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Titlebook: Evolutionary Computing; AISB Workshop, Brigh Terence C. Fogarty Conference proceedings 1996 Springer-Verlag Berlin Heidelberg 1996 artifici

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11#
發(fā)表于 2025-3-23 10:26:43 | 只看該作者
Evaluating European Education Policy-Makingion of the populations. In this context it is important to fully understand the temporal characteristics of the algorithm. This paper endeavours to model the genetic algorithm using temporal logic, with the emphasis on population characteristics and the evolution of populations towards convergence.
12#
發(fā)表于 2025-3-23 15:16:24 | 只看該作者
13#
發(fā)表于 2025-3-23 22:03:30 | 只看該作者
Generation of structured process models using Genetic Programming, consuming even for experienced experts..This paper reports on a new method for the design of structured process models based on the metaphor of Genetic Programming. This new methodology allows the automatic generation of non-linear process models in a self-organizing way.
14#
發(fā)表于 2025-3-23 22:58:28 | 只看該作者
15#
發(fā)表于 2025-3-24 06:15:49 | 只看該作者
16#
發(fā)表于 2025-3-24 10:06:42 | 只看該作者
Evolutionary Computing978-3-540-70671-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
17#
發(fā)表于 2025-3-24 14:39:23 | 只看該作者
Quality of Life and Longer Term Outcomesermining RBF network architecture (number of hidden layer nodes, basis function centres and widths) in conjunction with supervised gradient-based learning for tuning connection weights. A direct encoding of RBF hidden layer node basis function centres and widths is employed. The genetic operators ut
18#
發(fā)表于 2025-3-24 17:54:56 | 只看該作者
https://doi.org/10.1057/9781137313799but, where the proposed synthesis consist of many individual steps, there is also a combinatorial difficulty to be solved. This paper discusses the use of a modified ant system algorithm to tackle the synthetic design problem.
19#
發(fā)表于 2025-3-24 20:46:17 | 只看該作者
20#
發(fā)表于 2025-3-24 23:54:54 | 只看該作者
Case-Studies in Economic Development and the evolution of free-form 3D shapes. On the first aspect, a thorough comparison of ten different search techniques applied to a wing-box design optimisation problem is described. The techniques used vary from deterministic gradient descent to stochastic Simulated Annealing (SA) and Genetic Alg
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