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Titlebook: Rough Sets and Knowledge Technology; First International Guo-Ying Wang,James F. Peters,Yiyu Yao Conference proceedings 2006 Springer-Verla

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Dayong Deng,Houkuan Huangudies as root production very often exceeds shoot production (Caldwell & Camp 1974; Coleman .. 1976; Lauenroth & Whitman 1977; Sims & Singh 1978; Persson 1978), thus determining to a large extent the input (quantitatively and qualitatively) of organic matter and nutrients into the soil. So, in order
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Hierarchical Machine Learning – A Learning Methodology Inspired by Human Intelligenceepresents the world at a certain grain-size and is denoted by a triplet, (., ., .) where . is a domain, .- the structure of ., .-the attribute of ...In this talk, we will discuss the hierarchical machine learning based on the proposed model. From the quotient space model point of view, a supervised
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Cognitive Neuroscience and Web Intelligenceph (EEG) experiments for obtaining various data from human cognitive mechanism, as well as how to analyze such data from multiple aspects for discovering new models of human cognition..In our studies, we propose a new methodology with a multi-step process, in which various psychological experiments,
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