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003			KUKTEM
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007			cr un ---uuuua
008			100804t2009 paua fsb 001 0 eng d
020			_a9781599048987 (electronic book)
020			_a9781599048970
039		9	_a201107131913 _bVLOAD _c201104221149 _dFida _c201008101151 _dida _c201008050900 _dida _y201008041124 _zida
040			_aUMP
090			_aHG106 .A78 2009
245	0	0	_aArtificial higher order neural networks for economics and business _h[electronic resource] / _cMing Zhang, editor
260			_aHershey, Pa. : _bInformation Science Reference, _cc2009
440		0	_aGale virtual reference library
504			_aIncludes bibliographical references and index
505	0		_aArtificial higher order neural network nonlinear models: SAS NLIN or HONNs? -- Higher order neural networks with Bayesian confidence measure for the prediction of the EUR/USD exchange rate -- Automatically identifying predictor variables for stock return prediction -- Higher order neural network architectures for agent-based computational economics and finance -- Foreign exchange rate forecasting using higher order flexible neural tree -- Higher order neural networks for stock index modeling -- Ultra high frequency trigonometric higher order neural networks for time series data analysis -- Artificial higher order pipeline recurrent neural networks for financial time series prediction -- A novel recurrent polynomial neural network for financial time series prediction -- Generalized correlation higher order neural networks for financial time series prediction -- Artificial higher order neural networks in time series prediction -- Application of pi-sigma neural networks and ridge polynomial neural networks to financial time series prediction -- Electric load demand and electricity prices forecasting using higher order neural networks trained by Kalman filtering -- Adaptive higher order neural network models and their applications in business -- CEO tenure and debt: an artificial higher order neural network approach -- Modelling and trading the soybean-oil crush spread with recurrent and higher order networks: a comparative analysis -- Fundamental theory of artificial higher order neural networks -- Dynamics in artificial higher order neural networks with delays -- A new topology for artificial higher order neural networks: polynomial kernel networks -- High speed optical higher order neural networks for discovering data trends and patterns in very large databases -- On complex artificial higher order neural networks: dealing with stochasticity, jumps and delays -- Trigonometric polynomial higher order neural network group models and weighted kernel models for financial data simulation and prediction.
520			_aProvides significant, informative advancements in the subject and introduces the concepts of HONN group models and adaptive HONNs
533			_aElectronic reproduction. _bFarmington Hills, Mi : _cGale. _nAvailable via World Wide Web
534			_pOriginal: _exxiii, 517 p. : ill. ; 29 cm.
538			_aMode of access: Internet
650		0	_aFinance _xComputer simulation
650		0	_aFinance _xMathematical models
650		0	_aFinance _xComputer programs
650		0	_aNeural networks (Computer science)
700	1		_aZhang, Ming
856	4	0	_uhttp://find.galegroup.com.libraryumpsa.idm.oclc.org/openurl/openurl?url_ver=Z39.88-2004&url_ctx_fmt=info:ofi/fmt:kev:mtx:ctx&req_dat=info:sid/gale:ugnid:myump&res_id=info:sid/gale:GVRL&ctx_enc=info:ofi:enc:UTF-8&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft_id=info:sid/gale:bmcode:recid/2RAV _zAvailable for Universiti Malaysia Pahang via Gale Virtual Reference Library. Click here to access
999			_aVIRTUA40 _c16468 _d16474
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