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020 _a9789819757183
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024 7 _a10.1007/978-981-97-5718-3
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
245 1 0 _aIntelligent Methods in Electrical Power Systems
_h[electronic resource] /
_cedited by Chetan B. Khadse, Ishaan R. Kale, Apoorva S. Shastri.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIII, 171 p. 100 illus., 79 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aEngineering Optimization: Methods and Applications,
_x2731-4057
505 0 _aReview on intelligent methods in Electrical power systems -- Investigation of Electric Load Forecasting Methods: A Weka Application (Regression and Optimization) -- Integration of Intelligent Systems for Efficient Smart Grid Management -- An Application of Artificial Bee Colony and Cohort Intelligence in Automatic Generation Control of Thermal Power System -- Distribution System Losses and Its Allocation: Effects of Load Power Factor and Distributed Generations -- IoT based Intelligent Home Automation System using IFTTT with Google Assistant -- A review on Meta-heuristic Optimization Methods for Efficient Power System Operation -- Ice thickness control circuit to automate the milk chilling system -- SCGB Neural Network based Micro-grid AC Side Fault Analysis -- Artificial intelligence based system for detection and classification of faults in Induction motor.
520 _aThis book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It covers various power system applications including efficient power system operation, load forecasting, fault analysis, home automation and efficient smart grid management. Each application is accompanied by case studies and a literature review in self-contained chapters. The book is dedicated to study the effectiveness of intelligent methods in addressing the power system problems and its mitigation using optimization algorithms. It discusses several optimization algorithms such as random forest algorithm, metaheuristic algorithm, scaled conjugate gradient descent algorithm, artificial bee colony algorithm etc. and their usability in intelligent decision makers for the various optimization problems in electrical engineering. This timely book serves as a practical guide and reference sources for students, researchers and professionals.
650 0 _aComputational intelligence.
_964052
650 0 _aElectric power production.
_965675
650 0 _aArtificial intelligence.
_958441
650 0 _aAlgorithms.
_958677
650 0 _aMathematical optimization.
_965522
650 1 4 _aComputational Intelligence.
_964052
650 2 4 _aElectrical Power Engineering.
_965867
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aAlgorithms.
_958677
650 2 4 _aOptimization.
_965528
700 1 _aKhadse, Chetan B.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987006
700 1 _aKale, Ishaan R.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987007
700 1 _aShastri, Apoorva S.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_987008
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819757176
776 0 8 _iPrinted edition:
_z9789819757190
776 0 8 _iPrinted edition:
_z9789819757206
830 0 _aEngineering Optimization: Methods and Applications,
_x2731-4057
_987009
856 4 0 _uhttps://doi.org/10.1007/978-981-97-5718-3
912 _aZDB-2-INR
912 _aZDB-2-SXIT
999 _c64706
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