{"product_id":"data-driven-evolutionary-modeling-in-materials-technology-9781032061733","title":"Data-Driven Evolutionary Modeling in Materials Technology","description":"\u003cp\u003e • Author(s): Nirupam Chakraborti\u003cbr\u003e • Publisher: Taylor \u0026amp; Francis\u003cbr\u003e • Publisher Imprint: CRC Press\u003cbr\u003e • BISAC: Materials Science - Metals \u0026amp; Alloys\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eDue to efficacy and optimization potential of genetic and evolutionary algorithms, they are used in learning and modeling especially with the advent of big data related problems. This book presents the algorithms and strategies specifically associated with pertinent issues in materials science domain. It discusses the procedures for evolutionary multi-objective optimization of objective functions created through these procedures and introduces available codes. Recent applications ranging from primary metal production to materials design are covered. It also describes hybrid modeling strategy, and other common modeling and simulation strategies like molecular dynamics, cellular automata etc.\u003c\/p\u003e\u003cp\u003eFeatures: \u003c\/p\u003e\u003cul\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eFocuses on data-driven evolutionary modeling and optimization, including evolutionary deep learning.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eInclude details on both algorithms and their applications in materials science and technology.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eDiscusses hybrid data-driven modeling that couples evolutionary algorithms with generic computing strategies.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eThoroughly discusses applications of pertinent strategies in metallurgy and materials.\u003c\/li\u003e \u003cp\u003e \u003c\/p\u003e \u003cli\u003eProvides overview of the major single and multi-objective evolutionary algorithms.\u003c\/li\u003e \u003c\/ul\u003e\u003cp\u003eThis book aims at Researchers, Professionals, and Graduate students in Materials Science, Data-Driven Engineering, Metallurgical Engineering, Computational Materials Science, Structural Materials, and Functional Materials.\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Hardcover","offer_id":45242009354391,"sku":"9781032061733","price":14663.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9781032061733.webp?v=1769230576","url":"https:\/\/atlanticbooks.com\/products\/data-driven-evolutionary-modeling-in-materials-technology-9781032061733","provider":"Atlantic Books","version":"1.0","type":"link"}