Xem 1-20 trên 118 kết quả Evolutionary algorithms
  • With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field.

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  • However, in the absence of this tool, the Swiss Army knife may be more suitable as a substitute. For example, to cut a piece of bread the kitchen knife is more suitable, but when traveling the Swiss Army knife is fine. Similarly, when a problemto be solved froma domain where the problem-specific knowledge is absent evolutionary algorithms can be successfully applied. Evolutionary algorithms are easy to implement and often provide adequate solutions.

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  • In recent years, the credit derivatives market has become extremely active. Especially credit default swaps (CDSs) and collateralized debt obligations (CDOs) have contributed to what has been an amazing development. The most important benefit of credit derivatives is their ability to transfer the credit risk of an arbitrary number of obligors in a simple, efficient, and standardized way, giving rise to a liquid market for credit risk that can be easily accessed by many market participants.

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  • Evolutionary computation has been widely used in computer science for decades. Even though it started as far back as the 1960s with simulated evolution, the subject is still evolving. During this time, new metaheuristic optimization approaches, like evolutionary algorithms, genetic algorithms, swarm intelligence, etc., were being developed and new fields of usage in artificial intelligence, machine learning, combinatorial and numerical optimization, etc., were being explored.

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  • In the chapter limit properties of genetic algorithms and theproblem of their classification are elaborated. Recently one can observe an increasing interest in properties of genetic algorithms modelled by Markov chains (Vose, Rowe). However, the known results are mainly limited to existence theorems. They say that there exists a limit distribution for a Markov chain describing a simple genetic algorithm. In the chapter we perform the next step on this way and present a formula for this limit distribution for a Markov chain.

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  • Genetic Algorithms (GAs) are global optimization techniques used in many real-life applications. They are one of several techniques in the family of Evolutionary Algorithms – algorithms that search for solutions to optimization problems by “evolving” better and better solutions. A Genetic Algorithm starts with a population of possible solutions for the desired application. The best ones are selected to become parents and then, using genetic operators like crossover and mutation, offspring are generated....

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  • Since the first production of tools at the beginning of human presence on Earth, human evolution is linked to the invention of new tools, usually combined with new environmental adaptations. The symbiosis of man with tools and environments represents one of the main factors in human evolutionary processes. It is evident how this coupling is based on the biophysics of our bodies and the development of the social memory system called culture.

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  • This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation.

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  • This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics.

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  • Tham khảo sách 'evolutionary computation_1', công nghệ thông tin, kỹ thuật lập trình phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả

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  • Evolutionary algorithms are successively applied to wide optimization problems in the engineering, marketing, operations research, and social science, such as include scheduling, genetics, material selection, structural design and so on. Apart...

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  • An origin of these algorithms is found in the Darwian principles of natural selection (Darwin, 1859). In accordance with these principles, only the fittest individuals can survive in the struggle for existence and reproduce their good characteristics into next generation. As illustrated in Fig. 1, evolutionary algorithms operate with the population of solutions. At first, the solution needs to be defined within an evolutionary algorithm. Usually, this definition cannot be described in the original problemcontext directly....

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  • Similarly, when a problemto be solved froma domain where the problem-specific knowledge is absent evolutionary algorithms can be successfully applied. Evolutionary algorithms are easy to implement and often provide adequate solutions. An origin of these algorithms is found in the Darwian principles of natural selection (Darwin, 1859). In accordance with these principles, only the fittest individuals can survive in the struggle for existence and reproduce their good characteristics into next generation....

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  • The book consists of 29 chapters. Chapters 1 to 9 describe the algorithms for enhancing the search performance of evolutionary algorithms such as Genetic Algorithm, Swarm Optimization Algorithm and Quantum-inspired Algorithm. Chapter 10 introduces the programming language for evolutionary algorithm. Chapter 11 explains evolutionary algorithms for the fuzzy data problems. Chapters 12 to 13 discuss theoretical analysis of evolutionary algorithms. The remaining chapters describe the applications of the evolutionary algorithms. ...

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  • Evolutionary algorithms are a type of general problem solvers that can be applied to many difficult optimization problems. Because of their generality, these algorithms act similarly like Swiss Army knife (Michalewicz & Fogel, 2004) that is a handy set of tools that can be used to address a variety of tasks. In general, a definite task can be performed better with an associated special tool.

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  • This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased optimization methods, this book presents diverse versions of genetic algorithms, genetic programming, and performance studies and analyses, as well as several particle swarm optimizers and hybrid approaches using neural networks and artificial immunological systems for multi-objective optimization....

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  • Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design - Part 1 studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modelling, mathematical algorithmic modelling, evolutionary algorithmic modelling, symbolic logic modelling, artificial intelligence modelling, and object-oriented computer modelling, in a logically structured approach to determining the integrity of engineering design. ...

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  • This is because the extent of damage of the beam members using design solutions at 800 gal 2 at 350 girls, while the beam member by using design solution at 750 gal is not damaged until the seismic force at 800 gal. Since the repair beam member requires scaffolding and other construction works even if the damage is small, repair costs higher than for the column members.

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  • Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design - Part 3 studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modelling, mathematical algorithmic modelling, evolutionary algorithmic modelling, symbolic logic modelling, artificial intelligence modelling, and object-oriented computer modelling, in a logically structured approach to determining the integrity of engineering design. ...

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  • Handbook of Reliability, Availability, Maintainability and Safety in Engineering Design - Part 2 studies the combination of various methods of designing for reliability, availability, maintainability and safety, as well as the latest techniques in probability and possibility modelling, mathematical algorithmic modelling, evolutionary algorithmic modelling, symbolic logic modelling, artificial intelligence modelling, and object-oriented computer modelling, in a logically structured approach to determining the integrity of engineering design. ...

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