2005年, 第18卷, 第1期　刊出日期：2005-01-15

  

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  TIME SERIES FORECASTING WITH MULTIPLE CANDIDATE MODELS: SELECTING OR COMBINING?

  Le An YU;Shou Yang WANG;K. K. Lai;Y. Nakamori

  Journal of Systems Science and Complexity. 2005, 18(1): 1-018.

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  Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study. The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.
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  THE GLOBAL STABILITY OF A COMPETING CHEMOSTAT MODEL WITH DELAYED NUTRIENT RECYCLING

  Li Qiang JIANG;Zhi Een MA;P. Fergola

  Journal of Systems Science and Complexity. 2005, 18(1): 19-026.

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  In this paper, by applying the method of Liapunov functionals we study the global stability of the positive equilibrium of a competing chemostat model with delayed nutrient recycling. The sufficient conditions of the global stability (involved in average time delay or not) are obtained.
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  GOODNESS-OF-FIT TEST WITH GENETIC BACKGROUND

  Ji Hua WU;Min Yu XIE;Rong PENG;Zhi Hua SUN

  Journal of Systems Science and Complexity. 2005, 18(1): 27-034.

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  The chi-square test is a well-known goodness-of-fit test. It is available for arbitrary alternative hypothesis, particularly for a very general alternative. However, when the alternative is a ``one-sided'' hypothesis, which usually appears in genetic linkage analysis, the chi-square test does not use the information offered by the one-sided hypothesis. Therefore, it is possible that an appropriate one-sided test, which uses the information, will be better than the chi-square test. This paper gives such an efficient one-sided test. Monte Carlo simulation results show that it is more powerful than the chi-square test, and its power has been increased by 30 percent as compared with that of the chi-square test in most situations.
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  CONTROLLABILITY OF EVOLUTION INCLUSIONS WITH NONLOCAL CONDITIONS

  Guo Cheng LI;Shi Ji SONG;Cheng WU

  Journal of Systems Science and Complexity. 2005, 18(1): 35-042.

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  In this paper we examine controllability problems of evolution inclusions with nonlocal conditions. Using Kakutani's fixed point theorem and Schauder's fixed point theorem, we establish sufficient conditions for the controllability under convex and nonconvex orientor fields respectively.
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  AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR

  Li JIA;Jin Shou YU

  Journal of Systems Science and Complexity. 2005, 18(1): 43-054.

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  In this paper, an intelligent control system based on recurrent neural fuzzy network is presented for complex, uncertain and nonlinear processes, in which a recurrent neural fuzzy network is used as controller (RNFNC) to control a process adaptively and a recurrent neural network based on recursive predictive error algorithm (RNNM) is utilized to estimate the gradient information $\partial \hat{y}/\partial u$ for optimizing the parameters of controller. Compared with many neural fuzzy control systems, it uses recurrent neural network to realize the fuzzy controller. Moreover, recursive predictive error algorithm (RPE) is implemented to construct RNNM on line. Lastly, in order to evaluate the performance of the proposed control system, the presented control system is applied to continuously stirred tank reactor (CSTR). Simulation comparisons, based on control effect and output error, with general fuzzy controller and feed-forward neural fuzzy network controller (FNFNC), are conducted. In addition, the rates of convergence of RNNM respectively using RPE algorithm and gradient learning algorithm are also compared. The results show that the proposed control system is better for controlling uncertain and nonlinear processes.
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  ON THE SECOND GREEDY WEIGHT FOR LINEAR CODES SATISFYING THE FULLRANK CONDITION

  Wen De CHEN;KL\O VE Torleiv

  Journal of Systems Science and Complexity. 2005, 18(1): 55-066.

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  The maximum of $g_2-d_2$ for linear $[n,k,d;q]$ codes $C$ is studied. Here $d_2$ is the smallest size of the support of 2-dimensional subcodes of $C$ and $g_2$ is the smallest size of the support of 2-dimensional subcodes of $C$ which contains a codeword of weight $d$. The extra cost to the greedy adversary to get two symbols of information using some algorithm is $g_2-d_2$. For codes satisfying the fullrank condition of general dimensions, upper bounds on the maximum of $g_2-d_2$ are given. Under some condition we have got code $C$ where $g_2-d_2$ reaches the upper bound.
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  TO IMPROVE THE COMMUNICATION DELAY BY UPGRADING NODES IN A CONTINUOUS VERSION

  Xiao Guang YANG

  Journal of Systems Science and Complexity. 2005, 18(1): 67-073.

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  In this paper, we consider a network communication delay improvement problem, which is to upgrade nodes in a network with minimum cost such that the communication delay between any two nodes of the network is below a pre-specific level. In the upgrading model, the improvement by upgrading one node is a continuous variable, and the cost incurred by such an upgrading is a linear function of the improvement. We show that achieving an approximation ratio $\beta \ln(|V|)$ for the problem is {\it NP}-hard for some constant $\beta > 0$ even if the underlying network is a bipartite graph. But if the underlying network is restricted as a tree, we show that it can be solved in a strongly polynomial time.
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  DUALITY FOR A CLASS OF NONSMOOTH MULTIOBJECTIVE PROGRAMMING PROBLEMS

  Jian Wen PENG;Xin Min YANG

  Journal of Systems Science and Complexity. 2005, 18(1): 74-085.

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  In this paper, two new dual models of nonsmooth multiobjective programming are constructed and two duality results are derived.
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  PARAMETER ESTIMATION OF EXPONENTIAL DISTRIBUTION

  Hai Yan XU;He Liang FEI

  Journal of Systems Science and Complexity. 2005, 18(1): 86-094.

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  Because of the importance of grouped data, many scholars have been devoted to the study of this kind of data. But, few documents have been concerned with the threshold parameter. In this paper, we assume that the threshold parameter is smaller than the first observing point. Then, on the basis of the two-parameter exponential distribution, the maximum likelihood estimations of both parameters are given, the sufficient and necessary conditions for their existence and uniqueness are argued, and the asymptotic properties of the estimations are also presented, according to which approximate confidence intervals of the parameters are derived. At the same time, the estimation of the parameters is generalized, and some methods are introduced to get explicit expressions of these generalized estimations. Also, a special case where the first failure time of the units is observed is considered.
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  THE RAMSEY NUMBERS $R(T_n,W_6)$ FOR $T_n$ WITHOUT CERTAIN DELETABLE SETS

  Yao Jun CHEN;Yun Qing ZHANG;Ke Min ZHANG

  Journal of Systems Science and Complexity. 2005, 18(1): 95-101.

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  Let $T_n$ denote a tree of order $n$ and $W_m$ a wheel of order $m+1$. In this paper, we determine the Ramsey numbers $R(T_n, W_6)$ for $T_n$ without certain deletable sets.
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  A GREEDY GENETIC ALGORITHM FOR UNCONSTRAINED GLOBAL OPTIMIZATION

  Xin Chao ZHAO

  Journal of Systems Science and Complexity. 2005, 18(1): 102-110.

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  The greedy algorithm is a strong local searching algorithm. The genetic algorithm is generally applied to the global optimization problems. In this paper, we combine the greedy idea and the genetic algorithm to propose the greedy genetic algorithm which incorporates the global exploring ability of the genetic algorithm and the local convergent ability of the greedy algorithm. Experimental results show that greedy genetic algorithm gives much better results than the classical genetic algorithm.
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  A NECESSARY AND SUFFICIENT CONDITION FOR A POINT TO BE A GLOBAL MAXIMIZER OF A CONSTRAINED OPTIMIZATION

  Chu Ren SUN

  Journal of Systems Science and Complexity. 2005, 18(1): 111-118.

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  It is difficult to judge whether a given point is a global maximizer of an unconstrained optimization problem. This paper deals with this problem by considering global information via integral and gives a necessary and sufficient condition judging whether a given point is a global maximizer of an unconstrained optimization problem. An algorithm is offered under such a condition and finally two test problems are verified via the offered algorithm.
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  THREE SOLUTIONS THEOREMS FOR NONLINEAR OPERATOR EQUATIONS AND APPLICATIONS

  Jing Xian SUN;Xi An XU

  Journal of Systems Science and Complexity. 2005, 18(1): 119-125.

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  In this paper, some three solutions theorems about a class of operators which are said to be limit-increasing are obtained. Some applications to the second order differential equations boundary value problems are given.
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  ON ASYMPTOTIC JOINT DISTRIBUTIONS OF EIGENVALUES OF RANDOM MATRICES WHICH ARISE FROM COMPONENTS OF COVARIANCE MODEL

  Wen Quan CUI;Lin Cheng ZHAO;Zhi Dong BAI

  Journal of Systems Science and Complexity. 2005, 18(1): 126-135.

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  In this paper, the authors derive the asymptotic joint distributions of the eigenvalues of some random matrices which arise from components of covariance model.
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  HIGHLY NONCONFORMING FINITE ELEMENT APPROXIMATIONS FOR A FOURTH ORDER VARIATIONAL INEQUALITY WITH CURVATURE OBSTACLE

  Dong Yang SHI;Shao Chun CHEN;Ichiro Hagiwara

  Journal of Systems Science and Complexity. 2005, 18(1): 136-142.

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  The purpose of this paper is to obtain the optimal error estimates of $O(h)$ for the highly nonconforming elements to a fourth order variational inequality with curvature obstacle in a convex domain with simply supported boundary by using the novel function splitting method and the orthogonal properties of the nonconforming finite element spaces. Morley's element approximation is our special case.