Autor/Autorin: Nabil Emad
Dr. Emad Nabil works in the department of Computer Science, Faculty of Computers and Information, Cairo University. His research interests are Bio-Inspired Algorithms, P systems, Optimization and Bioinformatics. He prepared this work in collaboration with Prof. Amr Badr, Faculty of Computers and Information, Cairo University.
Membrane Computing (P Systems) is an emergent and promising branch of Natural Computing. Designing P Systems is a heavy difficult problem. Until now there is no tool exists that can help in designing of P systems. This book shows how to use clonal selection algorithm with adaptive mutation in the design of P systems. In Addition the book proposes a Membrane-Immune algorithm that is inspired from the structure of living cells and the vertebrate immune system. The algorithm is tested by solving the Multiple Zero/One Knapsack Problem. The Membrane-Immune algorithm surpassed two variants of genetic algorithms that solved the same problem. The Membrane-Immune algorithm is also applied to generate a fuzzy rule based system to be used in breast cancer diagnosis. Generating a fuzzy rule system composes an exponential search space, which leads to the area of NP-complete problems. The algorithm is compared with five techniques and surpassed them. Last chapter presents a proposal of P Systems implementation using Cloud Computing. The proposed Implementation is illustrated by solving SAT problem.
Über den Autor
Dr. Emad Nabil works in the department of Computer Science, Faculty of Computers and Information, Cairo University. His research interests are Bio-Inspired Algorithms, P systems, Optimization and Bioinformatics. He prepared this work in collaboration with Prof. Amr Badr, Faculty of Computers and Information, Cairo University.
Klappentext
Membrane Computing (P Systems) is an emergent and promising branch of Natural Computing. Designing P Systems is a heavy difficult problem. Until now there is no tool exists that can help in designing of P systems. This book shows how to use clonal selection algorithm with adaptive mutation in the design of P systems. In Addition the book proposes a Membrane-Immune algorithm that is inspired from the structure of living cells and the vertebrate immune system. The algorithm is tested by solving the Multiple Zero/One Knapsack Problem. The Membrane-Immune algorithm surpassed two variants of genetic algorithms that solved the same problem. The Membrane-Immune algorithm is also applied to generate a fuzzy rule based system to be used in breast cancer diagnosis. Generating a fuzzy rule system composes an exponential search space, which leads to the area of NP-complete problems. The algorithm is compared with five techniques and surpassed them. Last chapter presents a proposal of P Systems implementation using Cloud Computing. The proposed Implementation is illustrated by solving SAT problem.
