Shortest Path Algorithm for Hypergraphs

Based on strong isomorphism for hypergraphs,vertex isomorphism is defined,which preserves hyper-adjacency property between vertices.Adjacency-matrixes of hypergraphs and weighted hypergraphs are presented respectively.The Floyd's algorithm is generalized to finding shortest paths between all pairs of vertices in a hypergraph.The publication provides an instance which verifies the practicability of the modified algorithm and whose results have been compared with those of the method given by LI Chun-ming.Time complexity of the presented algorithm is obtained to be(O(n~3)).     

A Data Detector Based on Channel Equalizer Designed for the Downlink of CDMA Systems

In code-division multiple-access (CDMA) systems,sub-optimum multi-user or joint detection algorithms have been studied recently, which are mostly designed for the uplink situation. The algorithms are too complex to implement for the downlink situation. The conventional receiver consisting of matched filters is often inefficient in eliminating MAI. The authors propose a data detection algorithm designed for downlink of CDMA systems which introduce channel equalization to eliminate MAI. It consists of a channel equalizer and code matched filter. The equalization algorithm is based on zero forcing (ZF) criterion.The performance of the algorithm is better than metched filter's and its complexity is cower than tunt of sub-optimum multi-user detection.     

Distributed Cutting Stock System Based on Heuristic Search and Knapsack Algorithm

A approximate algorithm is presented by which satisfactory results of two dimensional optimal layout belonged to NP complete problems can be obtained efficiently and rapidly. The algorithm integrated with widespread of computer network has been applied to the distributed cutting stock system Adopting Heuristic search and Knapsack algorithm, the algorithm makes each layout optimal locally and obtained the approximate optimal solution. It is compared with other two approximate algorithms and pointed out their shortcomings. In the end of the article a layout example was presented.     

THE REAL RESISTIVE MODEL FOR FREQUENCY -DOMAIN ANALYSIS

A new model for frequency - domain analysis - the real resistive model which is based on Complex Network Theory is proposed in this paper. The network equations formed with the new model without contain complex numbers because there are only sources and resirtive elements in the model. A CAA algorithm for frequency analysis by using the new model is also given. It is shown that the trouble with the complex operation in the traditional algorithm has been avoided. The algorithm presented in this paper is simple and convenient,hence it is easy to popularize.     

基于株平均值的胚乳性状QTL作图的极大似然方法

根据三倍体胚乳性状的数量遗传模型,发展出一种新的专用于胚乳性状数量基因座位（QTL）区间作图的统计方法。该方法以分离群体中各植株的分子标记基因型以及植株上若干粒种子胚乳性状的平均值为数据模式,采用基于平均值混合分布理论的极大似然方法进行QTL分析。QTL效应估计通过EM算法实现。由于该方法利用标记基因型内QTL基因型的混合分布特性,因此,它比同样基于株平均值的最小平方QTL分析方法以及迭代重新加权最小平方QTL分析方法具有更高的统计功效和精确度。方法的可行性和有效性通过计算机模拟数据分析得到了进一步验证。     

Distribution Network Structure Planning Based on Multi-population Immune Genetic Algorithm

Distribution Network Structure planning is a complex combinatorial optimization problem, which is difficult to solve properly by using traditional optimization methods. The authors put forward Multiple Population Immune Genetic Algorithm (MPIGA)for optimal planning of distribution network structure, and do optimal search to different aspects of optimization goals. During the genetic evolution process, biologic immune mechanism is introduced to do some immune operator operation on chromosomes of each population, which can interact mutually by the shift of excellent units. By this way, it can effectively prevent population retrogression, promote diversity and the whole optimal searching ability of genetic algorithm. In order to minimize network annual expenditure, a mathematic model is established. The optimal solution is obtained by this algorithm, which has been illustrated effectively by specific examples at the same time.     

The Algorithm of Pole-Assignment Self Tuning Robust Control

An control algorithm with goed robustness has been developed,based on the combination of poletassignment self- tuning control algorithm with robust estimation and control al-gorithms,while the input signal and process parameters are varied on a large scale. The design of controller based on presented algorithm is simple,with good robustness for parameter changes and a strong ability for overcoming determined disturbance.The simulating research results proved the ef-fectiveness of the pole- assienment self-tuning robust control algorithm.     

The Multi-objective Fuzzy Optimal Power Flow Model and its Neural Network Algorithm

This paper has presented a multi-objective fuzzy optimal power flow medel.Inthe model , the multiple objectives, such as the minimum generation cost and the minimum powerloss, have been considered simultaneously, A new algorithm based on neural network models is aisopresented,in which the neural networks are employed to express, the membership function of fuzzysets and solve the optimization problems. The validity of model and algorithm is verified with numerical examples.     

Stepwise Decomposition Algorithm Research of the Intersecting Body Volume of Irregular Polyhedrons

We integrate the problems of deduction of intersecting grooves and bases in the constructional engineering into the problem calculating the intersecting body volume of irregular polyhedrons, and put forward the stepwise decomposition algorithm of the intersecting body volume of irregular polyhedrons based on computer graphics. The method takes advantage of the basic algorithms in the computer graphics and improves one of the algorithms which can be used to judge whether the dot is in the plane or not. By analyzing the method, we have developed the calculation formulae. Winth the segmentation function, the stepwise decomposition algorithm can be used to compute the intersecting body volume not only of the convex polyhedrons, but also the concave polyhedrons. By programming, the stepwise decomposition algorithm has been carried out, and its accuracy has been testified by a typical example.     

遗传算法的DV-Hop算法改进

DV-Hop算法中,平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差,对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离;然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离,减少平均每跳距离带来的误差。仿真结果表明,在不增加硬件开销的基础上,改进算法能够有效提高算法的定位精度,并且具有较好的稳定性。     

Multiple Load Flow Solutions in Electric Power Systems Based on Genetic Algorithm

Methods for satisfying the power balance requirement and the voltage magnitude costraint are developed and incorporated into the genetic algorithm method to form a constrained genetic algorithm for solving the load flow problem.The robustness of the load flow algorithm is enhanced by the dynamic population.the technique for accelerating the convergence of the optimisation process and the network node sequencing procedure described in the paper.The efficiency and feasibility of the developed CGALF algorithm have been tested using KK 11 node system under light load and heavy load conditions.     

Automatic image analysis and spot classification for detection of fruit fly infestation in hyperspectral images of mangoes

Fruit fly infestation of mangos is a major concern for growers and exporters, leading to requirements for quarantine treatments such as vapor heat treatment or irradiation and subsequent reduction in quality and consumer acceptance. An on-line method for detection and removal of infested fruit would thus benefit producers and consumers. An algorithm has been developed to identify spots generated in hyperspectral images of mangoes infested with fruit fly larvae. The algorithm incorporates background removal, application of a Gaussian blur, thresholding, and particle count analysis to identify locations of infestations. Each of the four algorithm steps involves adjustable parameters which were iteratively tested to find the optimal combination for detection in terms of false positive and false negative results. For algorithm parameters selected to minimize false negative results, a false negative error rate of 1.0% was achieved with 11.1% false positive error and 6.0% overall error in heavily infested samples. For the same sample set, the lowest overall error rate achieved was 2.0%, with 1.0% false positive and 3.0% false negative. For samples with lower infestation rates, the error rates were much higher, the lowest overall error being 12.3%. This therefore demonstrates the feasibility of hyperspectral imaging for fruit fly detection while highlighting the need for technology with improved resolution and signal to noise ratio to allow detection of single larvae.     

Fingerprint Identification Using Point Pattern Matching

Fingerprint is those lines distributing on the finger surface. It's unique and stable. It has been hundreds years to use fingerprint to identity. AFIS (Auto Fingerprint Identification System) has been widely used. Besides traditional criminal, AFIS has been used to validate user in OS and web access, and embedded AFIS also has been used in ATM, credit card and door-lock. Fingerprint matching is one of the most important problems in AFIS. In general, the minutiae such as ridge endings and ridge bifurcation is to be used to represent a fingerprint and the fingerprint matching through minutiae matching. Based on this observation and by representing the minutiae as a point pattern, an automatic fingerprint verification problem may be reduced to a point pattern matching (minutia matching) problem. Point pattern matching is a famous problem in the field of pattern recognition. For a good point pattern matching approach, it is able to perform the geometrical invariant quantities (translation, rotation, and scaling) efficiently. Various algorithms have been proposed for point pattern matching. For example, the relaxation approach handles translational difference only and the complexity of triangles approach is very high. In this paper, an algorithm for fingerprint identification using point pattern matching based on cluster approach is proposed, which effectively solves the problems of optimal matching between two fingerprint minutiae images under geometrical transformation and minutiae quantity change. Process which bases on the matching of vector pairs is developed to determine the registration parameters. The experimental results show that the proposed matching algorithm is fast and has high accuracy.     

Modeling and Simulation Based on Pole-zero Placement Self-adaptive Temperature Control System

Based on model parameters estimating, a kind of algorithm of pole-zero placement self-adaptive temperature control is put forward according to closed loop apices distribution of resistance furnace temperature control. The mathematic model is presented by discursion for the controlled object, at the same time, the algorithm is illustrated identification method of model parameters, compute formula and simulation result of controlled parameters. Simulations and practices of the model proved that the algorithm is of rapid constringency speed , satisfactory effect on the object with time changing especially for the controlled objects of the high current and low voltage characteristics. The algorithm has been applied in the temperature control of intelligent slag measurement equipment of a iron-steel graduate school.     

Solving the Symmetric Positive Definitesystems of Linear Equations Which Have Positive Semi-definite Tri-diagonal Matrix Increments

This paper deals with a kind of iterations,which need to solve the symmetric positive definite systems of linear equations whose matrices of coefficients have varying positive semi-definite tri-diagonal martrix increments. The positive semi-definite tri-diagonal martrix increment is especially divided, an iterative algorithm is presented. It to use the algorithm in the iterative process of repeatedly solving above mentioned system. Wu Zhuzhu has presented an algorithm for diagonal elements with positive increments. The algorithm of this paper which takes martrix increments into account, is the generalization of the algorithm presented by Wu Zhuzhu.     

A Globally Convergent Algorithm for Nonlinear Programming

A new globally convergent algorithm was presented for a continuous differen-tiable nonlinear programming by defining a measure function deviating from the Kuhn-Tucker point. With this algorithm which can be used to get the optimum solution of the problem,the optimal lagrangian multiplier corresponding the optimal solution of the problem was also obtained. A new iterative algorithm for quadratic programming is obtained when applying the general algorithm to quadratic programming. Finally,a numerical example was given.     

Application of RBF Algorithm Based on Generalized Genetic Optimization in Prediction Model for Molten Iron Desulfuration

Desulfuration process is a very sophisticate reaction which is not only diverse but also non-line. A RBF algorithm based on generalized genetic optimization is proposed after studying the standard genetic and RBF algorithm. The authors also introduce its application in prediction Model for molten Iron Desulfuration. The algorithm perfectly resolve the problem of random selection of RBF cluster center number. Furthermore, it also reduces the time which GA uses. Comparison between the simulation results of RBF and RBF algorithm Based on GGA optimization further proves the efficiency and precision of its application in Prediction Model for Molten Iron Desulfuration. Finally the result of the test shows that after adopting the algorithm, the end-point hitting ratio can reach eighty-five percent. This indicate the algorithm has the engineering practicability.     

求解粮食调运问题的两阶段优化算法

粮食调运优化问题过去已有研究,但是当问题较为复杂时,传统算法就要花费大量时间而且准确性也难以保证.针对这一缺陷,本文对已有的粮食调运模型进行改进,并基于该改进模型提出了一个解决粮食调运优化问题的两阶段求解方法,在第一阶段,由图搜索算法产生所有可行的运输路线,并根据约束条件对搜索树进行剪枝;在第二阶段,采用蚁群算法从第一阶段产生的可行路线集合中选取最佳路线,使总的运输成本最低.经过实例测试,该算法在粮食调运过程中具有较好的效果.     

Reliability evaluation algorithm for complex electrical distribution networks using the storage structure of adjacency multilist

A section algorithm of reliability evaluation for complex medium voltage Electrical Distribution Networks (EDNs) using adjacency multilist (AM) is proposed. The constructing method for AM is introduced. The AM can be used to store the structure data of EDNs and to solve the problem of space & time complexity. A new power flow algorithm of backward / forward sweep is proposed and a fast algorithm of forming sections in distribution network is put forward. The proposed algorithm makes a perfect combination of the power flow algorithm and the section algorithm of reliability evaluation, which makes efforts to decrease the work of programming and saves the computing time. Applying the proposed algorithm in RBTS-BUS6 system and actual EDNs, the reliability assessment results show that the algorithm has an advantage of saving time and possesses efficiency in engineering practicality.     

Recognition and prediction of fracture by using antcolony algorithm analysis in carbonate reservoir

A fracture-developed carbonate oil field in the east has a complicate oil and gas distribution in facture network at late development stage, which leads to multiplicity of favorable reservoir estimation. In view of problems above, ant colony algorithm is adapted to recognition and predict facture in this field. The ant parameters are optimized on the basis of core and image log data, and the spatial distribution feature of fracture is described, as a reticulate structure with three dominant clusters of fracture (NW, NNE & NE). Drilling leakage, production data and image log are then used for reliability analysis of fracture predict, which presents that ant colony algorithm is a practicable methodology to recognition fracture and provides a support for remaining oil distribution analysis. As a booming bionic algorithm, ant colony algorithm has great potential for quantitative fracture predict with seismic materials.