An Integrated Algorithm of Liu´s Generalized Lambda-Measure Based Choquet Integral and Hurst Exponent

In this paper, a novel integrated algorithm of Choquet integral with respect to Liu´s generalized Lambda-measure and Hurst exponent was proposed, it can be used for predicting the temperature of thermos table proteins on some useful physicochemical quantities of each amino symbolic sequence with different lengths. A real data set of the temperature of thermos table proteins with 5-fold cross-validation MSE is conducted, for comparing the performances of the integrated algorithm of Hurst exponent and Choquet integral regression model with respect to six measures, P-measure, λ-measure, L-measure, extensional L-measure, generalized L-measure and Liu, s generalized Lambda-measure, respectively, and two traditional regression model, multiple regression model and ridge regression model, the results show that the integrated algorithm of Hurst exponent and Choquet integral regression model with respect to Liu´s generalized Lambda-measure has the best performance.