Intelligent Decision Technologies

This book gathers selected papers from the KES-IDT 2023 Conference, held in Rome, Italy, on June 1416, 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 analysistheory 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.

Presents research works in the field of intelligent decision-making Provides original works presented at KES-IDT 2023 held in Rome, Italy Serves as a reference for researchers and practitioners in academia and industry

Autorentext

Ireneusz Czarnowski is a professor at the Gdynia Maritime University. He holds B.Sc. and M.Sc. degrees in Electronics and Communication Systems from the same University. He gained the doctoral degree in the field of computer science in 2004 at Faculty of Computer Science and Management of Poznan University of Technology. In 2012, he earned a postdoctoral degree in the field of computer science in technical sciences at Wroclaw University of Science and Technology. His research interests include artificial intelligence, machine learning, evolutionary computations, multi-agent systems, data mining and data science. He is an associate editor of the Journal of Knowledge-Based and Intelligent Engineering Systems, published by the IOS Press, and a reviewer for several scientific journals. Dr. Robert Howlett is the executive chair of KES International, a non-profit organization that facilitates knowledge transfer and the dissemination of research results in areas including intelligent systems, sustainability and knowledge transfer. He is a visiting professor at Bournemouth University in the UK. His technical expertise is in the use of intelligent systems to solve industrial problems. He has been successful in applying artificial intelligence, machine learning and related technologies to sustainability and renewable energy systems; condition monitoring, diagnostic tools and systems; and automotive electronics and engine management systems. His current research work is focused on the use of smart microgrids to achieve reduced energy costs and lower carbon emissions in areas such as housing and protected horticulture. Dr. Lakhmi C. Jain, Ph.D., M.E., B.E.(Hons), fellow (Engineers Australia) is with the University of Technology Sydney, Australia, and Liverpool Hope University, UK. Professor Jain serves the KES International for providing a professional community the opportunities for publications, knowledge exchange, cooperation and teaming. Involving around 5,000 researchers drawn from universities and companies worldwide, KES facilitates international cooperation and generates synergy in teaching and research. KES regularly provides networking opportunities for professional community through one of the largest conferences of its kind in the area of KES.

Inhalt
Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning.- Multimedia Industrial and Medical Applications Supported by Machine Learning.- Accessibility Measures and Indicators: A Basis for Dynamic Simulations to Improve Regional Planning.- Image-multimodal Data Analysis for Defect Classification: Case Study of Industrial Printing.- Image-multimodal Data Analysis for Defect Classification: Case Study of Semiconductor Defect Patter.- Decision-making Model for Updating Geographical Information Systems for Polish Municipalities Using the Fuzzy TOPSIS Method.- An Ontology-based Collaborative Assessment Analytics Framework to Predict Groups' Disengagement.- On Sensing Non-visual Symptoms of Northern Leaf Blight Inoculated Maize for Early Disease Detection Using IoT/AI.- Inference Analysis of Lightweight CNNs for Monocular Depth Estimation.- Arabic Text-to-speech Service with Syrian Dialect.- A Systematic Review of Sentiment Analysis in Arabizi.