A FINITE ELEMENT ALGORITHM FOR PARALLEL PROCESSING OF MULTI-FRONTS

In this paper,a new algorithm for solving large-scale finite element system is presented, which utilizes the architecture of parallel processing. Firstly, the structure is partitioned into sub-regions. Then multi-fronts are used to assemble and eliminate concurrently in every sub-region. Thus the condensed interface stiffness matrices and load vectors are obtained. By serially assembling and solving global equation to get interface displacements and backing to every sub-region, the inter-nodal displacements and element stresses can be solved. The results of computation show that it can not only increase the speed of computation,but also save the memory space of computer effectively. This algorithm is an effective method for solving large-scale structural finite element systems.     

AN ACCELERATION SEARCH METHOD FOR UNCONSTRAINED OPTIMIZATION AND ITS APPLICATION IN MODEL PARAMETER ESTIMATION

In order to improve the convergence rate of the algorithms, an acceleration search method along a straight or curve is proposed,and the specific calculation steps of the algorithms are presented. The numerical results in model parameter estimation show that the convergence rate is improved and the calculation accords with the practical demands.     

NETWORK FEOW APPROACH TO RELIABILITY EVALUATION IN IARGE SCALE NETWORKS BY MIXING INCREASING ELOW WITH DECREASING FLOW

Based on the maximum flow principle about networks, a network flow approach to reliability evaluation in large scale netwerks ty mixing inereasing flow with decreasing flow is proposed in this paper.This approach gets the initial flow of each branch in a r.etwork associated with a state of the retwork by decreasing flows of some branches correlative to another state of the network.As a result, the number of flow compute required can be reduced enormously.The numerical example shows that the approach is powerful. The comparison of this approach with the minimal cutset one is also given in this paper.     

A Study on Human Simulation Intelligent Control Algorithm to a Category of Objects

Based on the model of Human Simulation Intelligent Controller (HSIC) presented briefly, a detailed algorithm was described for the servo system control by using the method of HSIC. Simulation results obtained proves the good performance of the control algorithm.     

AN INTELLIGENT BACKTRACKING METHOD FOR SOLVING COMBINATORIAL PROBLEMS

This paper proposes an intelligent method for solving a kind of intractable combinatorial problems, investigates and analyzes several important problems of this kind Theoretical and experimental results show that this method is better than the classical backtracking method.     

Distribution Network Structure Planning Based on Improved Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem,which is difficult to solve properly by using traditional optimization methods.In order to solve this problem,Improved Immune Genetic Algorithm is introduced to the distribution network optimal planning. Improved Immune Genetic Algorithm draws into the immune diversity and antibody's density mechanism to maintain the individual's diversity and remains evolution algorithm's global stochastic searching ability,so it can promote diversity and the whole optimal-searching ability of genetic algorithm.The optimal module takes the minimum annual cost as its object,and the capacity and voltage drop of feeder and the radiation of distribution network as its restrictions.According to the require of radiation of distribution network,the spanning tree of the alternative network is taken as the initial solution to speed up the calculation.And the branch-exchange method is used in designing crossover operator and mutation operator to avoid the radiation checking and enhance the optimizing ability.This algorithm has been illustrated effectively by examples,at the same time,the calculation example demonstrates that,the algorithm has higher calculation speed than the traditional immune genetic algorithm.     

OPTIMIZATION OF BIPARTITE JOINS WITH GRAPH THGORY

An optimization approach for multi-relational joins based on the matching concept in graph theory is introduced. The basic idea lies in constructing a join graph from an expression of N-relation query, and seeking for a maximun matching with minimun total weight. The algorithm for bipartition(X, Y) is proposed in this paper.     

A Dynamic Model for Generation Expansion Planning and Algorithm

This paper discusses the problem of long-range generation expansion planning. A dynamic model for long-range expansion planning is set up and an algorithm-a two-step programming is presented, which is used here in a case.