否认 发表于 2025-3-27 00:58:24
https://doi.org/10.1007/978-1-4471-0819-1DNA computing; artificial neural network; case-based reasoning; data mining; emotion; evolution; evolutionOffensive 发表于 2025-3-27 01:23:22
978-1-85233-062-0Springer-Verlag London Limited 1999OVER 发表于 2025-3-27 08:51:13
STPA Guided Systems EngineeringThis paper is devoted to an intelligent approach towards the total glass production management in glass furnaces, and to a presentation of recent results. The global approach based on three-layered multiagent expert system architecture is explained, together with some details about various furnace parts control.BALE 发表于 2025-3-27 12:23:03
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Rajkumar Roy,Takeshi Furuhashi,Pravir K. ChawdhryA unique collection of research papers from leading experts around the world presented in one volume Innovative techniques on evolutionary design and optimisation are a main topic of the book The editpineal-gland 发表于 2025-3-27 18:00:45
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Arnaud Gotlieb,Morten Mossige,Helge Spiekerd. Conventional computing is considered to be ‘hard’, because it is limited to represent human like ‘vagueness’. Soft computing provides the opportunity to represent ‘ambiguity’ in human thinking with the real life ‘uncertainty’. The concept is proved to be useful for many real life problems. The pr遭遇 发表于 2025-3-28 05:46:08
https://doi.org/10.1007/978-3-319-24255-2ural progression from traditional design databases to systems that are created to more actively support knowledge-based design. In contrast to traditional design databases, design repositories serve not only as archives, but as repositories of heterogeneous information that are designed to enable reisotope 发表于 2025-3-28 07:47:34
Computer Safety, Reliability, and Securityrol systems. This approach is called evolving connectionist systems (ECOS). ECOS evolve through incremental, on-line learning. They can accommodate any new input data, including new features, new classes, etc. New connections and new neurons are created during operation. The ECOS framework is illust慷慨援助 发表于 2025-3-28 12:31:36
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