標(biāo)題: Titlebook: EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation; Emilia Tantar,Alexandru-Adrian Tantar,Oliver Sch [打印本頁(yè)] 作者: 遮蔽 時(shí)間: 2025-3-21 19:02
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書(shū)目名稱(chēng)EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation被引頻次
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書(shū)目名稱(chēng)EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation讀者反饋
書(shū)目名稱(chēng)EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation讀者反饋學(xué)科排名
作者: HEDGE 時(shí)間: 2025-3-21 21:34 作者: Encephalitis 時(shí)間: 2025-3-22 03:03
Studies in Computational Intelligencehttp://image.papertrans.cn/e/image/300635.jpg作者: DEMUR 時(shí)間: 2025-3-22 07:35
https://doi.org/10.1007/978-3-642-32726-1Computational Intelligence; Evolutionary Computation; Probability; Set Oriented Numerics作者: 孵卵器 時(shí)間: 2025-3-22 11:20
978-3-642-44503-3Springer Berlin Heidelberg 2013作者: Harpoon 時(shí)間: 2025-3-22 13:55 作者: Harpoon 時(shí)間: 2025-3-22 17:41 作者: 有常識(shí) 時(shí)間: 2025-3-22 22:09 作者: 揮舞 時(shí)間: 2025-3-23 01:53 作者: 愛(ài)哭 時(shí)間: 2025-3-23 06:53 作者: 樹(shù)上結(jié)蜜糖 時(shí)間: 2025-3-23 10:41 作者: minimal 時(shí)間: 2025-3-23 14:17 作者: consolidate 時(shí)間: 2025-3-23 18:45 作者: 男生如果明白 時(shí)間: 2025-3-24 00:35 作者: ETHER 時(shí)間: 2025-3-24 04:55
ation. For single-objective scheduling problems, that is the optimization of task assignments to sparse resources over time, a variety of optimal algorithms or heuristic rules are available. However, in the multi-objective domain it is often impossible to provide specific and theoretically well foun作者: calamity 時(shí)間: 2025-3-24 07:03 作者: 無(wú)目標(biāo) 時(shí)間: 2025-3-24 14:19 作者: MUMP 時(shí)間: 2025-3-24 14:52
On the Foundations and the Applications of Evolutionary Computing tools leads to fascinating mathematics related to Feynman-Kac path integral theory and their interacting particle interpretations. In this chapter, we provide an introduction to the stochastic modeling and the theoretical analysis of these particle algorithms. We also illustrate these methods through several applications.作者: Spirometry 時(shí)間: 2025-3-24 20:24 作者: 堅(jiān)毅 時(shí)間: 2025-3-25 00:11
A Complex-Networks View of Hard Combinatorial Search Spacesnalysis is primarily based on decision problems, i.e. those that require a yes/no answer [7, 15], but the theory can readily be extended to optimization problems [16], roughly speaking, those in which we seek a solution with an associated minimum or maximum cost, which are the ones that will be dealt with here.作者: dermatomyositis 時(shí)間: 2025-3-25 06:58 作者: 嚴(yán)重傷害 時(shí)間: 2025-3-25 08:57
A Comparative Study of Heuristic Conversion Algorithms, Genetic Programming and Return Predictabilitdapt the buying and selling rules of the investigated algorithms resulting in a new algorithm. Results show that a genetic programming approach does not lead to good new algorithms. We extend former works by using the . as a measure of risk, and by applying competitive analysis.作者: 依法逮捕 時(shí)間: 2025-3-25 14:25 作者: 嘲笑 時(shí)間: 2025-3-25 16:37
eal-valued MOPs. We show the main aspects to be considered when building local search operators using the objective function gradients, and when coupling them with evolutionary algorithms. We present an overview of our current methods with discussion about their convenience for particular kinds of problems.作者: Narcissist 時(shí)間: 2025-3-25 20:21
Book 2013or creating a bridge between probability, set-oriented numerics and evolutionary computation. .The volume encloses a collection of contributions that were presented at the EVOLVE 2011 international workshop, held in Luxembourg, May 25-27, 2011, coming from invited speakers and also from selected reg作者: 沙草紙 時(shí)間: 2025-3-26 03:48 作者: Assemble 時(shí)間: 2025-3-26 08:09 作者: exceed 時(shí)間: 2025-3-26 12:28
https://doi.org/10.1007/978-3-7091-4832-7re for selecting the most important dependencies in EDAs by truncating regular vines. Moreover, this chapter also shows how the use of mutual information in the learning of graphical models implies a natural way of employing copula functions.作者: 不要不誠(chéng)實(shí) 時(shí)間: 2025-3-26 15:02 作者: forbid 時(shí)間: 2025-3-26 19:58
ar Genetic Algorithm(cGA).We replace themutation operator by amutation based on concepts of PSO. We present two hybrid algorithms and analyze their performance using a set of different problems. The results obtained are quite satisfactory in efficacy and efficiency, outperforming in most cases existing algorithms for a set of problems.作者: progestogen 時(shí)間: 2025-3-26 21:15
dapt the buying and selling rules of the investigated algorithms resulting in a new algorithm. Results show that a genetic programming approach does not lead to good new algorithms. We extend former works by using the . as a measure of risk, and by applying competitive analysis.作者: Bricklayer 時(shí)間: 2025-3-27 02:17 作者: AGOG 時(shí)間: 2025-3-27 06:25
On Gradient-Based Local Search to Hybridize Multi-objective Evolutionary Algorithmseal-valued MOPs. We show the main aspects to be considered when building local search operators using the objective function gradients, and when coupling them with evolutionary algorithms. We present an overview of our current methods with discussion about their convenience for particular kinds of problems.作者: Facilities 時(shí)間: 2025-3-27 12:08 作者: 注射器 時(shí)間: 2025-3-27 16:10
covering of .. Further, we present a class of multiobjective optimal control problems which can be efficiently handled by the set oriented continuation methods using a transformation into high-dimensionalMOPs. We illustrate all the methods on both academic and real world examples.作者: depreciate 時(shí)間: 2025-3-27 19:00
the design of efficient CCEAs schemes on two applications related to the modeling of an industrial agri-food process. The experiments correspond to complex optimisations encountered in the modeling of a Camembert-cheese ripening process. Two problems are considered:作者: triptans 時(shí)間: 2025-3-28 01:28 作者: REP 時(shí)間: 2025-3-28 05:28 作者: 策略 時(shí)間: 2025-3-28 07:01
Cooperative Coevolution for Agrifood Process Modelingthe design of efficient CCEAs schemes on two applications related to the modeling of an industrial agri-food process. The experiments correspond to complex optimisations encountered in the modeling of a Camembert-cheese ripening process. Two problems are considered:作者: 改變立場(chǎng) 時(shí)間: 2025-3-28 12:06 作者: GONG 時(shí)間: 2025-3-28 17:25
Incorporating Regular Vines in Estimation of Distribution Algorithmss. Several kinds of statistical dependencies among continuous variables can be taken into account by using regular vines. This work presents a procedure for selecting the most important dependencies in EDAs by truncating regular vines. Moreover, this chapter also shows how the use of mutual informat作者: TOXIC 時(shí)間: 2025-3-28 20:11
The Gaussian Polytree EDA with Copula Functions and Mutationslocal optimizers. The new construction and simulation algorithms, and its application to estimation of distribution algorithms with continuous Gaussian variables are also introduced. The algorithm for the construction of the structure and for edge orientation is based on information theoretic concep作者: 得罪人 時(shí)間: 2025-3-28 23:32
On Quality Indicators for Black-Box Level Set Approximationfor instance, when finding sets of solutions to optimization problems or in solving nonlinear equation systems. After defining and motivating level set problems from a decision theoretic perspective, we discuss quality indicators that could be used to measure how well a set of points approximates a 作者: 心痛 時(shí)間: 2025-3-29 06:43 作者: dithiolethione 時(shí)間: 2025-3-29 07:21
A Complex-Networks View of Hard Combinatorial Search Spacesstance, [15]). Thus, according to this point of view, large enough instances of these problems cannot be solved in reasonable time. The mathematical analysis is primarily based on decision problems, i.e. those that require a yes/no answer [7, 15], but the theory can readily be extended to optimizati作者: 左右連貫 時(shí)間: 2025-3-29 11:57 作者: 瘋狂 時(shí)間: 2025-3-29 18:44 作者: 傻 時(shí)間: 2025-3-29 21:20
On Gradient-Based Local Search to Hybridize Multi-objective Evolutionary Algorithmsolidated research area it counts with a number of guidelines and processes; even though, their efficiency is still a big issue which lets room for improvements. In this chapter we explore the use of gradient-based information to increase efficiency on evolutionary methods, when dealing with smooth r作者: assent 時(shí)間: 2025-3-30 01:13 作者: 裹住 時(shí)間: 2025-3-30 08:07 作者: 使熄滅 時(shí)間: 2025-3-30 09:36
A Comparative Study of Heuristic Conversion Algorithms, Genetic Programming and Return Predictabilitprocedure are used to test for predictive ability. Results show that the algorithms considered do not have predictive ability. Further, . is used to adapt the buying and selling rules of the investigated algorithms resulting in a new algorithm. Results show that a genetic programming approach does n作者: fodlder 時(shí)間: 2025-3-30 14:08
EVOLVE- A Bridge between Probability, Set Oriented Numerics and Evolutionary Computation
