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Titlebook: Data Science and Big Data: An Environment of Computational Intelligence; Witold Pedrycz,Shyi-Ming Chen Book 2017 Springer International Pu

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發(fā)表于 2025-3-28 17:02:11 | 只看該作者
Aimilios Lallas,Horacio Cabo,Gabriel Salernitrol of their consumption. On the other hand, the ever-increasing pervasiveness of technology together with the smart paradigm, are becoming the reference point of anyone involved in innovation, and energy management issues. In this context, the information that can potentially be made available by
42#
發(fā)表于 2025-3-28 22:04:04 | 只看該作者
Digestion and Absorption of Carbohydratesmple is to design a smart agent to make decisions within environment in response to the presence of human beings. Smart building/home is a typical computational intelligence based system enriched with sensors to gather information and processors to analyze it. Indoor computational intelligence based
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發(fā)表于 2025-3-28 23:44:49 | 只看該作者
Digestion and Absorption of Lipidsramatically escalating, mainly due to the high level of exposure of the network components to weather elements. Combined, 75% of power outages are either directly caused by weather-inflicted faults (e.g., lightning, wind impact), or indirectly by equipment failures due to wear and tear combined with
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發(fā)表于 2025-3-29 03:25:24 | 只看該作者
Data Science and Big Data: An Environment of Computational Intelligence978-3-319-53474-9Series ISSN 2197-6503 Series E-ISSN 2197-6511
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發(fā)表于 2025-3-29 07:45:14 | 只看該作者
Large-Scale Clustering Algorithmsossible: (i) adapt available algorithms or design new approaches such that they can run on a distributed computing environment (ii) develop model-based learning techniques that can be trained efficiently on a small subset of the data and make reliable predictions. In this chapter two recent algorith
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發(fā)表于 2025-3-29 11:40:00 | 只看該作者
On High Dimensional Searching Spaces and Learning Methodss, the membership assignments, and distance or similarity functions. In this chapter we describe different data types, membership functions, and similarity functions and discuss the pros and cons of using each of them. Conventional similarity functions evaluate objects in the vector space. Contraril
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發(fā)表于 2025-3-29 17:42:29 | 只看該作者
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發(fā)表于 2025-3-29 21:49:13 | 只看該作者
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