$a10.1007/978-3-319-26293-2$$2doi 000752881 035__ $$aSP(OCoLC)ocn932170298 000752881 035__ $$aSP(OCoLC)932170298$$z(OCoLC)932002885 000752881 040__ $$aNUI$$beng$$cNUI$$dOCLCO$$dAZU$$dCOO$$dOCLCF$$dGW5XE$$dYDXCP$$dCUI 000752881 049__ $$aISEA 000752881 050_4 $$aQ342 000752881 08204 $$a006.3$$223 000752881 1001_ $$aSingh, Pritpal$$c(Lecturer in computer science),$$eauthor. 000752881 24510 $$aApplications of soft computing in time series forecasting$$h[electronic resource] :$$bsimulation and modeling techniques /$$cPritpal Singh. 000752881 264_1 $$aCham :$$bSpringer,$$c2016. 000752881 300__ $$a1 online resource (xxi, 158 pages) :$$billustrations. 000752881 336__ $$atext$$btxt$$2rdacontent 000752881 337__ $$acomputer$$bc$$2rdamedia 000752881 338__ $$aonline resource$$bcr$$2rdacarrier 000752881 347__ $$atext file$$bPDF$$2rda 000752881 4901_ $$aStudies in Fuzziness and Soft Computing,$$x1434-9922 ;$$vv. 330 000752881 506__ $$aAccess limited to authorized users. 000752881 520__ $$aThis book reports on an in-depth study of fuzzy time series (FTS) modeling. It reviews and summarizes previous research work in FTS modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and evolutionary computing (EC), focusing on how these techniques can be integrated into different phases of the FTS modeling approach. In particular, the book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization. It also demonstrates how a new ANN-based model can be successfully applied in the context of predicting Indian summer monsoon rainfall. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to fuzzy time series modeling, and will be valuable not only for graduate students, but also for researchers and professionals working for academic, business and government organizations. . 000752881 650_0 $$aEngineering. 000752881 650_0 $$aArtificial intelligence. 000752881 650_0 $$aComputer simulation. 000752881 650_0 $$aStatistical physics. 000752881 650_0 $$aComputational intelligence. 000752881 77608 $$iPrint version:$$z9783319262925 000752881 830_0 $$aStudies in fuzziness and soft computing ;$$v330. 000752881 852__ $$bebk 000752881 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-26293-2$$zOnline Access$$91397441.1 000752881 909CO $$ooai:library.usi.edu:752881$$pGLOBAL_SET 000752881 980__ $$aEBOOK 000752881 980__ $$aBIB 000752881 982__ $$aEbook 000752881 983__ $$aOnline 000752881 994__ $$a92$$bISE