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Intelligent Data Engineering and Analytics: Proceedings of the 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2023) (Smart Innovation, Systems and Technologies #371)

by João Manuel R. S. Tavares Vikrant Bhateja Fiona Carroll Peter Peer Sandeep Singh Sengar

The book presents the proceedings of the 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2023), held at Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, Wales, UK, during April 11–12, 2023. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. This book is divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols, and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines.

Intelligent Data Engineering and Analytics: Proceedings of the 12th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2024) (Smart Innovation, Systems and Technologies #420)

by Vikrant Bhateja Milan Simic Preeti Patel

The book presents the proceedings of the 12th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2024), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6–7, 2024. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. This book is divided into four volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines.

Intelligent Data Engineering and Analytics: Proceedings of the 9th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA 2021) (Smart Innovation, Systems and Technologies #266)

by Suresh Chandra Satapathy Vikrant Bhateja Peter Peer Jinshan Tang Anumoy Ghosh

This book presents the proceedings of the 9th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2021), held at NIT Mizoram, Aizwal, Mizoram, India, during June 25 – 26, 2021. FICTA conference aims to bring together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. This volume covers broad areas of Intelligent Data Engineering and Analytics. The conference papers included herein presents both theoretical as well as practical aspects of data intensive computing, data mining, big data, knowledge management, intelligent data acquisition and processing from sensors, data communication networks protocols and architectures, etc. The volume will also serve as a knowledge centre for students of post-graduate level in various engineering disciplines.

Intelligent Data Engineering and Automated Learning – IDEAL 2019: 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part I (Lecture Notes in Computer Science #11871)

by Ronaldo Menezes David Camacho Hujun Yin Antonio J. Tallón-Ballesteros Peter Tino Richard Allmendinger

This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.

Intelligent Data Engineering and Automated Learning – IDEAL 2019: 20th International Conference, Manchester, UK, November 14–16, 2019, Proceedings, Part II (Lecture Notes in Computer Science #11872)

by Ronaldo Menezes David Camacho Hujun Yin Antonio J. Tallón-Ballesteros Peter Tino Richard Allmendinger

This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019. The 94 full papers presented were carefully reviewed and selected from 149 submissions. These papers provided a timely sample of the latest advances in data engineering and machine learning, from methodologies, frameworks, and algorithms to applications. The core themes of IDEAL 2019 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models (including neural networks, evolutionary computation and swarm intelligence), agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI.

Intelligent Data Engineering and Automated Learning – IDEAL 2021: 22nd International Conference, IDEAL 2021, Manchester, UK, November 25–27, 2021, Proceedings (Lecture Notes in Computer Science #13113)

by Paulo Novais David Camacho Hujun Yin Ke Tang Antonio J. Tallón-Ballesteros Peter Tino Richard Allmendinger Sung-Bae Cho Susana Nascimento

This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic.The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.

Intelligent Data Engineering and Automated Learning – IDEAL 2023: 24th International Conference, Évora, Portugal, November 22–24, 2023, Proceedings (Lecture Notes in Computer Science #14404)

by Paulo Quaresma Teresa Gonçalves David Camacho Vicente Julian Hujun Yin Antonio J. Tallón-Ballesteros

This book constitutes the proceedings of the 24th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2023, held in Évora, Portugal, during November 22–24, 2023.The 45 full papers and 4 short papers presented in this book were carefully reviewed and selected from 77 submissions. IDEAL 2023 is focusing on big data challenges, machine learning, deep learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspired models, agents and hybrid intelligent systems, and real-world applications of intelligence techniques and AI.The papers are organized in the following topical sections: main track; special session on federated learning and (pre) aggregation in machine learning; special session on intelligent techniques for real-world applications of renewable energy and green transport; and special session on data selection in machine learning.

Intelligent Data Engineering and Automated Learning – IDEAL 2024: 25th International Conference, Valencia, Spain, November 20–22, 2024, Proceedings, Part I (Lecture Notes in Computer Science #15346)

by Paulo Novais David Camacho Vicente Julian Hujun Yin Juan M. Alberola Vitor Beires Nogueira Antonio Tallón-Ballesteros

This two-volume set, LNCS 15346 and LNCS 15347, constitutes the proceedings of the 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024, held in Valencia, Spain, during November 20–22, 2024. The 86 full papers and 6 short papers presented in this book were carefully reviewed and selected from 130 submissions. IDEAL 2024 is focusing on Big Data Analytics and Privacy, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Information Retrieval and Management, Bio and Neuro-Informatics, and Hybrid Intelligent Systems and Agents.

Intelligent Data Engineering and Automated Learning – IDEAL 2024: 25th International Conference, Valencia, Spain, November 20–22, 2024, Proceedings, Part II (Lecture Notes in Computer Science #15347)

by Paulo Novais David Camacho Vicente Julian Hujun Yin Juan M. Alberola Vitor Beires Nogueira Antonio Tallón-Ballesteros

This two-volume set, LNCS 15346 and LNCS 15347, constitutes the proceedings of the 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024, held in Valencia, Spain, during November 20–22, 2024. The 86 full papers and 6 short papers presented in this book were carefully reviewed and selected from 130 submissions. IDEAL 2024 is focusing on Big Data Analytics and Privacy, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Information Retrieval and Management, Bio and Neuro-Informatics, and Hybrid Intelligent Systems and Agents.

Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems (IEEE Press Series on Power and Energy Systems)

by Zita Vale Tiago Pinto Michael Negnevitsky Ganesh Kumar Venayagamoorthy

Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.

Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications (Intelligent Data-Driven Systems and Artificial Intelligence)

by B Rajanarayan Prusty, Neeraj Gupta, Kishore Bingi, and Rakesh Sehgal

This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include: an exclusive section on essential preprocessing approaches for the data-driven model a detailed overview of data-driven model applications to power system planning and operational activities specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.

Intelligent Data-Driven Techniques for Security of Digital Assets (Intelligent Data-Driven Systems and Artificial Intelligence)

by Arun Kumar Rana Vishnu Sharma Sumit Kumar Rana Ritu Dewan

The book covers the role of emerging technologies such as blockchain technology, machine learning, IoT, cryptography, etc., in digital asset management. It further discusses digital asset management applications in different domains such as healthcare, travel industry, image processing, and our daily life activities to maintain privacy and confidentiality.This book:• Discusses techniques for securing and protecting digital assets in collaborative environments, where multiple organizations need access to the same resources.• Explores how artificial intelligence can be used to automate the management of digital assets, and how it can be used to improve security and privacy.• Explains the role of emerging technology such as blockchain technology for transforming conventional business models.• Highlights the importance of machine learning techniques in maintaining the privacy and security of data.• Covers encryption and decryption techniques, their advantages and role in improving the privacy of data.The text is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science and engineering, information technology, and business management.

Intelligent Decarbonisation: Can Artificial Intelligence and Cyber-Physical Systems Help Achieve Climate Mitigation Targets? (Lecture Notes in Energy #86)

by Oliver Inderwildi Markus Kraft

The book explains the need to decarbonise energy supplies, urban systems and industrial processes to reduce global greenhouse gases and meet the ambitious emissions reduction goals set out in the Paris Agreement 2016. It discusses how the introduction of AI to cyber-physical systems (CPS) can do this, using illustrations throughout to highlight the potential impacts.Intelligent Decarbonisation comprehensively assesses the current and future impact of digital technologies and artificial intelligence (AI) on the decarbonisation of key economic sectors.The book is divided into four parts – Technology, Impact, Implications and Incubation – moving clearly from the theoretical and technical to the real-world effects and areas for future development. It also presents insights into the economic and environmental transformation fostered by digital technologies.Intelligent Decarbonisation brings together work from private and public sector professionals, academics and think tank experts, and provides truly comprehensive insights into the topic. It is an interesting and informative text for policymakers, researchers and industry professionals alike.

Intelligent Decision Support Systems

by Miquel Sànchez-Marrè

This book presents the potential use and implementation of intelligent techniques in decision making processes involved in organizations and companies. It provides a thorough analysis of decisions, reviewing the classical decision theory, and describing usual methods for modeling the decision process. It describes the chronological evolution of Decision Support Systems (DSS) from early Management Information Systems until the appearance of Intelligent Decision Support Systems (IDSS). It explains the most commonly used intelligent techniques, both data-driven and model-driven, and illustrates the use of knowledge models in Decision Support through case studies. The author pays special attention to the whole Data Science process, which provides intelligent data-driven models in IDSS. The book describes main uncertainty models used in Artificial Intelligence to model inexactness; covers recommender systems; and reviews available development tools for inducing data-driven models, for using model-driven methods and for aiding the development of Intelligent Decision Support Systems

Intelligent Decision Support Systems for Smart City Applications (Concise Introductions to AI and Data Science)

by Loveleen Gaur Prasenjit Chatterjee Vernika Agarwal

INTELLIGENT DECISION SUPPORT SYSTEMS FOR SMART CITY APPLICATIONS This book provides smart city frameworks to address new difficulties by adding new features and allowing the city environment to react to collected data and information to increase the efficiency and sustainability of services for inhabitants. Making a smart city is an emerging strategy to mitigate the problems generated by urban population growth and rapid urbanization. This book aims to provide a better understanding of the concept of smart cities and the application of an intelligent decision support system. Based on the analysis of existing information there are eight critical factors of smart city initiatives: management and organization, technology, governance, policy context, people and communities, economy, built infrastructure, and natural environment. This book will focus on the application of the decision support system in managing these eight crucial aspects of smart cities. The intent in writing this book was also to provide a source that covers the stage-by-stage integration of the four key areas involving planning, physical infrastructure, ICT infrastructure, and deploying the smart solutions necessary for city transformation. With this as the motivation, “Decision Support Systems for Smart City Applications” provides the application of an intelligent decision support system for effectively and efficiently managing the transformation process, which can aid various supply chain stakeholders, academic researchers, and related professionals in building smart cities. Various chapters of this book are expected to support practicing managers during the implementation of smart solutions for city transformation. Audience This book is aimed at both academics and practitioners alike in the fields of intelligent computing, decision support systems, the manufacturing industry, supply chain managers, stakeholders, policymakers, and other technical and administrative personnel.

Intelligent Decision Support Systems—A Journey to Smarter Healthcare (Intelligent Systems Reference Library #157)

by Smaranda Belciug Florin Gorunescu

The goal of this book is to provide, in a friendly and refreshing manner, both theoretical concepts and practical techniques for the important and exciting field of Artificial Intelligence that can be directly applied to real-world healthcare problems. Healthcare – the final frontier. Lately, it seems like Pandora opened the box and evil was released into the world. Fortunately, there was one thing left in the box: hope. In recent decades, hope has been increasingly represented by Intelligent Decision Support Systems. Their continuing mission: to explore strange new diseases, to seek out new treatments and drugs, and to intelligently manage healthcare resources and patients. Hence, this book is designed for all those who wish to learn how to explore, analyze and find new solutions for the most challenging domain of all time: healthcare.

Intelligent Decision Technologies 2016: Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part II (Smart Innovation, Systems and Technologies #57)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski Alfonso Mateos Caballero

The KES-IDT-2016 proceedings give an excellent insight into recent research, both theoretical and applied, in the field of intelligent decision making. The range of topics explored is wide, and covers methods of grouping, classification, prediction, decision support, modelling and many more in such areas as finance, linguistics, medicine, management and transportation. This proceedings contain several sections devoted to specific topics, such as: · Specialized Decision Techniques for Data Mining, Transportation and Project Management · Pattern Recognition for Decision Making Systems · New Advances of Soft Computing in Industrial and Management Engineering · Recent Advances in Fuzzy Systems · Intelligent Data Analysis and Applications · Reasoning-based Intelligent Systems · Intelligent Methods for Eye Movement Data Processing and Analysis · Intelligent Decision Technologies for Water Resources Management · Intelligent Decision Making for Uncertain Unstructured Big Data · Decision Making Theory for Economics · Interdisciplinary Approaches in Business Intelligence Research and Practice · Pattern Recognition in Audio and Speech Processing The KES-IDT conference is a well-established international annual conference, interdisciplinary in nature. These two volumes of proceedings form an excellent account of the latest results and outcomes of recent research in this leading-edge area.

Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), Volume 1 (Smart Innovation, Systems and Technologies #142)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

The book presents a collection of peer-reviewed articles from the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT-19), held Malta on 17–19 June 2019. The conference provided opportunities for the presentation of new research results and discussion about them. It was also an opportunity to generation of new ideas in the field of intelligent decision making. The range of topics explored is wide, and covers methods of classification, prediction, data analysis, decision support, modelling and many more in such areas as finance, cybersecurity, economy, health, management and transportation. The topics cover also problems of data science, signal processing and knowledge engineering.

Intelligent Decision Technologies 2019: Proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), Volume 2 (Smart Innovation, Systems and Technologies #143)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

The book presents a collection of peer-reviewed articles from the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT-19), held Malta on 17–19 June 2019. The conference provided opportunities for the presentation of new research results and discussion about them. It was also an opportunity to generation of new ideas in the field of intelligent decision making. The range of topics explored is wide, and covers methods of classification, prediction, data analysis, decision support, modelling and many more in such areas as finance, cybersecurity, economy, health, management and transportation. The topics cover also problems of data science, signal processing and knowledge engineering.

Intelligent Decision Technologies: Proceedings of the 12th KES International Conference on Intelligent Decision Technologies (KES-IDT 2020) (Smart Innovation, Systems and Technologies #193)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

This book gathers selected papers from the KES-IDT-2020 Conference, held as a Virtual Conference on June 17–19, 2020. The aim of the annual conference was to present and discuss the latest research results, and to generate new ideas in the field of intelligent decision-making. However, the range of topics discussed during the conference was definitely broader and covered methods in e.g. classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in such diverse areas as finance, cybersecurity, economics, health, management and transportation. The Problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as Intelligent Data Processing and its ApplicationsHigh-Dimensional Data Analysis and its ApplicationsMulti-Criteria Decision Analysis – Theory and ApplicationsLarge-Scale Systems for Intelligent Decision-Making and Knowledge EngineeringDecision Technologies and Related Topics in Big Data Analysis of Social and Financial IssuesDecision-Making Theory for Economics

Intelligent Decision Technologies: Proceedings of the 13th KES-IDT 2021 Conference (Smart Innovation, Systems and Technologies #238)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

This book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14–16, 2021. The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discussion about them under the common title "Intelligent Decision Technologies". The conference has been creating for years a platform for knowledge transfer and the generation of new ideas in the field of intelligent decision making.The range of topics discussed during the conference covered methods of classification, prediction, data analysis, big data, decision support, knowledge engineering, modeling, social networks and many more in areas such as finance, economy, management and transportation. The discussed topics covered also decision making for problems regarding the electric vehicle industry.The book contains also several sections devoted to specific topics, such asAdvances in intelligent data processing and its applicationsMulti-criteria decision analysis methodsKnowledge engineering in large-scale systemsHigh-dimensional data analysisSpatial data analysis and sparse estimationInnovative technologies and applications in computer intelligenceIntelligent diagnosis and monitoring of systemsDecision making theory for economics.

Intelligent Decision Technologies: Proceedings of the 14th KES-IDT 2022 Conference (Smart Innovation, Systems and Technologies #309)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

This book gathers selected papers from the KES-IDT 2022 Conference, held in Rhodes, Greece on June 20–22, 2022. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed are classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in diverse areas such as finance, cybersecurity, economics, health, management, and transportation. The problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues, and decision-making theory for economics.

Intelligent Decision Technologies: Proceedings of the 15th KES-IDT 2023 Conference (Smart Innovation, Systems and Technologies #352)

by Lakhmi C. Jain Ireneusz Czarnowski R. J. Howlett

This book gathers selected papers from the KES-IDT 2023 Conference, held in Rome, Italy, on June 14–16, 2023. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed is classification, prediction, data analysis, big data, data science, decision support, knowledge engineering and modeling in diverse areas such as finance, cybersecurity, economics, health, management and transportation. The problems in industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues and decision-making theory for economics.

Intelligent Decision Technologies: Proceedings of the 16th KES-IDT 2024 Conference (Smart Innovation, Systems and Technologies #411)

by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski

This book gathers selected papers from the KES-IDT 2024 conference, held in Madeira, Portugal, on June 19–21, 2024. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed is classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in diverse areas such as finance, cybersecurity, economics, health, management, and transportation. The problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies, and related topics in big data analysis of social and financial issues and decision-making theory for economics.

Intelligent Decision-making Models for Production and Retail Operations

by Zhaoxia Guo

This book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.

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