In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa...In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.展开更多
In this paper,the authors have empirically analyzed the convergence in per capita GDP gap and the convergence in the variation of energy intensity with respect to the change of per capita GDP between China and eight d...In this paper,the authors have empirically analyzed the convergence in per capita GDP gap and the convergence in the variation of energy intensity with respect to the change of per capita GDP between China and eight developed countries.Then,the authors run a regression on the impact of decisive factors of economic growth on energy intensity and its change,so as to find out the economic mechanism of energy intensity gap changing with respect to the variation of economic growth.This study concludes that:First,there is a convergence in per capita GDP gap between China and the eight developed countries.With the convergence in per capita GDP gap,the energy intensity gap between China and eight different countries also converge,and the convergence rate of the latter is faster than that of the former,i.e.if the per capita GDP gap between China and the eight developed countries decreases by 1%,the energy intensity gap between them will correspondingly decrease by 1.552%.Second,the energy intensity decreases with the improvement of industrial structure,the rising of energy prices,the advances of technology,and the expansion of investment in fixed assets,and it slightly increases with the increase of FDI.Third,the energy intensity gap between China and eight developed countries narrows with the lessening of the difference in fixed assets investment,energy prices,and technological progress between China and eight developed countries,yet increases with the narrowing of the difference in FDI,and has no significant correlation with the difference in industrial structure.Fourth,the narrowing of difference in per capita GDP between China and the eight developed countries can result in the lessening of energy intensity gap,whose economic mechanism is that the decisive factors,such as difference in investment,technology,and the competition mechanism of prices,which can determine the difference in economic growth,can significantly affect the energy intensity gap.展开更多
Kernel canonical correlation analysis(CCA) is a nonlinear extension of CCA,which aims at extract-ing the information shared by two random variables. It has wide applications in many fields,such as information retrieva...Kernel canonical correlation analysis(CCA) is a nonlinear extension of CCA,which aims at extract-ing the information shared by two random variables. It has wide applications in many fields,such as information retrieval. This paper gives the convergence rate analysis of kernel CCA under some approximation conditions and some suggestions on how to choose the regularization parameter. The result shows that the convergence rate only depends on two parameters:the rate of regularization parameter and the decay rate of eigenvalues of compact operator VY X,and it gives better understanding of kernel CCA.展开更多
Wavelet shrinkage is a strategy to obtain a nonlinear approximation to a given function f and is widely used in data compression,signal processing and statistics,etc.For Calder′on-Zygmund operators T,it is interestin...Wavelet shrinkage is a strategy to obtain a nonlinear approximation to a given function f and is widely used in data compression,signal processing and statistics,etc.For Calder′on-Zygmund operators T,it is interesting to construct estimator of T f,based on wavelet shrinkage estimator of f.With the help of a representation of operators on wavelets,due to Beylkin et al.,an estimator of T f is presented in this paper.The almost everywhere convergence and norm convergence of the proposed estimators are established.展开更多
基金Supported by the Major State Basic Research Development Program of China (2012CB720500)the National Natural Science Foundation of China (Key Program: U1162202)+1 种基金the National Natural Science Foundation of China (General Program:61174118)Shanghai Leading Academic Discipline Project (B504)
文摘In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
文摘In this paper,the authors have empirically analyzed the convergence in per capita GDP gap and the convergence in the variation of energy intensity with respect to the change of per capita GDP between China and eight developed countries.Then,the authors run a regression on the impact of decisive factors of economic growth on energy intensity and its change,so as to find out the economic mechanism of energy intensity gap changing with respect to the variation of economic growth.This study concludes that:First,there is a convergence in per capita GDP gap between China and the eight developed countries.With the convergence in per capita GDP gap,the energy intensity gap between China and eight different countries also converge,and the convergence rate of the latter is faster than that of the former,i.e.if the per capita GDP gap between China and the eight developed countries decreases by 1%,the energy intensity gap between them will correspondingly decrease by 1.552%.Second,the energy intensity decreases with the improvement of industrial structure,the rising of energy prices,the advances of technology,and the expansion of investment in fixed assets,and it slightly increases with the increase of FDI.Third,the energy intensity gap between China and eight developed countries narrows with the lessening of the difference in fixed assets investment,energy prices,and technological progress between China and eight developed countries,yet increases with the narrowing of the difference in FDI,and has no significant correlation with the difference in industrial structure.Fourth,the narrowing of difference in per capita GDP between China and the eight developed countries can result in the lessening of energy intensity gap,whose economic mechanism is that the decisive factors,such as difference in investment,technology,and the competition mechanism of prices,which can determine the difference in economic growth,can significantly affect the energy intensity gap.
基金supported by National Natural Science Foundation of China (Grant Nos. 11001247, 11071276)
文摘Kernel canonical correlation analysis(CCA) is a nonlinear extension of CCA,which aims at extract-ing the information shared by two random variables. It has wide applications in many fields,such as information retrieval. This paper gives the convergence rate analysis of kernel CCA under some approximation conditions and some suggestions on how to choose the regularization parameter. The result shows that the convergence rate only depends on two parameters:the rate of regularization parameter and the decay rate of eigenvalues of compact operator VY X,and it gives better understanding of kernel CCA.
基金supported by National Natural Science Foundation of China(Grant Nos.11171014 and 91130009)National Basic Research Program of China(Grant No.973-2010CB-731900)
文摘Wavelet shrinkage is a strategy to obtain a nonlinear approximation to a given function f and is widely used in data compression,signal processing and statistics,etc.For Calder′on-Zygmund operators T,it is interesting to construct estimator of T f,based on wavelet shrinkage estimator of f.With the help of a representation of operators on wavelets,due to Beylkin et al.,an estimator of T f is presented in this paper.The almost everywhere convergence and norm convergence of the proposed estimators are established.
