A CUTTING PLANE METHOD FOR LINEAR BILEVEL PROGRAMS

1.IntroductionThebilevelprogr~ngproblem(BLPP),anoptimizationproblemwithaspecialconstraintfunctionwhichisimplicitlydeterminedbyanotheroptimizationproblem,hasreceivedmuchatteDtionofresearchersduringthelastdecade.Falkll]pioneeredtheworkbystudyingthegeneralmad-minproblem,aspecialcaseoflinearBLPP,andproposedamethodbasedonbranch-and-boundandlinearprogrammingtechniques.BialasandKar.an[2]investigatedthegeometricpropertiesofthefeasibleregionofthelinearBLPPandshowedthatsolutionsoftheproblemmayoccu…     

一种基于随机优势的对话式决策方法

讨论应用随机优势原则求解随机决策问题的对话式决策方法．文中首先证明了在一定条件下可用一系列已知函数的正线性组合逼近决策人的效用函数所在的类,在此基础上,给出了在决策人提供新信息时确定新的效用函数类并在此新类中判断两方案随机优势关系的方法,进而提出了使决策人隐知的效用函数的数学期望达到最大的对话式决策程序．     

一种求解连续型结点变量影响图的概率衍值方法

本文分析研究了目前影响图评价的几种算法，指出了常规方法在影响图评价中存在的缺点与不足，并根据在思考问题过程中，同一领城专家的认知方式不同，分别采取因果推理及诊断推理的特点，提出一种能有效获取上述两种知识的数据获取与行值方法。     

ASYMPTOTIC EXPANSION AND ASYMPTOTIC BEHAVIOR OF THE SOLUTION FOR THE TIME-DEPENDENT NEUTRON TRANSPORT PROBLEM IN A SLAB WITH GENERALIZED BOUNDARY CONDITIONS

In this paper,the time-dependent neutron transport integro-differential equationin a nonuniform slab with generalized boundary conditions and initial value is considered forgeneral cases concerned with an arbitrary nonhomogeneous medium possibly with cavity,withthe anisotropic scattering and fission,and with continuous energy varying from null to any finiteconstant or from one positive constant to another positive constant.We prove that the correspon-ding neutron transport operator A has finite Spectrum points in any strip {λ|β_1≤R(?)λ≤β_2}whereβ_2>β1>-λ~*(λ~* is the essential infimum of v∑(x,v)),and obtain the asymptotic expansion ofthe time-dependent solution which exists and is unique.Furthermore,we give the existence ofthe dominant eigenvalue and indicate the asymptotic behavior of the neutron density as t→+∞.     

A GENERAL APPROACH BASED ON AUTOCORRELATION TO DETERMINE INPUT VARIABLES OF NEURAL NETWORKS FOR TIME SERIES FORECASTING

Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumption about the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conduct comparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms inf