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政大機構典藏 > 商學院 > 統計學系 > 學位論文 > Item 140.119/94418

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/94418

Title:	迴歸分析與類神經網路預測能力之比較 A comparison on the prediction performance of regression analysis and artificial neural networks
Authors:	楊雅媛
Contributors:	陳麗霞陳春龍楊雅媛
Keywords:	迴歸分析類神經網路區域搜尋法演化策略法類神經網路倒傳遞類神經網路 Regression analysis Artificial neural networks Local search methods Evolution strategies neural network (ESNN) Back-propagation neural network (BPNN)
Date:	2002
Issue Date:	2016-05-06 16:36:10 (UTC+8)
Abstract:	迴歸分析與類神經網路此兩種方法皆是預測領域上的主要工具。本論文嘗試在線性迴歸模式及非線性迴歸模式的條件下，隨機產生不同特性的資料以完整探討資料特性對迴歸分析與類神經網路之預測效果的影響。這些特性包括常態分配、偏態分配、不等變異、Michaelis-Menten關係模式及指數迴歸模式。 Both regression analysis and artificial neural networks are the main techniques for prediction. In this research, we tried to randomly generate different types of data, so as to completely explore the effect of data characteristics on the predictive performance of regression analysis and artificial neural networks. The data characteristics include normal distribution, skew distribution, unequal variances, Michaelis-Menten relationship model and exponential regression model.
Description:	碩士國立政治大學統計學系 88354017
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G91NCCU1932012
Data Type:	thesis
Appears in Collections:	[統計學系] 學位論文

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