?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Modelling+and+control+of+chaotic+processes%0Athrough+their+Bifurcation+Diagrams+generated%0Awith+the+help+of+Recurrent+Neural+Networks%0Amodels+Part+2+-+Industrial+Study&rft.creator=Jallu%2C+Krishnaiah&rft.creator=Kumar%2C+C.S.&rft.creator=Faruqi%2C+M.A.&rft.subject=Dynamical+Systems&rft.subject=Machine+Learning&rft.subject=Neural+Nets&rft.description=Many+real-world+processes+tend+to+be+chaotic+and+are+not+amenable+to+satisfactory%0Aanalytical+models.+It+has+been+shown+here+that+for+such+chaotic+processes+represented%0Athrough+short+chaotic+noisy+observed+data%2C+a+multi-input+and+multi-output+recurrent%0Aneural+network+can+be+built+which+is+capable+of+capturing+the+process+trends+and%0Apredicting+the+behaviour+for+any+given+starting+condition.+It+is+further+shown+that%0Athis+capability+can+be+achieved+by+the+recurrent+neural+network+model+when+it+is%0Atrained+to+very+low+value+of+mean+squared+error.+Such+a+model+can+then+be+used%0Afor+constructing+the+Bifurcation+Diagram+of+the+process+leading+to+determination%0Aof+desirable+operating+conditions.+Further%2C+this+multi-input+and+multi-output+model%0Amakes+the+process+accessible+for+control+using+open-loop+%2F+closed-loop+approaches%0Aor+bifurcation+control+etc.&rft.publisher=Elsevier&rft.date=2006-01&rft.type=Journal+(Paginated)&rft.type=PeerReviewed&rft.format=application%2Fpdf&rft.identifier=http%3A%2F%2Fcogprints.org%2F4881%2F1%2Fjpc-maf2.pdf&rft.identifier=++Jallu%2C+Krishnaiah+and+Kumar%2C+C.S.+and+Faruqi%2C+M.A.++(2006)+Modelling+and+control+of+chaotic+processes+through+their+Bifurcation+Diagrams+generated+with+the+help+of+Recurrent+Neural+Networks+models+Part+2+-+Industrial+Study.++%5BJournal+(Paginated)%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F4881%2F