000 04540nam a22006135i 4500
001 978-1-84628-184-6
003 DE-He213
005 20161121231017.0
007 cr nn 008mamaa
008 100301s2005 xxk| s |||| 0|eng d
020 _a9781846281846
_9978-1-84628-184-6
024 7 _a10.1007/1-84628-184-9
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aPalit, Ajoy K.
_eauthor.
245 1 0 _aComputational Intelligence in Time Series Forecasting
_h[electronic resource] :
_bTheory and Engineering Applications /
_cby Ajoy K. Palit, Dobrivoje Popovic.
264 1 _aLondon :
_bSpringer London,
_c2005.
300 _aXXII, 372 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Industrial Control,
_x1430-9491
505 0 _aComputational Intelligence: An Introduction -- Traditional Problem Definition -- Basic Intelligent Computational Technologies -- Neural Networks Approach -- Fuzzy Logic Approach -- Evolutionary Computation -- Hybrid Computational Technologies -- Neuro-fuzzy Approach -- Transparent Fuzzy/Neuro-fuzzy Modelling -- Evolving Neural and Fuzzy Systems -- Adaptive Genetic Algorithms -- Recent Developments -- State of the Art and Development Trends.
520 _aForesight in an engineering enterprise can make the difference between success and failure and can be vital to the effective control of industrial systems. Forecasting the future from accumulated historical data is a tried and tested method in areas such as engineering finance. Applying time series analysis in the on-line milieu of most industrial plants has been more problematic because of the time and computational effort required. The advent of soft computing tools such as the neural network and the genetic algorithm offers a solution. Chapter by chapter, Computational Intelligence in Time Series Forecasting harnesses the power of intelligent technologies individually and in combination. Examples of the particular systems and processes susceptible to each technique are investigated, cultivating a comprehensive exposition of the improvements on offer in quality, model building and predictive control, and the selection of appropriate tools from the plethora available; these include: • forecasting electrical load, chemical reactor behaviour and high-speed-network congestion using fuzzy logic; • prediction of airline passenger patterns and of output data for nonlinear plant with combination neuro-fuzzy networks; • evolutionary modelling and anticipation of stock performance by the use of genetic algorithms. Application-oriented engineers in process control, manufacturing, the production industries and research centres will find much to interest them in Computational Intelligence in Time Series Forecasting and the book is suitable for industrial training purposes. It will also serve as valuable reference material for experimental researchers. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 0 _aComputer simulation.
650 0 _aStatistics.
650 0 _aControl engineering.
650 0 _aRobotics.
650 0 _aMechatronics.
650 0 _aQuality control.
650 0 _aReliability.
650 0 _aIndustrial safety.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aSimulation and Modeling.
650 2 4 _aControl, Robotics, Mechatronics.
650 2 4 _aQuality Control, Reliability, Safety and Risk.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
700 1 _aPopovic, Dobrivoje.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781852339487
830 0 _aAdvances in Industrial Control,
_x1430-9491
856 4 0 _uhttp://dx.doi.org/10.1007/1-84628-184-9
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c507227
_d507227