Lecture Notes In Data Engineering Computational Intelligence And Decision Making Volume 1
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Lecture Notes in Data Engineering, Computational Intelligence, and Decision Making
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.
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.
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.