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.     

Improved Genetic Algorithm and Its Application in TSP

Crossover operator and mutation operator are basic operators of genetic algorithm , which play important roles in improving the quality of the solution populations. We propose the improved crossover operator , mutation operator and rotation operator on the basis of good point set with the traveling salesman problem , the experimental result shows these operators are very efficient.     

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.     

棉花对红铃虫抗性及有关性状的遗传分析

1990～1991年选用对红铃虫抗性有显著差异的8个棉花稳定基因型,按第二种双列杂交方案分析棉花对红铃虫的抗性遗传行为,测试48个性状,结果表明:(1)侵入率和子害率的h_B中等,GCV较大;铃壳厚度、衣指和衣分的h_B较高,GCV也较大;铃壳致密度、单铃重和子指h_B较高而GCV较小;铃壳含水量等11个性状h_B中偏低,GCV也较小。(2)子指和绒长的GCA和SCA差异均显著,子仁丹宁含量的SCA差异显著而GCA不显著,子害率、铃壳含水量、子仁淀粉、单铃重、衣指、衣分、纤维比强度、伸长率和麦克隆值均为GCA差异显著而SCA不显著。(3)以83—82、7211、7209、1118和华棉101为亲本可提高后代的抗性。(4)铃壳的4个厚度性状、致密度、含水量、丹宁含量和子仁的类黄酮、总酚共9个理化性状与抗性至关,而遗传特点较好或中等,子害率与主要经济性状间的遗传相关系数多为较高正值。本文还就有关问题进行了讨论。     

大麦多数量性状相关分析

穗长、穗粒重两性对小区产量直接影响较大;每穗实粒数和每穗不实粒两性状数对小区产量直接影响很小,但通过其他性状对小区产量的间接负影响很大;每穗总粒数对小区产量直接负影响很大,株高通过其他性状对小区产量间接正影响很大。     

Study on Genetic Fingerprinting Technique of Microbial Communities

The 99% of all microorganisms in naturecannot be isolated by standard culture methods without conspicuous external characters to classify them morphologically. In addition, classification based on physiological or biochemical features are often fuzzy. Molecular techniques are used for uncultured microorganisms to explore the diversity of microbial communities and novel resources without the need of cultivation. DNA dynamics and cloning of PCR products obtained from environmental DNA is now routinely used to identify microbial populations in microbial ecology. For practical reasons the approach is not suited to study the complex dynamics of microbial communities in environment. Genetic fingerprinting techniques are better tools, which give complement for the traditional microbiological methods. The methods are rapid and relatively easy to perform, and they allow the simultaneous analysis of multiple samples, which makes it possible to compare the genetic diversity of microbial communities from different habitats, or to study the behaviour of individual communities over time.     

陆地棉同核异质系异源胞质的遗传效应

通过核代换培育了具有亚洲棉(G.arboreum)、草棉(C.herbaceum)、异常棉(G.anomalum)、长萼棉(G.longicalyx)、哈克尼西棉(G.harknesii)、海岛棉(G.barbadense)、和陆地棉(C.hirsutum)野生种系蓬蓬棉(G.h.purpurascens)、墨西哥野生棉(C.h.mexicanum)等8个棉属种和种系胞质的中棉所7号同核系,并培育了中棉所7号自交系。在检验同核异质系核的同质性基础上研究了胞质遗传效应,结果所有供研究的胞质对产量、产量性状及除花器官外的形态特征均没有显著影响,胞质的遗传效应主要表现对花器官及抗枯萎病性的影响;哈克尼西棉胞质导致雄性完全不育并显著增加花药数量,笔形冠长度和直径显著变小,亚洲棉和异常棉胞质引起花药数量显著减少,笔形冠形状发生显著变化,亚洲棉胞质对抗枯萎病有较显著效应。     

X射线灭活活体日本沼虾精子的初步研究

为检测X射线对日本沼虾精子的灭活效果,利用X射线对雄性日本沼虾进行不同时间的照射处理,将处理后的雄虾与刚完成生殖脱壳的雌虾交配。待雌虾产卵后,计数雌虾抱卵天数,并在显微镜下观察卵的畸形情况。X射线管照射强度为100 k V,5 m A,源距10 cm,照射时间为0、30、60、90、120 min。结果发现:照射30 min组的抱卵天数及卵的畸形率较0 min组无变化,卵的畸形率为0,卵能正常发育至孵化出膜。随着照射时间的增加,在30~90 min之间,雌虾抱卵天数逐渐减少,且所抱卵的畸形率呈上升趋势。照射120 min组的抱卵天数较90 min组变化不大,卵的畸形率达100%。在本试验照射时间范围(0~120 min)内,灭活日本沼虾精子遗传物质的最佳照射时间为90~120 min。     

土壤水分特征曲线几种标定的对比分析

土壤水分特征曲线的标定是土壤水的能量和数量关系在不同尺度间转换的方法,也是植被生态需水机理研究的重要组成部分。通过对传统的迭代法、一次法和建立的2种混合遗传算法进行比较,标定的结果表明,多项式遗传算法能综合考虑2种方差的影响,并能给出一致性的标定结果,这种经验式混合遗传算法对传统的标定算法进行了改进。