Titlebook: Genetic Programming; First European Works Wolfgang Banzhaf,Riccardo Poli,Terence C. Fogarty Conference proceedings 1998 Springer-Verlag Ber

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書目名稱Genetic Programming影響因子(影響力)




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




書目名稱Genetic Programming網(wǎng)絡(luò)公開(kāi)度




書目名稱Genetic Programming網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Genetic Programming被引頻次




書目名稱Genetic Programming被引頻次學(xué)科排名




書目名稱Genetic Programming年度引用




書目名稱Genetic Programming年度引用學(xué)科排名




書目名稱Genetic Programming讀者反饋




書目名稱Genetic Programming讀者反饋學(xué)科排名

蓋他為秘密

Where does the good stuff go, and why? how contextual semantics influences program structure in simty of genetic program trees during the evolutionary process. We show that contextual semantics influence the composition, location and flows of operative code in a program. In detail we analyze these dynamics and discuss the impact of our findings on micro-level descriptions of genetic programming.

變化無(wú)常

凹槽

Concepts of inductive genetic programming,g tasks. We review the components of the method, and propose new approaches to some open issues such as: the sensitivity of the operators to the topology of the genetic program trees, the coordination of the operators, and the investigation of their performance. The genetic operators are examined by

Campaign

Immediate transfer of global improvements to all individuals in a population compared to automatica, an improvement in a part of a program (an ADF or a main body) can only be transferred via crossover. In this article, we consider whether it is a good idea to transfer immediately improvements found by a single individual to the whole population. A system that implements this idea has been propose

GULF

Non-destructive depth-dependent crossover for genetic programming,rmal crossover, i.e., building blocks are broken unexpectedly. In the depth-dependent crossover, the depth selection ratio was varied according to the depth of a node. However, the depth-dependent crossover did not work very effectively as generated programs became larger. To overcome this, we intro

GULF

Grammatical evolution: Evolving programs for an arbitrary language,nition is mapped to a program, expressions and programs of arbitrary complexity may be evolved. Other automatic programming methods are described, before our system, ., is applied to a symbolic regression problem.

結(jié)構(gòu)

喚醒

Speech sound discrimination with genetic programming, data of human speech. We examine whether a genetic programming algorithm can find programs that are able to discriminate certain spoken vowels and consonants. We present evidence that this can indeed be achieved with a surprisingly simple approach that does not need preprocessing. The data we have

漂泊

Efficient evolution of asymmetric recurrent neural networks using a PDGP-inspired two-dimensional rent architectures have been hindered by the fact that available training algorithms are considerably more complex than those for feedforward networks. In this paper, we present a new method to build recurrent neural networks based on evolutionary computation, which combines a linear chromosome with