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.     

A New Adaptive Sequential Diagnosis Algorithm in the PMC Model

We present an adaptive algorithm for sequential diagnosis in the PMC model,which can directly identify a faulty processor without first identifying a fault-free processor.     

Real-time Performance of Linux System

The standard Linux is a typical time-sharing system, it has a poor real-time performance. But according to the applications of the Linux OS are expanding on real-time domain, it becomes necessary to enhance the performance of the Linux system. This paper analyses the schedule policies and schedule algorithms of the Linux kernel, and discusses several different kinds of methods about enhancing real-time performance of the Linux system from the total Linux system. They authors summarizes the current research's developments of the Linux system.     

Automatic Fingerprint Classification by GA-Based Neural Network

Fingerprint classification can provide an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce fingerprint matching time for large database. In the paper, by combining genetic algorithm and neural network is presented a fingerprint classification algorithm which is able to achieve an accurate classification. By inputting the global feature represented by directional image to three layer neural network trained by genetic algorithm, the fingerprints were classified into six categories: whorl, right loop, left loop, arch, double loop and undiscerning type successfully.     

Avoiding Obstacle Planning for Robots on Molecular Optimization Algorithm

Interest in DNA computing has increased overwhelmingly since Adleman successfully demonstrated its capability to solve Hamiltonian Path Problem. This article introduces the improving method in virtue of the biological thery of DNA technology, a new molecular algorithm is advanced. After a numerical simulation, the result shows that it avoids the prematurely and lower convergent speed of the classic genetic algorithm, and inherits global search capability, the validity and the speed of the genetic algorithm have been increased. The best result can be obtained in few iterative times. It is fit for solving path planning problem.     

超级稻“三定”栽培法研究 Ⅱ.不同施肥量对超级杂交稻产量及生长生理特性的影响

2004—2005年在长沙（28°13′N）采用低肥（N 135kg/hm2、P 29.7kg/hm2、K 112.1kg/hm2）、中肥（N 180kg/hm2、P 39.6kg/hm2、K 149.4kg/hm2）、高肥（N 225kg/hm2、P 49.5kg/hm2、K 186.8kg/hm2）3种施肥水平，对超级杂交稻两优293和准两优527的产量及生长生理特性进行了比较研究。结果表明：在试验范围内不同施肥量处理间超级稻产量及有效穗、每穗粒数、结实率等产量构成差异不显著，2年平均产量以中肥处理最高，其中准两优527为9.03t/hm2，两优293为7.28t/hm2；不同年际间超级稻产量及有效穗、每穗粒数、结实率等产量构成差异显著；超级杂交稻准两优527和两优293的适宜氮肥用量为150~180kg/hm2。与准两优527比较，两优293茎秆粗壮，根系发达、根系活力强、分蘖力强、但分蘖成穗率不高，而准两优527前中期生长平稳，分蘖成穗率高，抽穗后光合产物积累多和运转率高，有利于高产形成，但不抗倒伏，生产上应适量减少氮肥施用量。     

水稻与高梁属间远缘杂交花粉管行为观察

水稻和高粱是禾本科的两个异属作物,因其遗传距离较远,杂交表现不亲和,结实率极低,难以获得种子.为初步了解水稻与高粱属间远缘杂交花粉管行为,探索该远缘杂交的发生过程,本实验以籼稻珍汕97A×珍汕97B和Ⅱ-32A×Ⅱ-32B两个组合为对照,对珍汕97A×晋江多枝高粱和Ⅱ-32A×晋江多枝高粱两个属间远缘杂交组合的花粉管行为作初步的观察与研究,结果表明晋江多枝高粱花粉粒能象水稻花粉粒一样在水稻柱头上正常萌发,花粉管在花柱及子房中生长与伸长,有些能最终到达子房的基部;同时高梁花粉管生长也出现诸如不能进入花柱、胼胝质不规则堆积、花粉管末端钝化等一系列的异常表现,致使不少花粉管停滞生长.