Yao X. and Liu Y. (1997): "EPNet for chaotic timeseries prediction". In: Yao X., Kim J.H. and Furuhashi T. (eds): Simulated Evolution and Learning, Lecture Notes in Artificial Intelligence, Vol. 1285, pp.146-156, Springer-Verlag, Berlin. Home/Search Document Details and Download
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Recent New Development in Evolutionary Programming - Yao Self-citation (Yao) (Correct)
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X. Yao and Y. Liu, "EPNet for chaotic time-series prediction," in Selected Papers from the Frist Asia-Pacific Conference on Simulated Evolution and Learning (SEAL'96) (X. Yao, J.-H. Kim, and T. Furuhashi, eds.), vol. 1285 of Lecture Notes in Artificial Intelligence, (Berlin), pp. 146-- 156, Springer-Verlag, 1997.
Evolving Artificial Neural Networks - Yao (1999) (66 citations) Self-citation (Yao) (Correct)
....have been taken in the direct encoding scheme. The first separates the evolution of architectures from that of connection weights [24] 150] 153] 154] 165] 167] 169] 170] The second approach evolves architectures and connection weights simultaneously [149] 179] 180] 182] [185] [200] This section will focus on the first approach. The second approach will be discussed in Section III D. In the first approach, each connection of an architecture is directly specified by its binary representation [24] 150] 153] 154] 165] 167] 169] 170] 202] For example, ....
....their hidden nodes differently have two different genotypical representations, the probability of producing a highly fit offspring by recombining them is often very low. Some researchers thus avoided crossover and adopted only mutations in the evolution of architectures [45] 128] 149] 179] [185] [197] 217] 223] although it has been shown that crossover may be useful and important in increasing the efficiency of evolution for some problems [48] 113] 212] 229] Hancock [113] suggested that the permutation problem might not be as severe as had been supposed with the population ....
[Article contains additional citation context not shown here]
X. Yao and Y. Liu, "EPNet for chaotic time-series prediction," in Select. Papers 1st Asia-Pacific Conf. Simulated Evolution and Learning (SEAL'96), vol. 1285 of Lecture Notes in Artificial Intelligence, X. Yao, J.-H. Kim, and T. Furuhashi, Eds. Berlin, Germany: Springer-Verlag, 1997, pp. 146--156.
Knowledge Extracted From Trained Neural Networks - Yao (1999) (66 citations) Self-citation (Yao) (Correct)
....parents from the population based on their fitness. 5. Apply search operators to the parents and generate offspring which form the next generation. Figure 6: A typical cycle of the evolution of architectures. Considerable research on evolving ANN architectures has been carried out in recent years [33, 42, 45, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 149, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 138, 213, 214, 215, 216, 118, 130, 127, 217, 218, 219, 220, 221, 222, 223, 128, 224, 225]. Most of the research has concentrated on the evolution of ANN topological structures. Relatively little has been done on the evolution of node transfer functions, let al..one the simultaneous evolution of both topological structures and node transfer functions. In this paper, we will analyze the ....
....Encoding Scheme Two different approaches have been taken in the direct encoding scheme. The first separates the evolution of architectures from that of connection weights [154, 153, 150, 24, 170, 169, 165, 167] The second approach evolves architectures and connection weights simultaneously [179, 180, 182, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 149, 198, 199, 200]. This section will focus on the first approach. The second approach will be discussed in Section 3.4. In the first approach, each connection of an architecture is directly specified by its binary representation [154, 153, 150, 24, 170, 169, 165, 167, 202] For example, an N Theta N matrix C = c ....
[Article contains additional citation context not shown here]
X. Yao and Y. Liu, "EPNet for chaotic time-series prediction," in Selected Papers from the Frist Asia-Pacific Conference on Simulated Evolution and Learning (SEAL'96) (X. Yao, J.-H. Kim, and T. Furuhashi, eds.), vol. 1285 of Lecture Notes in Artificial Intelligence, (Berlin), pp. 146--156, Springer-Verlag, 1997.
A Multi-agent Based Simulated Stock Market - Testing on.. - Kendall, Su (2003) (Correct)
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Yao X. and Liu Y. (1997): "EPNet for chaotic timeseries prediction". In: Yao X., Kim J.H. and Furuhashi T. (eds): Simulated Evolution and Learning, Lecture Notes in Artificial Intelligence, Vol. 1285, pp.146-156, Springer-Verlag, Berlin.
A Multi-agent Based Simulated Stock Market - Testing on.. - Kendall, Su (2003) (Correct)
No context found.
Yao X. and Liu Y. (1997): "EPNet for chaotic timeseries prediction". In: Yao X., Kim J.H. and Furuhashi T. (eds): Simulated Evolution and Learning, Lecture Notes in Artificial Intelligence, Vol. 1285, pp.146-156, Springer-Verlag, Berlin.
On Making Problems Evolutionarily Friendly Part 1: Evolving .. - Sebald Chellapilla (1998) (1 citation) (Correct)
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Yao X, Liu Y (1997), "EPNet for chaotic time-series prediction," Simulated Evolution and Learning. First Asia-Pacific Conference, pp. 146-156, Berlin: Springer-Verlag, 1997.
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