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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8877

    Title: A novel predicting algorithm of thermostable proteins based on choquet integral with respect to L-measure and hurst exponent
    Authors: Shieh, Jiunn-I;Liu, Yu-Lung;Lee, Kuei-Jen;Chang, Pei-Chun;Liu, Yi-Cheng
    Contributors: Department of Information Science and Applications
    Keywords: Amines;Control theory;Cybernetics;Integral equations;Mathematical models;Proteins;Robot learning;Choquet integral;Cross validation;Fractal properties;Hurst exponent;Hurst exponents;L-measure;Multiple regression model;P-measure;Physicochemical property;Prediction methods;Prediction model;Prediction schemes;Regression model;Ridge regression;Singleton measures;Symbolic sequence
    Date: 2009
    Issue Date: 2010-04-08 20:36:02 (UTC+8)
    Publisher: Asia University
    Abstract: Establishing a good algorithm for predicting temperature of thermostable proteins is an important issue. In this study, a novel thermostable proteins prediction method using Hurst exponent and Choquet integral regression model based on L-measure and γ-support is proposed. The main idea of this method is to integrate the physicochemical properties, fractal property and Choquet integral regression model for amino symbolic sequences with different lengths. For evaluating the performance of this new algorithm, a 5-fold Cross-Validation MSE is performed. Experimental result shows that this new prediction scheme is better than the Choquet integral regression model based on λ-measure and P-measure, respectively and two methods based on Hurst exponent and the traditional prediction models, ridge regression and multiple regression model, respectively.
    Relation: Proceedings of the 2009 International Conference on Machine Learning and Cybernetics 6:3167-3171
    Appears in Collections:[行動商務與多媒體應用學系] 會議論文

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