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A Metaheuristic Approach to Protein Structure Prediction - Algorithms and Insights from Fitness Landscape Analysis (Hardcover,... A Metaheuristic Approach to Protein Structure Prediction - Algorithms and Insights from Fitness Landscape Analysis (Hardcover, 1st ed. 2018)
Nanda Dulal Jana, Swagatam Das, Jaya Sil
R2,892 Discovery Miles 28 920 Ships in 10 - 15 working days

This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.

Intrusion Detection - A Data Mining Approach (Hardcover, 1st ed. 2020): Nandita Sengupta, Jaya Sil Intrusion Detection - A Data Mining Approach (Hardcover, 1st ed. 2020)
Nandita Sengupta, Jaya Sil
R4,233 Discovery Miles 42 330 Ships in 12 - 19 working days

This book presents state-of-the-art research on intrusion detection using reinforcement learning, fuzzy and rough set theories, and genetic algorithm. Reinforcement learning is employed to incrementally learn the computer network behavior, while rough and fuzzy sets are utilized to handle the uncertainty involved in the detection of traffic anomaly to secure data resources from possible attack. Genetic algorithms make it possible to optimally select the network traffic parameters to reduce the risk of network intrusion. The book is unique in terms of its content, organization, and writing style. Primarily intended for graduate electrical and computer engineering students, it is also useful for doctoral students pursuing research in intrusion detection and practitioners interested in network security and administration. The book covers a wide range of applications, from general computer security to server, network, and cloud security.

A Metaheuristic Approach to Protein Structure Prediction - Algorithms and Insights from Fitness Landscape Analysis (Paperback,... A Metaheuristic Approach to Protein Structure Prediction - Algorithms and Insights from Fitness Landscape Analysis (Paperback, Softcover reprint of the original 1st ed. 2018)
Nanda Dulal Jana, Swagatam Das, Jaya Sil
R2,873 Discovery Miles 28 730 Ships in 10 - 15 working days

This book introduces characteristic features of the protein structure prediction (PSP) problem. It focuses on systematic selection and improvement of the most appropriate metaheuristic algorithm to solve the problem based on a fitness landscape analysis, rather than on the nature of the problem, which was the focus of methodologies in the past. Protein structure prediction is concerned with the question of how to determine the three-dimensional structure of a protein from its primary sequence. Recently a number of successful metaheuristic algorithms have been developed to determine the native structure, which plays an important role in medicine, drug design, and disease prediction. This interdisciplinary book consolidates the concepts most relevant to protein structure prediction (PSP) through global non-convex optimization. It is intended for graduate students from fields such as computer science, engineering, bioinformatics and as a reference for researchers and practitioners.

Intrusion Detection - A Data Mining Approach (Paperback, 1st ed. 2020): Nandita Sengupta, Jaya Sil Intrusion Detection - A Data Mining Approach (Paperback, 1st ed. 2020)
Nandita Sengupta, Jaya Sil
R4,348 Discovery Miles 43 480 Ships in 10 - 15 working days

This book presents state-of-the-art research on intrusion detection using reinforcement learning, fuzzy and rough set theories, and genetic algorithm. Reinforcement learning is employed to incrementally learn the computer network behavior, while rough and fuzzy sets are utilized to handle the uncertainty involved in the detection of traffic anomaly to secure data resources from possible attack. Genetic algorithms make it possible to optimally select the network traffic parameters to reduce the risk of network intrusion. The book is unique in terms of its content, organization, and writing style. Primarily intended for graduate electrical and computer engineering students, it is also useful for doctoral students pursuing research in intrusion detection and practitioners interested in network security and administration. The book covers a wide range of applications, from general computer security to server, network, and cloud security.

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