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.
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 as Advances in intelligent data processing and its applications Multi-criteria decision analysis methods Knowledge engineering in large-scale systems High-dimensional data analysis Spatial data analysis and sparse estimation Innovative technologies and applications in computer intelligence Intelligent diagnosis and monitoring of systems Decision making theory for economics.
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.
Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment of expert system technology. Fast decision making, completion of projects in time and development of new products. Improvement in decision making capability and quality. Usage of Knowledge database and Preservation of expertise of individuals Eases complex decision problems. Ex: Diagnosis in Healthcare To address the issues and challenges related to development, implementation and application of automatic and intelligent prediction and decision support systems in domains such as manufacturing, healthcare and software product design, development and optimization, this book aims to collect and publish wide ranges of quality articles such as original research contributions, methodological reviews, survey papers, case studies and/or reports covering intelligent systems, expert prediction systems, evaluation models, decision support systems and Computer Aided Diagnosis (CAD).
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.
This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.
This book gathers the proceedings of the KES-IDT-2018 conference, held in Gold Coast, Queensland, Australia, on June 20–22, 2018 The conference provided opportunities to present and discuss the latest research results, promoting knowledge transfer and the generation of new ideas in the field of intelligent decision-making. The range of topics explored is wide, and includes methods for decision-making, decision support, data analysis, modeling and many more in areas such as finance, economics, management, engineering and transportation. The book contains several sections devoted to specific topics, such as: · Decision-Making Theory for Economics · Advances in Knowledge-based Statistical Data Analysis · On Knowledge-Based Digital Ecosystems & Technologies for Smart and Intelligent Decision Support Systems · Soft Computing Models in Industrial and Management Engineering · Computational Media Computing and its Applications · Intelligent Decision-Making Technologies · Digital Architectures and Decision Management
Information and computer technologies for data analysis and processing in various fields of data mining and machine learning generates the conditions for increasing the effectiveness of information processing by making it faster and more accurate. The book includes 49 scientific papers presenting the latest research in the fields of data mining, machine learning and decision-making. Divided into three sections: “Analysis and Modeling of Complex Systems and Processes”; “Theoretical and Applied Aspects of Decision-Making Systems”; and “Computational Intelligence and Inductive Modeling”, the book is of interest to scientists and developers in the field.
RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
It is with great pleasure that I present to you the proceedings of our Recent Advances in Management and Engineering held on November 24 – 27, 2023 in Male. Maldives. This conference represents a milestone in our ongoing journey towards academic excellence where we aspire to become a renowned platform for the exchange of ideas, collaboration, networking, and learning. These proceedings contain contributions that are very amazing in innovations in management. It covers a wide range of issues, ranging from the most recent trends in business to innovations in fundamentals of management. A broad collection of scholars, practitioners, and thought leaders from four continents across the world worked together to produce these results, which are a reflection of their combined efforts.
