Dna Computing Based Genetic Algorithm

Author : Jili Tao
Publisher : Springer Nature
ISBN 13 : 981155403X
Total Pages : 280 pages
Book Rating : 4.32/5 ( download)

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Download or read book DNA Computing Based Genetic Algorithm written by Jili Tao and published by Springer Nature. This book was released on 2020-07-01 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.

Author : Kitto, Rob
Publisher : London : Department of Computer Science, University of Western Ontario
ISBN 13 : 9780771421723
Total Pages : 31 pages
Book Rating : 4.29/5 ( download)

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Download or read book Potential Applications for DNA Computing : Fuzzy Logic, Genetic Algorithms, and Expert Systems written by Kitto, Rob and published by London : Department of Computer Science, University of Western Ontario. This book was released on 1999 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Kim-Fung Man
Publisher : Springer Science & Business Media
ISBN 13 : 144710577X
Total Pages : 346 pages
Book Rating : 4.70/5 ( download)

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Download or read book Genetic Algorithms written by Kim-Fung Man and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book gives a overview of the latest discussions in the application of genetic algorithms to solve engineering problems. Featuring real-world applications and an accompanying disk, giving the reader the opportunity to use an interactive genetic algorithms demonstration program.

Author : G. Winter
Publisher :
ISBN 13 :
Total Pages : 486 pages
Book Rating : 4.13/5 ( download)

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Download or read book Genetic Algorithms in Engineering and Computer Science written by G. Winter and published by . This book was released on 1995 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Algorithms in Engineering and Computer Science Edited by G. Winter University of Las Palmas, Canary Islands, Spain J. Périaux Dassault Aviation, Saint Cloud, France M. Galán P. Cuesta University of Las Palmas, Canary Islands, Spain This attractive book alerts us to the existence of evolution based software — Genetic Algorithms and Evolution Strategies—used for the study of complex systems and difficult optimization problems unresolved until now. Evolution algorithms are artificial intelligence techniques which mimic nature according to the "survival of the fittest" (Darwin’s principle). They randomly encode physical (quantitative or qualitative) variables via digital DNA inside computers and are known for their robustness to better explore large search spaces and find near-global optima than traditional optimization methods. The objectives of this volume are two-fold: to present a compendium of state-of-the-art lectures delivered by recognized experts in the field on theoretical, numerical and applied aspects of Genetic Algorithms for the computational treatment of continuous, discrete and combinatorial optimization problems. to provide a bridge between Artificial Intelligence and Scientific Computing in order to increase the performance of evolution programs for solving real life problems. Fluid dynamics, structure mechanics, electromagnetics, automation control, resource optimization, image processing and economics are the featured multi-disciplinary areas among others in Engineering and Applied Sciences where evolution works impressively well. This volume is aimed at graduate students, applied mathematicians, computer scientists, researchers and engineers who face challenging design optimization problems in Industry. They will enjoy implementing new programs using these evolution techniques which have been experimented with by Nature for 3.5 billion years.

Author : Daniel Ashlock
Publisher : Springer Science & Business Media
ISBN 13 : 0387319093
Total Pages : 578 pages
Book Rating : 4.94/5 ( download)

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Download or read book Evolutionary Computation for Modeling and Optimization written by Daniel Ashlock and published by Springer Science & Business Media. This book was released on 2006-04-04 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concentrates on developing intuition about evolutionary computation and problem solving skills and tool sets. Lots of applications and test problems, including a biotechnology chapter.

Author : Hubert Schölnast
Publisher : GRIN Verlag
ISBN 13 : 3640594762
Total Pages : 89 pages
Book Rating : 4.64/5 ( download)

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Download or read book Genetic Programming in the Context of Natural Computing written by Hubert Schölnast and published by GRIN Verlag. This book was released on 2010-08 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bachelor Thesis from the year 2009 in the subject Computer Science - Programming, grade: 1, University of Applied Sciences Technikum Vienna (Informations- und Kommunikationssysteme), language: English, abstract: From the sector "Natural Computing" (simulation of natural Phenomena, hardware from nature, nature borrowed methods, etc.), the area "Biological inspired Computing" is selected and described. A systematic literature analysis of this field of research over the past 30 years shows that after a boom in neural networks in the 1990s, in the last five years genetic algorithms, including particularly the methods of genetic programming, came to the foreground. In this heuristic procedure computer programs are optimized in an iterative loop. In the startup phase, programs will be randomly generated. In a frequently recurring cycle, the steps program execution, evaluation of results (determination of fitness); selection and diversification (especially crossover and mutation) are used to "grow" better programs from generation to generation. This work shows criteria to decide in favor of whether or not to use genetic programming. Proven and experimental methods are presented for all phases of the optimization process, and one will find a short survey on how far these methods correlate to their natural role model. This thesis also refers to common problems such as Bloat. A library of methods collected by the author forms a mixture of a cookbook and a toolbox to be used in Genetic Programming. Finally, this thesis provides some examples where with the help of genetic programming award-winning practical applications have been created, which in many cases have outperformed conventionally obtained results.

Author : Alfons Schuster
Publisher : Springer Science & Business Media
ISBN 13 : 1846289432
Total Pages : 255 pages
Book Rating : 4.39/5 ( download)

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Download or read book Intelligent Computing Everywhere written by Alfons Schuster and published by Springer Science & Business Media. This book was released on 2007-10-04 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects the current perception in various fields that modern computing applications are becoming increasingly challenged in terms of complexity and intelligence. It investigates the relevance and relationship artificial intelligence maintains with "modern strands of computing". These consist of pervasive computing and ambient intelligence, bioinformatics, neuroinformatics, computing and the mind, non-classical computing and novel computing models, as well as DNA computing and quantum computing.

Author : Laura F. Landweber
Publisher : Springer Science & Business Media
ISBN 13 : 364255606X
Total Pages : 348 pages
Book Rating : 4.67/5 ( download)

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Download or read book Evolution as Computation written by Laura F. Landweber and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms and genetic and evolutionary programming.

Author : Giancarlo Zaccone
Publisher : BPB Publications
ISBN 13 : 9388511611
Total Pages : 301 pages
Book Rating : 4.12/5 ( download)

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Download or read book Natural Computing with Python written by Giancarlo Zaccone and published by BPB Publications. This book was released on 2019-09-17 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms. DESCRIPTIONÊ Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, youÕll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePyÊ and Cellular Automata techniques such as Game of Life, Langton's ant, etc.Ê The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. KEY FEATURES Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals WHAT WILL YOU LEARN Mastering Artificial Neural Networks Developing Artificial Intelligence systemsÊ Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computation WHO THIS BOOK IS FORÊ This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book. Table of Contents Neural Networks Deep Learning Genetic Programming Swarm Intelligence Cellular Automata Fractals Quantum Computing DNA Computing

Author : Laura F. Landweber
Publisher : Springer Science & Business Media
ISBN 13 : 9783540667094
Total Pages : 360 pages
Book Rating : 4.91/5 ( download)

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Download or read book Evolution as Computation written by Laura F. Landweber and published by Springer Science & Business Media. This book was released on 2002-11-27 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms and genetic and evolutionary programming.