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Intelligent Data Engineering and Automated Learning – IDEAL 2017: 18th International Conference, Guilin, China, October 30 – November 1, 2017, Proceedings (Lecture Notes in Computer Science #10585)
by Hujun Yin, Yang Gao, Songcan Chen, Yimin Wen, Guoyong Cai, Tianlong Gu, Junping Du, Antonio J. Tallón-Ballesteros and Minling ZhangThis book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017.The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
Intelligent Data Engineering and Automated Learning – IDEAL 2018: 19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings, Part I (Lecture Notes in Computer Science #11314)
by Paulo Novais David Camacho Hujun Yin Antonio J. Tallón-BallesterosThis two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
Intelligent Data Engineering and Automated Learning – IDEAL 2018: 19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings, Part II (Lecture Notes in Computer Science #11315)
by Paulo Novais David Camacho Hujun Yin Antonio J. Tallón-BallesterosThis two-volume set LNCS 11314 and 11315 constitutes the thoroughly refereed conference proceedings of the 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, held in Madrid, Spain, in November 2018. The 125 full papers presented were carefully reviewed and selected from 204 submissions. These papers provided a timely sample of the latest advances in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.
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 AllmendingerThis 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 AllmendingerThis 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 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part I (Lecture Notes in Computer Science #12489)
by Paulo Novais David Camacho Cesar Analide Hujun YinThis two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*The 93 papers presented were carefully reviewed and selected from 134 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 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.
Intelligent Data Engineering and Automated Learning – IDEAL 2020: 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part II (Lecture Notes in Computer Science #12490)
by Paulo Novais David Camacho Cesar Analide Hujun YinThis two-volume set of LNCS 12489 and 12490 constitutes the thoroughly refereed conference proceedings of the 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020, held in Guimaraes, Portugal, in November 2020.*The 93 papers presented were carefully reviewed and selected from 134 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 2020 include big data challenges, machine learning, data mining, information retrieval and management, bio-/neuro-informatics, bio-inspiredmodels, agents and hybrid intelligent systems, real-world applications of intelligent techniques and AI. * The conference was held virtually due to the COVID-19 pandemic.
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 NascimentoThis 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 2022: 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings (Lecture Notes in Computer Science #13756)
by David Camacho Hujun Yin Peter TinoThis book constitutes the refereed proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022, which took place in Manchester, UK, during November 24-26, 2022. The 52 full papers included in this book were carefully reviewed and selected from 79 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-BallesterosThis 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-BallesterosThis 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-BallesterosThis 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 in Law Enforcement Analytics: New Neural Networks Applied to Real Problems
by William J. Tastle Paolo Massimo BuscemaThis book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.
Intelligent Data Processing: 11th International Conference, IDP 2016, Barcelona, Spain, October 10–14, 2016, Revised Selected Papers (Communications in Computer and Information Science #794)
by Dmitry I. Ignatov Vadim V. Strijov Konstantin V. VorontsovThis book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Processing, IDP 2016, held in Barcelona, Spain, in October 2016. The 11 revised full papers were carefully reviewed and selected from 52 submissions. The papers of this volume are organized in topical sections on machine learning theory with applications; intelligent data processing in life and social sciences; morphological and technological approaches to image analysis.
Intelligent Data Warehousing: From Data Preparation to Data Mining
by Zhengxin ChenEffective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in
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 DewanThe 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 Decision Making in Quality Management
by Cengiz Kahraman Seda YanıkThis book presents recently developed intelligent techniques with applications and theory in the area of quality management. The involved applications of intelligence include techniques such as fuzzy sets, neural networks, genetic algorithms, etc. The book consists of classical quality management topics dealing with intelligent techniques for solving the complex quality management problems. The book will serve as an excellent reference for quality managers, researchers, lecturers and postgraduate students in this area. The authors of the chapters are well-known researchers in the area of quality management.
Intelligent Decision Support Systems
by Miquel Sànchez-MarrèThis 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 AgarwalINTELLIGENT 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 for Sustainable Computing
by Ajith Abraham Patrick Siarry Arun Kumar Sangaiah Michael ShengThis unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective. Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms. The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be exploited to create effectual computing systems, and addresses sustainability problems in computing and information processing environments and technologies at the different levels of CI paradigms. An excellent guide to surveying the state of the art in computational intelligence applied to challenging real-world problems in sustainable computing, it is intended for scientists, practitioners, researchers and academicians dealing with the new challenges and advances in area.
Intelligent Decision Support Systems: Combining Operations Research and Artificial Intelligence - Essays in Honor of Roman Słowiński (Multiple Criteria Decision Making)
by Constantin Zopounidis Jerzy Stefanowski Vincent Mousseau Salvatore GrecoThis book presents a collection of essays written by leading researchers to honor Roman Słowiński’s major scholarly interests and contributions. He is well-known for conducting extensive research on methodologies and techniques for intelligent decision support, where he combines operational research and artificial intelligence. The book reconstructs his main contributions, presents cutting-edge research and provides an outlook on the most promising and advanced domains of computer science and multiple criteria decision aiding. The respective chapters cover a wide range of related research areas, including decision sciences, ordinal data mining, preference learning and multiple criteria decision aiding, modeling of uncertainty and imprecision in decision problems, rough set theory, fuzzy set theory, multi-objective optimization, project scheduling and decision support applications. As such, the book will appeal to researchers and scholars in related fields.
Intelligent Decision Support Systems—A Journey to Smarter Healthcare (Intelligent Systems Reference Library #157)
by Smaranda Belciug Florin GorunescuThe 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
by Lakhmi C. Jain Robert J. Howlett Rui Neves-SilvaThis book presents the 57 papers accepted for presentation at the Seventh KES International Conference on Intelligent Decision Technologies (KES-IDT 2015), held in Sorrento, Italy, in June 2015. The conference consists of keynote talks, oral and poster presentations, invited sessions and workshops on the applications and theory of intelligent decision systems and related areas. The conference provides an opportunity for the presentation and discussion of interesting new research results, promoting knowledge transfer and the generation of new ideas. The book will be of interest to all those whose work involves the development and application of intelligent decision systems.
Intelligent Decision Technologies 2016
by Lakhmi C. Jain Robert J. Howlett Ireneusz Czarnowski Alfonso Mateos CaballeroThe 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 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 CaballeroThe 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.