Lecture Notes In Data Engineering Computational Intelligence And Decision Making
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Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making
This book contains of 39 scientific papers which include the results of research regarding the current directions in the fields of data mining, machine learning and decision-making. This book is devoted to current problems of artificial and computational intelligence including decision-making systems. Collecting, analysis and processing information are the current directions of modern computer science. Development of new modern information and computer technologies for data analysis and processing in various fields of data mining and machine learning create the conditions for increasing effectiveness of the information processing by both the decrease of time and the increase of accuracy of the data processing. The papers are divided in terms of their topic into three sections. The first section "Analysis and Modeling of Hybrid Systems and Processes" contains of 11 papers, and the second section "Theoretical and Applied Aspects of Decision-Making Systems" contains of 11 ones too. There are 17 papers in the third section "Data Engineering, Computational Intelligence and Inductive Modeling". The book is focused to scientists and developers in the fields of data mining, machine learning and decision-making systems.
Lecture Notes in Data Engineering, Computational Intelligence, and Decision-Making, Volume 2
This book addresses contemporary challenges in artificial and computational intelligence, particularly focusing on decision-making systems. It explores current trends in computer science, including the collection, analysis, and processing of information. The advancement of modern information and computer technologies for data analysis and processing in data mining and machine learning is highlighted, showcasing their role in enhancing the efficiency of information processing by reducing time and increasing accuracy. The book comprises 16 scientific papers presenting cutting-edge research in data mining, machine learning, and decision-making. It is categorized into three sections: 1. Data engineering, computational intelligence, and inductive modeling—16 papers. This book is designed for scientists and developers specializing in data mining, machine learning, and decision-making systems.
Lecture Notes in Data Engineering, Computational Intelligence, and Decision-Making, Volume 1
This book addresses contemporary challenges in artificial and computational intelligence, particularly focusing on decision-making systems. It explores current trends in computer science, including the collection, analysis, and processing of information. The advancement of modern information and computer technologies for data analysis and processing in data mining and machine learning is highlighted, showcasing their role in enhancing the efficiency of information processing by reducing time and increasing accuracy. The book comprises 37 scientific papers presenting cutting-edge research in data mining, machine learning, and decision-making. It is categorized into three sections: 1. Analysis and modeling of hybrid systems and processes—14 papers. 2. Theoretical and applied aspects of decision-making systems—7 papers. 3. Data engineering, computational intelligence, and inductive modeling—16 papers. This book is designed for scientists and developers specializing in data mining, machine learning, and decision-making systems.