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Multi step ahead forecasting of wind power by different class of neural networks

contributor authorSaroha, S. , Aggarwal, S.K.
date accessioned2020-03-12T19:39:51Z
date available2020-03-12T19:39:51Z
date issued2014
identifier other6799528.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/985389?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleMulti step ahead forecasting of wind power by different class of neural networks
typeConference Paper
contenttypeMetadata Only
identifier padid8101016
subject keywordsaxles
subject keywordsfatigue
subject keywordsreliability
subject keywordsroad vehicles
subject keywordsvehicle dynamics
subject keywordswheels
subject keywordsSimulink
subject keywordsacceleration load spectrum
subject keywordsboundary condition
subject keywordsnoise model
subject keywordspavement roughness characteristics
subject keywordsrain flow counting
subject keywordsroad roughness model
subject keywordsvehicle fatigue reliability evaluation
subject keywordsvehicle model
subject keywordsvehicle speed
subject keywordsvehicle speed effect
subject keywordswheel axle acceleration
subject keywordswheel axle pseudodamage
subject keywordsAxles
subject keywordsLoad modeling
subject keywordsMathematical model
subject keywordsRoads
subject keywordsVehicles
subject keywordsWheels
subject keywordsWhite noise
subject keywordspavement roughness
subject keywordspseudo damage
subject keywordsvehicle speed
subject keywordswheel axl
identifier doi10.1109/ITEC-AP.2014.6941133
journal titlengineering and Computational Sciences (RAECS), 2014 Recent Advances in
filesize1107509
citations0


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