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Optimization and machine learning : ...

Chelouah, Rachid.

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Optimization and machine learning : = optimization for machine learning and machine learning for optimization /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Optimization and machine learning :/ coordinated by Rachid Chelouah, Patrick Siarry.
其他題名:	optimization for machine learning and machine learning for optimization /
其他作者:	Chelouah, Rachid.
出版者:	London, UK :ISTE, Ltd. ; : c2022.,
面頁冊數:	xiv, 236 p. :ill. ;25 cm.
內容註:	Front Matter -- Optimization. Vehicle Routing Problems with Loading Constraints: An Overview of Variants and Solution Methods / Ines Sbai, Saoussen Krichen -- MAS-aware Approach for QoS-based IoT Workflow Scheduling in Fog-Cloud Computing / Marwa Mokni, Sonia Yassa -- Solving Feature Selection Problems Built on Population-based Metaheuristic Algorithms / Mohamed Sassi -- Solving the Mixed-model Assembly Line Balancing Problem by using a Hybrid Reactive Greedy Randomized Adaptive Search Procedure / Belkharroubi Lakhdar, Khadidja Yahyaoui -- Machine Learning. An Interactive Attention Network with Stacked Ensemble Machine Learning Models for Recommendations / Ahlem Drif, SaadEddine Selmani, Hocine Cherifi -- A Comparison of Machine Learning and Deep Learning Models with Advanced Word Embeddings: The Case of Internal Audit Reports / Gustavo Fleury Soares, Induraj Pudhupattu Ramamurthy -- Hybrid Approach based on Multi-agent System and Fuzzy Logic for Mobile Robot Autonomous Navigation / Khadidja Yahyaoui -- Intrusion Detection with Neural Networks: A Tutorial / Alvise De' Faveri Tron -- List of Authors -- Index.
標題:	Machine learning. -
ISBN:	9781789450712

Optimization and machine learning : = optimization for machine learning and machine learning for optimization /
Optimization and machine learning :optimization for machine learning and machine learning for optimization /coordinated by Rachid Chelouah, Patrick Siarry. - London, UK :ISTE, Ltd. ;c2022. - xiv, 236 p. :ill. ;25 cm. - Sciences. Computer science. Operational research and decision. - Sciences. Computer science. Operational research and decision..

Includes bibliographical references and index.

Front Matter -- Optimization. Vehicle Routing Problems with Loading Constraints: An Overview of Variants and Solution Methods / Ines Sbai, Saoussen Krichen -- MAS-aware Approach for QoS-based IoT Workflow Scheduling in Fog-Cloud Computing / Marwa Mokni, Sonia Yassa -- Solving Feature Selection Problems Built on Population-based Metaheuristic Algorithms / Mohamed Sassi -- Solving the Mixed-model Assembly Line Balancing Problem by using a Hybrid Reactive Greedy Randomized Adaptive Search Procedure / Belkharroubi Lakhdar, Khadidja Yahyaoui -- Machine Learning. An Interactive Attention Network with Stacked Ensemble Machine Learning Models for Recommendations / Ahlem Drif, SaadEddine Selmani, Hocine Cherifi -- A Comparison of Machine Learning and Deep Learning Models with Advanced Word Embeddings: The Case of Internal Audit Reports / Gustavo Fleury Soares, Induraj Pudhupattu Ramamurthy -- Hybrid Approach based on Multi-agent System and Fuzzy Logic for Mobile Robot Autonomous Navigation / Khadidja Yahyaoui -- Intrusion Detection with Neural Networks: A Tutorial / Alvise De' Faveri Tron -- List of Authors -- Index.

Machine learning and optimization techniques are revolutionizing our world. Other types of information technology have not progressed as rapidly in recent years, in terms of real impact. The aim of this book is to present some of the innovative techniques in the field of optimization and machine learning, and to demonstrate how to apply them in the fields of engineering. Optimization and Machine Learning presents modern advances in the selection, configuration and engineering of algorithms that rely on machine learning and optimization. The first part of the book is dedicated to applications where optimization plays a major role, and the second part describes and implements several applications that are mainly based on machine learning techniques. The methods addressed in these chapters are compared against their competitors, and their effectiveness in their chosen field of application is illustrated.

ISBN: 9781789450712US177.95 Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .C43 2022

Dewey Class. No.: 006.3/1

Optimization and machine learning : = optimization for machine learning and machine learning for optimization /
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245 0 0 $a Optimization and machine learning : $b optimization for machine learning and machine learning for optimization / $c coordinated by Rachid Chelouah, Patrick Siarry.
260 # $a London, UK : $b ISTE, Ltd. ; $a Hoboken, NJ : $b Wiley, $c c2022.
300 $a xiv, 236 p. : $b ill. ; $c 25 cm.
490 1 $a Sciences. Computer science. Operational research and decision
504 $a Includes bibliographical references and index.
505 0 # $a Front Matter -- Optimization. Vehicle Routing Problems with Loading Constraints: An Overview of Variants and Solution Methods / Ines Sbai, Saoussen Krichen -- MAS-aware Approach for QoS-based IoT Workflow Scheduling in Fog-Cloud Computing / Marwa Mokni, Sonia Yassa -- Solving Feature Selection Problems Built on Population-based Metaheuristic Algorithms / Mohamed Sassi -- Solving the Mixed-model Assembly Line Balancing Problem by using a Hybrid Reactive Greedy Randomized Adaptive Search Procedure / Belkharroubi Lakhdar, Khadidja Yahyaoui -- Machine Learning. An Interactive Attention Network with Stacked Ensemble Machine Learning Models for Recommendations / Ahlem Drif, SaadEddine Selmani, Hocine Cherifi -- A Comparison of Machine Learning and Deep Learning Models with Advanced Word Embeddings: The Case of Internal Audit Reports / Gustavo Fleury Soares, Induraj Pudhupattu Ramamurthy -- Hybrid Approach based on Multi-agent System and Fuzzy Logic for Mobile Robot Autonomous Navigation / Khadidja Yahyaoui -- Intrusion Detection with Neural Networks: A Tutorial / Alvise De' Faveri Tron -- List of Authors -- Index.
520 # $a Machine learning and optimization techniques are revolutionizing our world. Other types of information technology have not progressed as rapidly in recent years, in terms of real impact. The aim of this book is to present some of the innovative techniques in the field of optimization and machine learning, and to demonstrate how to apply them in the fields of engineering. Optimization and Machine Learning presents modern advances in the selection, configuration and engineering of algorithms that rely on machine learning and optimization. The first part of the book is dedicated to applications where optimization plays a major role, and the second part describes and implements several applications that are mainly based on machine learning techniques. The methods addressed in these chapters are compared against their competitors, and their effectiveness in their chosen field of application is illustrated.
650 # 0 $a Machine learning. $3 533906
650 # 0 $a Mathematical optimization. $3 517763
700 1 # $a Chelouah, Rachid. $3 3641692
700 1 # $a Siarry, Patrick. $3 814742
830 0 $a Sciences. Computer science. Operational research and decision. $3 3641693