Lakhmi C. Jain

George A. Tsihrintzis

Haris Doukas

Maria Virvou

Decision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues. DSSs have proven to be particularly useful at the strategic level, while they usually require only limited computer-proficiency skills from their users. Although DSSs have been under development and use for several decades, recent advances in both Software Engineering technologies and Artificial Intelligence (AI) methodologies have heralded new avenues for research and development in this field. This book exposes its readers to some of the most significant Advances in Artificial Intelligence-Empowered Decision Support Systems. It consists of an editorial note and an additional sixteen (16) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. The chapters are organized into five parts, namely (i) AI-Empowered DSS in Medical Diagnosis and Biology, (ii) AI-Empowered DSS in Healthcare and Health Insurance, (iii) AI-Empowered DSS in Urban Matters, (iv) Various Applications of AI-Empowered DSS, and (v) Novel AI-Empowered Methodologies in Decision Making. Targeted toward academics, researchers, practitioners, and students in Computer Science, Artificial Intelligence, and Management, this book is also accessible to individuals from other disciplines interested in the cutting-edge developments of AI-empowered DSS technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them.

Papers in Honour of Professor John Psarras

Advances in Artificial Intelligence-Empowered Decision Support Systems

Alexandros Flamos

Jenny Lieu

This open access book analyzes and seeks to consolidate the use of robust quantitative tools and qualitative methods for the design and assessment of energy and climate policies. In particular, it examines energy and climate policy performance and associated risks, as well as public acceptance and portfolio analysis in climate policy, and presents methods for evaluating the costs and benefits of flexible policy implementation as well as new framings for business and market actors. In turn, it discusses the development of alternative policy pathways and the identification of optimal switching points, drawing on concrete examples to do so. Lastly, it discusses climate change mitigation policies’ implications for the agricultural, food, building, transportation, service and manufacturing sectors.--

Multidisciplinary Methods and Tools for a Low Carbon Society

Understanding Risks and Uncertainties in Energy and Climate Policy

Haris Doukas

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