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模糊數據的局部加權回歸 / Locally weighted regression of fuzzy data陳帥 Unknown Date (has links)
目標:本文旨在建構一種新型的模糊回歸模式,解決一类較複雜的模糊回歸問題。
研究方法:推廣局部加權回歸的思想,先從理論上構建新模型;然後借由模拟數據,從多個方面考察新模型的性質,并和其他模型做比較。
發現:局部加權回歸方法結合模糊隸屬度概念,使模糊回歸理論有更多的應用場合。
原創性:目前在模糊回歸領域的主流思想是通過線性規劃等方法來構建模型,而本文另闢蹊徑,首次從局部加權的角度構建了模糊回歸的新模型。
關鍵字: 模糊理論 模糊回歸分析 局部加權 / Objective: This paper aims to construct a new fuzzy regression model to solve a more complex fuzzy regression problem.
Method: Build a new model by promoting the idea of locally weighted regression; Using simulated data to compare the new model with other models.
Conclusion: The fuzzy membership degree concept combined with the locally weighted regression method makes the fuzzy regression theory have more applications.
Originality: At present, the main idea in the field of fuzzy regression is to construct models by means of linear programming. In this paper, a new model of fuzzy regression is constructed from the perspective of locally weighted method for the first time.
Keyword: Fuzzy theory、 Fuzzy regression、Locally weighted method
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