Mumble 发表于 2025-3-23 13:29:21

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occult 发表于 2025-3-23 16:04:13

Julie A. Worley,Johnny L. Matsonf scientific data. We then shortly present our contributions to this field in the form of original methods for the automatic classification of documents and easy interpretation of their content through characteristic keywords and classes created by our algorithms. In a second step, we focus our anal

abysmal 发表于 2025-3-23 19:09:14

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非实体 发表于 2025-3-24 01:17:47

Single-Case Experimental Designswhen rules are not organized into any structure, the system is inefficient. In the author’s opinion, modification of both the knowledge base structure and inference algorithms lead to improve the efficiency of the inference process. Rules partition enables reducing significantly the percentage of th

间谍活动 发表于 2025-3-24 02:55:39

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Custodian 发表于 2025-3-24 07:21:52

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同时发生 发表于 2025-3-24 11:21:17

Single-Case Experimental Designsid memetic approach where local (gradient descent) and global (differential evolution) approach are combined to tune parameters of a neuro-fuzzy system. Application of the memetic approach results in lower error rates than either gradient descent optimisation or differential evolution alone. The res

FLAGR 发表于 2025-3-24 16:42:24

Single-Case Experimental Designs data the firing strength of the rules cannot be calculated. Some neuro-fuzzy systems impute the missing firing strength. This approach has been successfully applied. Unfortunately in some cases the imputed firing strength values are very low for all rules and data items are poorly recognized by the

STIT 发表于 2025-3-24 19:04:41

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COUCH 发表于 2025-3-25 00:23:44

Anthony M. Graziano,James N. Katze protection of national heritage, so important nowadays, requires a multicriteria assessment. Seeing that different factors in varying degrees affect the comprehensive assessment of the object, it becomes necessary to use computational intelligence methods. This paper presents a rough sets approach
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查看完整版本: Titlebook: Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge ; 12th International C Stanisław Koziel