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.
Inhoudsopgave
Arg Vote: Which Party Argues Like Me? Exploring an Argument-Based Voting Advice Application.- Arg Vote: Which Party Argues Like Me? Exploring an Argument-Based Voting Advice Application.- Impact of the Time Window Length on the Ship Trajectory Reconstruction Based on AIS Data Clustering.- Improved Genetic Algorithm for Electric Vehicle Charging Station Placement.- Solving a Many-objective Crop Rotation Problem with Evolutionary Algorithms.- The Utility of Neural Model in Predicting Tax Avoidance Behavior.- Triple-Station System of Detecting Small Airborne Objects in Dense Urban Environment.- Using Families of Extremal Quasi-Orthogonal Matrices in Communication Systems.- Variable Selection for Correlated High-dimensional Data with Infrequent Categorical Variables: Based on Sparse Sample Regression and Anomaly Detection Technology.- Verification of the Compromise Effect’s Suitability Based on Product Features of Automobiles.
Over de auteur
Irek Czarnowski is 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 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 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 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 focussed 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, received his Ph.D., M.E., B.E.(Hons) from the University of Technology Sydney, Australia, and Liverpool Hope University, UK and is Fellow of Engineers Australia. 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.
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