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991.
Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 95–112, March–April, 1994. 相似文献
992.
993.
N. Yu. Kuznetsov 《Cybernetics and Systems Analysis》1994,30(3):419-439
Published in Kibernetika i Sistemnyi Analiz, No. 3, pp. 128–150, May–June, 1994. 相似文献
994.
S. Otakulov 《Cybernetics and Systems Analysis》1994,30(3):458-462
Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 172–176, May–June, 1994 相似文献
995.
This research was supported under project No. 6.02.02/128-93 as part of the state scientific-technical program on future information
technologies and systems by the Ukrainian State Committee, of Science and Technology. 相似文献
996.
997.
998.
This paper is a reply to Laviolette and Seaman's critical discussion of fuzzy set theory. Rather than questioning the interest of the Bayesian approach to uncertainty, some reasons why Bayesian find the idea of a fuzzy set not palatable are laid bare. Some links between fuzzy sets and probability that Laviolette and Seaman seem not to be aware of are pointed out. These links suggest that, contrary to the claim sometimes found in the literature, probability theory is not a special case of fuzzy set theory. The major objection to Laviolette and Seaman is that they found their critique on as very limited view of fuzzy sets, including debatable papers, while they fail to account for significant works pertaining to axiomatic derivation of fuzzy set connectives, possibility theory, fuzzy random variables, among others 相似文献
999.
In the editorial by J.C. Bezdek (ibid., p.1), an example is presented to demonstrate differences between fuzzy membership and probability. The authors argue that probability can be used in a way much more closely analogous to this use of fuzzy membership, weakening the argument for the latter 相似文献
1000.
First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen 相似文献