基于RAGA的PPC模型在黑土区玉米调亏灌溉评价中的应用

调亏灌溉作为一种行之有效的节水灌溉方式,对黑土区农业水资源的可持续高效利用具有重要意义。而调亏灌溉方案的优劣取决于它的综合效果,难以直观评价。以2013年在黑龙江省红星农场进行的玉米调亏灌溉技术效应的试验研究为基础,选取了8个评价指标,采用投影寻踪分类模型(PPC),利用基于实数编码的加速遗传算法(RAGA)优化其投影方向,根据投影函数值得到各评价指标对综合评价的贡献大小对不同调亏处理的各项指标进行排序。结果表明:苗期水分调亏程度为田间持水量60%的处理为最佳调亏灌溉方案,产量和水分利用效率比适宜调亏灌溉处理分别提高了2.11%和6.42%。研究结果可为黑土区玉米灌溉管理提供科学依据。     

考虑陀螺效应的动力总成悬置系统分析和优化

应用陀螺力学理论，对传统动力总成悬置系统的无阻尼动力学方程进行修正，引入陀螺矩阵，得到新的动力学方程。对新的动力总成悬置系统动力学模型进行计算分析，研究了陀螺矩阵对频域、时域响应的影响。使用遗传算法分别对修改前后的方程进行优化计算，并进行比较分析。结果表明，对于低转速发动机，曲轴转动的陀螺效应不明显，而对于高转速的发动机，陀螺效应不能忽略，应以考虑陀螺力矩的方程为基础进行设计分析。     

Wavelet Application in Algorithms of Data Mining

Wavelets have been widely applied in such research areas as image processing, computer vision, network management and data mining. Wavelets have many favorable properties, which are hierarchical and multiresolution decomposition structure, linear time and space complexity of the transformations. The paper presents wavelet application on the algorithms of data mining, in cluding as clustering, classification, distributed data mining, similarity search, approximate query processing, visualization and so on. Finally, the paper concludes by discussing the impact of wavelets on data mining research and outlining potential future research directions and applications.     

A MIMD PARALLEL ALGORITHM TO SOLVE TRIDIAGONAL TOEPLITZ LINEAR EQUATIONS

The rank one updating formula and the parallel eliminating algorithm for linear recurrence systems ane combined fo form a MTMD parallel algorithm fo solve tridiagonal Toeplitz Cinear equations. This algorithm has a simple strictire and requires onlty a few storages as well as in-terprocessor communications. There is no special demand on the number of processors in the parallel system. The speedup can come dose to p12 comparing with the LU decomposition method (p is the number of processors). It is worth pointing out that it is proposed algcmthn that considels and organizes the parallel arithmetic in the first order linear ricurrence systems with constant coefficients.     

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.     

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.