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[null,"1.","Record Nr.",null,"UNINA9910702001203321"]
[null,null,"Autore",null,"Ciardullo Samuel W"]
[null,null,"Titolo",null,"Evaluation of capillary reinforced composites [[electronic resource] /] : by Samuel W. Ciardullo and Lewis J. Stoffer"]
[null,null,"Pubbl/distr/stampa",null,"Cincinnati, Ohio : , : General Electric Company, Aircraft Engine Business Group"]
[{"$nulls":4},"[Cleveland, Ohio] : , : National Aeronautics and Space Administration, NASA Lewis Research Center, , [1985]"]
[null,null,"Descrizione fisica",null,"1 online resource (8 unnumbered pages, 131 pages) : illustrations"]
[null,null,"Collana",null,"[NASA contractor report] ; ; NASA CR-175061"]
[null,null,"Soggetti",null,"Aircraft structures"]
[{"$nulls":4},"Capillary flow"]
[{"$nulls":4},"Composite materials"]
[{"$nulls":4},"Deicing"]
[{"$nulls":4},"Heat transfer"]
[{"$nulls":4},"Ice formation"]
[{"$nulls":4},"Intake systems"]
[{"$nulls":4},"Jet engines"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from title screen (viewed on June 29, 2012)."]
[{"$nulls":4},"\"September, 1985.\""]
[null,"2.","Record Nr.",null,"UNINA9910437776603321"]
[null,null,"Autore",null,"Hong Wei-Chiang"]
[null,null,"Titolo",null,"Intelligent energy demand forecasting / / Wei-Chiang Hong"]
[null,null,"Pubbl/distr/stampa",null,"London : , : Springer, , 2013"]
[null,null,"ISBN",null,"1-4471-4968-8"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (xiii, 189 pages) : illustrations (some color)"]
[null,null,"Collana",null,"Lecture Notes in Energy, , 2195-1284 ; ; 10"]
[null,null,"Disciplina",null,"333.7913"]
[null,null,"Soggetti",null,"Power resources - Forecasting"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"ISSN: 2195-1284.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"1.Introduction -- 2.Modeling for Energy Demand Forecasting -- 3.Evolutionary Algorithms in SVR’s Parameters Determination -- 4.Chaos/Cloud Theories to Avoid Trapping into Local Optimum -- 5.Recurrent/Seasonal Mechanism to Improve the Accurate Level of Forecasting."]
[null,null,null,"Sommario/riassunto","As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand.   Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms.   Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools."]