標(biāo)題: Titlebook: Computational Intelligence; A Methodological Int Rudolf Kruse,Christian Borgelt,Pascal Held Textbook 20131st edition Springer-Verlag London [打印本頁] 作者: Exaltation 時(shí)間: 2025-3-21 17:45
書目名稱Computational Intelligence影響因子(影響力)
作者: anagen 時(shí)間: 2025-3-21 22:10 作者: 放逐 時(shí)間: 2025-3-22 01:40
Introduction They consist of a large number of fairly simple units, the so-called ., which are working in parallel. These neurons communicate by sending information in the form of activation signals, along directed connections, to each other. A commonly used synonym for “neural network” is the term “connectioni作者: 發(fā)現(xiàn) 時(shí)間: 2025-3-22 06:14 作者: induct 時(shí)間: 2025-3-22 10:37 作者: Expand 時(shí)間: 2025-3-22 15:15
Radial Basis Function Networksf layers is always three, that is, there is exactly one hidden layer. In addition, radial basis function networks differ from multi-layer perceptrons in the network input and activation functions, especially in the hidden layer. In this hidden layer . are employed, which are responsible for the name作者: Expand 時(shí)間: 2025-3-22 20:59
Self-organizing Mapsidden layer of a radial basis function network is already the output layer of a self-organizing map. This output layer also has an internal structure, since the neurons are arranged in a grid. The neighborhood relationships resulting from this grid are exploited in the training process in order to d作者: 仲裁者 時(shí)間: 2025-3-22 21:27
Hopfield Networksever, we turn to so-called ., that is, networks, the graph of which may contain (directed) cycles. We start with one of the simplest forms, the so-called ., which originated as physical models to describe magnetism. Hopfield networks are indeed closely related to the Ising model of magnetism.作者: Ingrained 時(shí)間: 2025-3-23 01:56 作者: Peak-Bone-Mass 時(shí)間: 2025-3-23 06:07
Introduction to Evolutionary Algorithmshich also includes, for example, particle swarm and ant colony optimization, which are inspired by other biological structures and processes, as well as classical methods like simulated annealing, which is inspired by a thermodynamical process. The core principle of evolutionary algorithms is to app作者: 迎合 時(shí)間: 2025-3-23 12:04 作者: dialect 時(shí)間: 2025-3-23 17:19
Fundamental Evolutionary Algorithmsidates, procedures how to select individuals based on their fitness, and genetic operators with which modified solution candidates can be obtained. Equipped with these ingredients we proceed in this chapter to introducing basic forms of evolutionary algorithms, including classical genetic algorithms作者: archetype 時(shí)間: 2025-3-23 18:14
Special Applications and Techniquesnd of metaheuristics. In the first section we consider behavioral simulation for the iterated prisoners dilemma with an evolutionary algorithm. In the next section we study evolutionary algorithms for multi-criteria optimization, especially in the presence of conflicting criteria, which instead of r作者: 懶鬼才會(huì)衰弱 時(shí)間: 2025-3-24 01:05 作者: 刺穿 時(shí)間: 2025-3-24 02:23 作者: 幼稚 時(shí)間: 2025-3-24 07:07
Nonrelativistic Stochastic Quantum Mechanicsn to this field. Among such methods we find artificial neural networks, evolutionary algorithms, and fuzzy systems. Finally, we mention how to use this book and where additional material can be found the Internet.作者: 治愈 時(shí)間: 2025-3-24 13:32 作者: 勾引 時(shí)間: 2025-3-24 17:21
S. Bhatnagar,H. Prasad,L. Prashanthin undesired effects can be avoided by adapting the fitness function or the selection method. The last section of this chapter is devoted to genetic operators, which serve as tools to explore the search space, and covers sexual and asexual recombination and other variation techniques.作者: 改變 時(shí)間: 2025-3-24 19:20 作者: 乞丐 時(shí)間: 2025-3-25 00:53 作者: Obstruction 時(shí)間: 2025-3-25 03:20
Springer Tracts in Advanced Roboticsin the network input and activation functions, especially in the hidden layer. In this hidden layer . are employed, which are responsible for the name of this type of neural network. With these functions a kind of “catchment region” is assigned to each neuron, in which it mainly influences the output of the neural network.作者: Gnrh670 時(shí)間: 2025-3-25 08:47
Algorithms for Constrained Optimizationresent . and to solve them (approximately) in a numerical fashion. If the type of differential equation is known that describes a given system, but the values of the parameters appearing in it are unknown, one may also try to train a suitable recurrent network with the help of example patterns in order to determine the system parameters.作者: COUCH 時(shí)間: 2025-3-25 15:36 作者: hardheaded 時(shí)間: 2025-3-25 19:11 作者: 凝結(jié)劑 時(shí)間: 2025-3-25 21:51 作者: intrude 時(shí)間: 2025-3-26 01:09 作者: colloquial 時(shí)間: 2025-3-26 06:43
Recurrent Networksresent . and to solve them (approximately) in a numerical fashion. If the type of differential equation is known that describes a given system, but the values of the parameters appearing in it are unknown, one may also try to train a suitable recurrent network with the help of example patterns in order to determine the system parameters.作者: 范圍廣 時(shí)間: 2025-3-26 09:32
Introduction to Evolutionary Algorithmsas classical methods like simulated annealing, which is inspired by a thermodynamical process. The core principle of evolutionary algorithms is to apply evolution principles like mutation and selection to populations of candidate solutions in order to find a (sufficiently good) solution for a given optimization problem.作者: artless 時(shí)間: 2025-3-26 14:24 作者: 憤世嫉俗者 時(shí)間: 2025-3-26 19:25
Introduction,n to this field. Among such methods we find artificial neural networks, evolutionary algorithms, and fuzzy systems. Finally, we mention how to use this book and where additional material can be found the Internet.作者: urethritis 時(shí)間: 2025-3-26 22:32
Introductionst model.” The research area that is devoted to the study of connectionist models is called “connectionism.” Furthermore, the expression “parallel distributed processing” can often be found in relation to (artificial) neural networks.作者: emulsify 時(shí)間: 2025-3-27 02:19
Elements of Evolutionary Algorithmsin undesired effects can be avoided by adapting the fitness function or the selection method. The last section of this chapter is devoted to genetic operators, which serve as tools to explore the search space, and covers sexual and asexual recombination and other variation techniques.作者: Ophthalmoscope 時(shí)間: 2025-3-27 08:44 作者: 獨(dú)特性 時(shí)間: 2025-3-27 12:13 作者: 美學(xué) 時(shí)間: 2025-3-27 15:29
Fundamental Evolutionary Algorithmsh tries to derive function expressions or even (simple) program structures with evolutionary principles). Finally, we take a look at related population-based approaches (like ant colony and particle swarm optimization).作者: 婚姻生活 時(shí)間: 2025-3-27 21:07
Textbook 20131st editionlutionary algorithms, fuzzy systems and Bayesian networks; covers the latest approaches, including ant colony optimization and probabilistic graphical models; written by a team of highly-regarded experts in CI, with extensive experience in both academia and industry.作者: abnegate 時(shí)間: 2025-3-28 01:40 作者: 積極詞匯 時(shí)間: 2025-3-28 02:59
S. Bhatnagar,H. Prasad,L. PrashanthThe following sections treat mathematical topics that were presupposed in the text (e.g. about straight line equations and about regression), or side remarks, which would have disturbed the flow of the exposition (e.g. about activation transformation in a Hopfield network).作者: GUISE 時(shí)間: 2025-3-28 07:49 作者: 歌唱隊(duì) 時(shí)間: 2025-3-28 11:45 作者: 下垂 時(shí)間: 2025-3-28 15:06
Nonrelativistic Stochastic Quantum Mechanicsnd process knowledge about the given problem setting. For certain types of problems, techniques inspired by natural or biological processes proved successful. These techniques belong to the field of computational intelligence. Our main objective with this textbook is to give a methodical introductio作者: plasma-cells 時(shí)間: 2025-3-28 20:12 作者: 仔細(xì)閱讀 時(shí)間: 2025-3-29 02:17 作者: 音的強(qiáng)弱 時(shí)間: 2025-3-29 04:12
https://doi.org/10.1007/978-3-319-02609-1in this and the subsequent chapters to specific forms of (artificial) neural networks. We start with the best-known and most widely used form, the so-called . (MLP), which is closely related to the networks of threshold logic units we studied in a previous chapter. They exhibit a strictly layered st作者: 永久 時(shí)間: 2025-3-29 09:28
Springer Tracts in Advanced Roboticsf layers is always three, that is, there is exactly one hidden layer. In addition, radial basis function networks differ from multi-layer perceptrons in the network input and activation functions, especially in the hidden layer. In this hidden layer . are employed, which are responsible for the name作者: 破譯 時(shí)間: 2025-3-29 14:53 作者: 好忠告人 時(shí)間: 2025-3-29 19:32 作者: 成份 時(shí)間: 2025-3-29 20:07
Algorithms for Constrained Optimizationter, however, we lift all restrictions and consider recurrent networks without any constraints. Such general recurrent networks are well suited to represent . and to solve them (approximately) in a numerical fashion. If the type of differential equation is known that describes a given system, but th作者: 施舍 時(shí)間: 2025-3-30 03:57
S. Bhatnagar,H. Prasad,L. Prashanthhich also includes, for example, particle swarm and ant colony optimization, which are inspired by other biological structures and processes, as well as classical methods like simulated annealing, which is inspired by a thermodynamical process. The core principle of evolutionary algorithms is to app作者: atopic 時(shí)間: 2025-3-30 04:28 作者: bioavailability 時(shí)間: 2025-3-30 10:43
Maintenance Modeling and Policies,idates, procedures how to select individuals based on their fitness, and genetic operators with which modified solution candidates can be obtained. Equipped with these ingredients we proceed in this chapter to introducing basic forms of evolutionary algorithms, including classical genetic algorithms作者: 群居男女 時(shí)間: 2025-3-30 13:26 作者: EWER 時(shí)間: 2025-3-30 18:15 作者: licence 時(shí)間: 2025-3-30 23:43
https://doi.org/10.1007/978-1-4615-4391-6ed to the issue of extending the concept of mappings or functions to fuzzy sets. These ideas allow us to define operations like addition, subtraction, multiplication, division or taking squares as well as set theoretic concepts like the composition of relations for fuzzy sets.作者: oxidize 時(shí)間: 2025-3-31 01:24 作者: dagger 時(shí)間: 2025-3-31 05:11 作者: 嗎啡 時(shí)間: 2025-3-31 11:06
Computational Intelligence978-1-4471-5013-8Series ISSN 1868-0941 Series E-ISSN 1868-095X
