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標(biāo)題: Titlebook: Gene Expression Programming; Mathematical Modelin Candida Ferreira Book 2006Latest edition Springer-Verlag Berlin Heidelberg 2006 algorithm [打印本頁(yè)]

作者: 初生    時(shí)間: 2025-3-21 16:53
書目名稱Gene Expression Programming影響因子(影響力)




書目名稱Gene Expression Programming影響因子(影響力)學(xué)科排名




書目名稱Gene Expression Programming網(wǎng)絡(luò)公開度




書目名稱Gene Expression Programming網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Gene Expression Programming被引頻次




書目名稱Gene Expression Programming被引頻次學(xué)科排名




書目名稱Gene Expression Programming年度引用




書目名稱Gene Expression Programming年度引用學(xué)科排名




書目名稱Gene Expression Programming讀者反饋




書目名稱Gene Expression Programming讀者反饋學(xué)科排名





作者: Crumple    時(shí)間: 2025-3-21 22:59
1860-949X tially revised and extended with five new chapters, including a new chapter describing two new algorithms for inducing decision trees with nominal and numeric/mixed attributes..978-3-642-06932-1978-3-540-32849-0Series ISSN 1860-949X Series E-ISSN 1860-9503
作者: OREX    時(shí)間: 2025-3-22 00:46

作者: certain    時(shí)間: 2025-3-22 06:59
Book 2006Latest editiongists...This second edition has been substantially revised and extended with five new chapters, including a new chapter describing two new algorithms for inducing decision trees with nominal and numeric/mixed attributes..
作者: 槍支    時(shí)間: 2025-3-22 10:32
Huajian Yao,Ying Liu,Zhiqi Zhang represent. The rules are also quite simple: they determine the spatial organization of the functions and terminals in the expression trees and the type of interaction between sub-expression trees in multigenic systems.
作者: 哀求    時(shí)間: 2025-3-22 15:48
China Sourcing und Wertsch?pfung in Chinats. These new individuals are, in their turn, subjected to the same developmental process: expression of the genomes, confrontation of the selection environment, selection, and reproduction with modification. The process is repeated for a certain number of generations or until a good solution has been found.
作者: 哀求    時(shí)間: 2025-3-22 20:14
https://doi.org/10.1007/978-981-16-1618-1gst themselves. Furthermore, the ADFs of genetic programming are further constrained by the number of arguments each takes, as the number of arguments must be a priori defined and cannot be changed during evolution.
作者: 吝嗇性    時(shí)間: 2025-3-23 00:01

作者: Console    時(shí)間: 2025-3-23 03:04

作者: 推崇    時(shí)間: 2025-3-23 08:46
Automatically Defined Functions in Problem Solving,gst themselves. Furthermore, the ADFs of genetic programming are further constrained by the number of arguments each takes, as the number of arguments must be a priori defined and cannot be changed during evolution.
作者: 灌輸    時(shí)間: 2025-3-23 12:34

作者: 衣服    時(shí)間: 2025-3-23 16:15

作者: 外觀    時(shí)間: 2025-3-23 18:33
Book 2006Latest edition This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained introduction to this new exciting field of computational intelligence, including several new algorithms fo
作者: Estrogen    時(shí)間: 2025-3-24 01:07
Racing with the Chinese Dragonshapes (parse trees); and in GEP the individuals are also nonlinear entities of different sizes and shapes (expression trees), but these complex entities are encoded as simple strings of fixed length (chromosomes).
作者: 向宇宙    時(shí)間: 2025-3-24 02:45

作者: adipose-tissue    時(shí)間: 2025-3-24 07:47
1860-949X asic ideas of gene expression programming (GEP) and numerous modifications to this powerful new algorithm. This monograph provides all the implementation details of GEP so that anyone with elementary programming skills will be able to implement it themselves. The book also includes a self-contained
作者: Ergots    時(shí)間: 2025-3-24 10:54

作者: 尊敬    時(shí)間: 2025-3-24 18:38

作者: 撫育    時(shí)間: 2025-3-24 21:28

作者: fatuity    時(shí)間: 2025-3-24 23:35

作者: 繼承人    時(shí)間: 2025-3-25 07:25

作者: 抗體    時(shí)間: 2025-3-25 08:35

作者: 間接    時(shí)間: 2025-3-25 14:08
Design of Neural Networks,ons between the units or nodes are usually weighted by real-valued weights. Weights are the primary means of learning in neural networks, and a learning algorithm is usually used to adjust the weights.
作者: 蚊子    時(shí)間: 2025-3-25 16:15

作者: 提煉    時(shí)間: 2025-3-25 20:37
Candida FerreiraPresents an exciting new development out of Genetic Algorithms.Includes supplementary material:
作者: 制定    時(shí)間: 2025-3-26 00:37

作者: 捕鯨魚叉    時(shí)間: 2025-3-26 07:17
Decision tree induction is extremely popular in data mining, with most currently available techniques being refinements of Quinlan’s original work (Quinlan 1986). His divide-and-conquer approach to decision tree induction involves selecting an attribute to place at the root node and then make the same decision about every other node in the tree.
作者: Hyperplasia    時(shí)間: 2025-3-26 10:59
Numerical Constants and the GEP-RNC Algorithm,Numerical constants are an integral part of most mathematical models and, therefore, it is important to allow their integration in the models designed by evolutionary techniques.
作者: electrolyte    時(shí)間: 2025-3-26 13:47
Decision Tree Induction,Decision tree induction is extremely popular in data mining, with most currently available techniques being refinements of Quinlan’s original work (Quinlan 1986). His divide-and-conquer approach to decision tree induction involves selecting an attribute to place at the root node and then make the same decision about every other node in the tree.
作者: harpsichord    時(shí)間: 2025-3-26 19:38
https://doi.org/10.1007/3-540-32849-1algorithms; artificial intelligence; combinatorial optimization; computer; logic; modeling; optimization; p
作者: Chemotherapy    時(shí)間: 2025-3-27 00:01
978-3-642-06932-1Springer-Verlag Berlin Heidelberg 2006
作者: Ballad    時(shí)間: 2025-3-27 02:27

作者: paleolithic    時(shí)間: 2025-3-27 06:12

作者: 其他    時(shí)間: 2025-3-27 10:46
Huajian Yao,Ying Liu,Zhiqi Zhangtwo: the chromosomes and the expression trees, the latter consisting of the expression of the genetic information encoded in the former. The process of information decoding (from the chromosomes to the expression trees) is called translation. And this translation implies obviously a kind of code and
作者: Adulate    時(shí)間: 2025-3-27 13:36
China Sourcing und Wertsch?pfung in Chinan of the chromosomes of a certain number of individuals (the initial population). Then these chromosomes are expressed and the fitness of each individual is evaluated against a set of fitness cases (also called selection environment which, in fact, is the input to a problem). The individuals are the
作者: 招人嫉妒    時(shí)間: 2025-3-27 19:55

作者: 展覽    時(shí)間: 2025-3-27 23:08
https://doi.org/10.1007/978-981-16-1618-1y a rigid syntax in which an S-expression, with a LIST-. function on the root, lists .-1 function-defining branches and one value-returning branch (Figure 6.1). The function-defining branches are used to create ADFs that may or may not be called upon by the value-returning branch. Such rigid structu
作者: 切割    時(shí)間: 2025-3-28 05:13
https://doi.org/10.1007/978-3-319-52893-9ls. Then we are going to discuss the importance of these so called Kolmogorov- Gabor polynomials in evolutionary modeling by comparing the performance of this new algorithm, GEP-KGP (GEP for inducing Kolmogorov-Gabor polynomials), with much simpler and much more intelligible GEP systems. The chapter
作者: resilience    時(shí)間: 2025-3-28 07:59
se, the simple chromosomes of the GA encode the values of the different parameters. Whether in binary or floating-point format, the different parameters of a function are directly encoded in the simple GA chromosomes.
作者: Apogee    時(shí)間: 2025-3-28 11:03
Chinese Socialism and Global Capitalismons between the units or nodes are usually weighted by real-valued weights. Weights are the primary means of learning in neural networks, and a learning algorithm is usually used to adjust the weights.
作者: Engulf    時(shí)間: 2025-3-28 18:40
India: Fifty years after Independencehe head length . is zero. Then, applying equation (2.4) for determining tail length, we get a gene length . = 1 and genes exclusively composed of terminals. So, in its simplest representation, gene expression programming is equivalent to the canonical genetic algorithm in which each gene consists of
作者: 英寸    時(shí)間: 2025-3-28 19:01

作者: somnambulism    時(shí)間: 2025-3-28 23:28
Introduction: The Biological Perspective,s (GAs) and genetic programming (GP). All three algorithms belong to the wider class of Genetic Algorithms (the use of capitals here is meant to distinguish this wider class from the canonical GA) as all of them use populations of individuals, select the individuals according to fitness, and introdu
作者: finite    時(shí)間: 2025-3-29 04:47

作者: 制造    時(shí)間: 2025-3-29 10:02

作者: phase-2-enzyme    時(shí)間: 2025-3-29 15:28

作者: Chivalrous    時(shí)間: 2025-3-29 16:04
Automatically Defined Functions in Problem Solving,y a rigid syntax in which an S-expression, with a LIST-. function on the root, lists .-1 function-defining branches and one value-returning branch (Figure 6.1). The function-defining branches are used to create ADFs that may or may not be called upon by the value-returning branch. Such rigid structu
作者: mastopexy    時(shí)間: 2025-3-29 23:29

作者: Aphorism    時(shí)間: 2025-3-30 03:13

作者: 連鎖,連串    時(shí)間: 2025-3-30 06:44
Design of Neural Networks,ons between the units or nodes are usually weighted by real-valued weights. Weights are the primary means of learning in neural networks, and a learning algorithm is usually used to adjust the weights.




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