Optimization and machine learning : optimization for machine learning and machine learning for optimization / coordinated by Rachid Chelouah, Patrick Siarry.

Contributor(s): Chelouah, Rachid [editor.] | Siarry, Patrick [editor.] | Ohio Library and Information Network
Series: Sciences. Computer science. Operational research and decisionPublisher: London, UK : Hoboken, NJ : ISTE, Ltd. ; Wiley, 2022Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781119902881; 1119902886; 9781119902874; 1119902878Subject(s): Machine learning | Mathematical optimizationGenre/Form: Electronic books.Additional physical formats: Print version:: No titleDDC classification: 006.3/1 LOC classification: Q325.5Online resources: Connect to resource
Contents:
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.
Summary: 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.
Tags from this library: No tags from this library for this title. Log in to add tags.
    Average rating: 0.0 (0 votes)
No physical items for this record

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.

Includes 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.

Available to OhioLINK libraries.

There are no comments for this item.

to post a comment.