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.     

Arch Axis Optimization of New Type Arch Bridge with Diagonal Web Cables Based on Geometric Nonlinear Mechanical Analysis

There are obvious geometric nonlinear mechanical characteristics in new type arch bridge with diagonal web cables. Meanwhile, the convergence of the existing arch axis iterative optimization method is not good. In order to solve new type arch bridge axis iteration convergence problem considering geometric nonlinear mechanical analysis, an arch axis iteration optimization method was proposed based on the iteration basis finite element model with two hinge arch model in main arch ring. A 600m span arch bridge with diagonal web cables was selected as an example to test the convergence performance and applicability of proposed method. The results showed that the bending moment of proposed method had better distribution along arch span, and it is about 35% smaller in maximum bending moment, 17% smaller in minimum bending moment and 23% smaller in bending strain energy compared to the results of linear iteration optimization method. Convergence analysis results demonstrated that proposed method had better iteration performance than the existing method. Meanwhile, different initial arch axis can converge to stable results.     

A Method to Improve the Decoding Iteration Convergence Performance of Turbo Codes

Turbo codes is an effective method for digital communication systems to get near channel capacity error correcting performance, its iteration convergence performance is the key factor for practicability. Based on the universal decoding method of Turbo codes, a step increment factor was introduced in the paper to improve the iteration convergence performance. The method to generate the step increment factor was also presented as well as its' computer simulations. Simulation results show the method proposed can improve the convergence performance efficiency for Turbo codes with short interleaver.     

Descending Dimension Algorithm of Nolinear Programming Problem with Linear Inequality Constraints

The general nonlinear programming with linear constraints was investigated. In the algorithm, the method of contributing set was used. Comparing with the general contributing set method, the descending dimension method was used to solve the sub-problem with equality constraints in iterative procedure and the problem with inequality constraints. The algorithm is effective by the numerical test. Finally, it was proved that the iteration points are descending, when the objective functions are convex.     

ALGORITHM AND CONVERGENCE OF TWO-STAGE ITERATIVE PROCEDURE FOR SOLVING SYSTEMS OF LINEAR EQUATIONS

This papr discusses algorithm and convergence of twostage iteratve procedure for solving systems of symmetric positive definite linear equation Ax=b. On the basis of nature splitting of A, this algorithm makes two-step linear iterative procedure (named outer iteration) and makes convergent inner iteraton of any kind.They generate a sequence of approximations {x_h} w.hich converges to the solution Ax=b quickly. This paper also proves is convergene and gives the estimation of error.     

Channel estimation for MB OFDM UWB system based on tap detecting

A novel channel estimation algorithm is proposed for MB OFDM Ultra Wide Band systems based on tap detecting by exploiting the sparse property of channel impulse response. The channel parameters are estimated using the DFT algorithm based on cyclic convolution property of the receive signals. The nonzero taps are detected by exploiting the matching pursuit(MP) algorithm. The new estimated channel parameters are obtained by forcing the zero taps to zeros. Simulation results demonstrate that it has better MSE (mean square error) performance for the four channels proposed by IEEE. Especially for CM1 and CM2 channels, the performance of the algorithm has been greatly improved.     

Job-Shop scheduling based on improved immune cloning algorithm

Parallel immune clone algorithm is proposed based on population coevolution theory and parallel computing affinity of individual at multiple compute nodes. Introducing the immune memory mechanism, the evolution processes of antibody population and memory units are conducted simultaneously, meanwhile, it improves mutual cooperation among antibodies, and ensures solution set approaching optimal solution from the inside of feasible region or infeasible region border. Clone proliferation, high frequency variation and operation of crossover operators increase the chance that better individuals gain affinity maturation by the operation of clone expansion, improve diversity of antibody population distribution, achieve the balance of optimization between depth and range, and ensure the convergence of the algorithm and the diversity of the search range. A computational study for a standard data set is carried out to test the validity of the algorithm, and the effect of algorithm parameters on the results is analyzed. The simulation results show that the global search capability, local search capability, algorithm stability and computing speed of the algorithm are all superior to conventional optimization algorithms such as normal immune clone optimization algorithm, genetic algorithm, etc.     

关于近交系数计算方法的改进

本文对经典方法予以较大的改进.特别是对于有规世代随机出现的系谱中的近交系数,本文给出分段迭代算法,继而大大地提高了近交系数的计算速度.此外,对于多始祖大系谱,我们给出分解算法,使得查找通径和计算工作极易进行.     

Quadrature Methods and Their Extrapolations for Solving Boundary Integral Equations of Steady Navier-Stokes Problems

This paper presents an iteration method of solving non linear boundary integral equations (BIE) of the plane Navier Stokes problem,which each step of the iteration is to solve a linear BIE of nonhomogeneous Stokes problem. Using the quadrature methods of [1],we give a new algorithm with a high order accuracy.The algorithm not only saves work,but also the accuracy can be improved by Richardson extrapolation.     

An edge detection method based on a good point set genetic algorithm

In order to improve the convergence rate of genetic algorithms based on edge detection, a novel edge detection method based on a good point set genetic algorithm (GGA) was proposed. The proposed method designed the crossover operation with the theory of good point set in which the progeny inherits the common genes of the parents which represent its family so as to improve the convergence rate of the genetic algorithm. Furthermore, before the algorithm was used for edge detection, the feature space of the image grey level was transformed into the feature space of the fuzzy entropy. Dissimilarity enhancement processing next was applied to the image by using a fuzzy entropy theory to filter the non edge pixels so as to reduce the scale of the solution domain. This approach offered another efficient way to improve the convergence rate. Experimental results show the proposed algorithm performs very well in terms of convergence rate. The detected edge image is well localized, thin, and robustly resistant to noise.     

Improved Genetic Algorithm of Float Encoding and Its Application

As an optimal method, Genetic Algorithm has obvious advantages, which is based on the nature selection and genetic transmission mechanisms such as high collateral,stochastic,self-reliance. but when in practical application, it usually has problems of premature convergence and result swing near optimum value.To solve the problem of premature convergence, the method called Monte-Carlo is adopted to prevent the algorithm from local optimal, and to the problem of result swing, the method changing the hunting zone dynamically is proposed to improve the accuracy of the optimal result. Further more, it devises programs to optimize the test functions of two famous optimal methods. The test results indicate that the improved Genetic Algorithm is valid, which can not only avoid local optimal but also improve the accuracy of the optimal result.     

Nonlinear Aerostatic Stability of Suspension Bridge with Spatial Main Cables

The three component coefficients of section model of You Cha Bridge were obtained by using two five component balances.And the three dimensional aerostatic stability of You Cha Bridge was analyzed based on the modified increment and inner outer iteration method implemented in ANSYS.It is indicated that the aerostatic stability of You Cha Bridge with spatial main cables is more excellent compared with those of suspension bridges which have two parallel main cables.A full aero elastic model with geometrical scale of 1:90.35 was designed and used to experimentally determine the wind velocity inducing aerostatic divergence in smooth wind.And it is found that the critical wind velocity for attendant bridge is higher than the design wind velocity.     

A Subchannel Allocation Policy of Multicarrier CDMA

To attain high rate data and high quality of service in wireless communication, a subchannel allocation policy combined with subcarriers and power allocation is proposed. In the proposed system, instead of identical power over the subcarriers in parallel, each user's DS waveform is transmitted over the subchannels that have large fading amplitude among all the subchannels. The powers of the subcarriers with small fading amplitude are allocated to the subcarriers with large ones. It can effectively suppress multiple-access interference while obtaining diversity gains. The allocation policy based on fading amplitudes has the advantages of low computation and good convergence compared with the policy proposed in other papers. Thus, it is suitable for engineering.     

Nonlinear Forecast System for River Water Pollution Based on GIS

Based on the analysis of the water pollution spatial distribution characters of Yangtze River in Chongqing,a new method based on the integration of BP neural network and genetic arithmetic(GA) is proposed.For some shortcomings existed in the standard BP neural network,this method has ultimately overcome these shortcomings by combining the GA with BP artificial neural network through altering stimulating function,adding momentum factor to power value for BP algorithm and introducing genetic arithmetic to searching for the knots of the hidden layer,momentum factor and learning level.Using this method can easily overcome the difficulty of measuring the water prediction model's parameters.GIS is used as a tool for data management and spatial analysis,and the prediction result of the model for the water pollution spatial distribution characters of Yangtze River in Chongqing is visualized and explored with the precision of more than 78%.     

Adaptive Iterative Learning Control of Nonlinear Systems with Unknown Control Direction

An adaptive iterative learning control scheme is proposed for a class of mismatched nonlinear systems with periodic uncertainties and unknown control directions. The control algorithm has the following three features;the control method does not need control direction information; the periodic uncertainties are learned online by a learning control method; and the algorithm can deal with mismatched uncertainties. The proposed method can achieve asymptotical convergence along a learning repetition horizon. A simulation example is provided can demonstrate the effectiveness and feasibility of the control strategy.     

A Fast One-Step Scanning Thinning Algorithm

A new quick thinning algorithm was presented in this paper,which assigneddifferent weights to different pixels near the skeleton pixels and rules out the im possible pixels in thethinning procedure. It needs neither iteration on pixel panel nor detection on every pixel such thatthe time consumed is greatly lessened. A filling algorithm is also offered for better results.Experiment on variety of binary patterns showed that it could get both a high speed and a goodskeleton shape compared with other algorithms,This new algorithm reaches perfect result.     

Application of a Particle Swarm Optimization Algorithm in Truss Structure Optimal Design

The particle swarm optimization (PSO) algorithm developed in recent years is a stochastic optimization algorithm based on swarm intelligence. It possesses advantages such as being a simple concept, ease of implementation and low resource occupation. The PSO algorithm was adopted to solve the problem of size optimization of truss structures with stress and displacement constraints. We present the basic principle of the original PSO algorithm in detail, and then introduce a constriction coefficient to modify it. Moreover, reasonable values of the coefficients are proposed for the modified PSO algorithm. Several classical problems are solved using the modified PSO algorithm, and the results compared with those using traditional optimization algorithms and genetic algorithms. Numerical results show that the modified PSO algorithm has good convergence and stability, and can be applied to the size optimization of truss structures.     

A Shared Resource Mutually Exclusive Operation in Parallel Processing System--The Application Model of Lock Control Thechnology

It is one of the pivotal technology that mutually exclusive operation is in the system structural design of the parallel processing to solve resource conflict.Traditionally,the sharer resource mutually exclusive operation is managed by single-computer operation system time-sharing mode for multitask condition,but all of parallel nodes possess renovate right in multi-mode OS,so high-grade lock mechanism is a pivotal technology to solve share resource confilict in parallel process to prevent share resource accessing conflict.This article describes lock control arithmetic of mutually exclusive operation from system structure and puts forward mutually exclusive operation model based on NODS.     

Hybrid Genetic Algorithms for Multimodal Optimization

Hybrid genetic algorithms, which are based on steepest descent algorithm and genetic algorithm, are investigated for the purpose of multimodal optimization. The performances of the hybrid genetic algorithms are evaluated with criteria such as convergence probability, average convergence time and average convergence value of the function in the case of solving global optimization for Schaffer function. It is shown that the performances of the hybrid genetic algorithms are better than steepest decent algorithm or genetic algorithm, and the hybrid genetic algorithm, in which the individuals used for local optimization by steepest decent method are chosen by chance in each generation population, is more efficient than that in which the individuals used for local optimization by steepest descent method are selected from excellent individuals.     

Parallel Computing in NC Machining Program

This paper presents a method which is based on MPI and uses idle distributed computation resource to speed up NC machining program. The experimental results of cutter-location data parallel computation algorithm based on projection method and adaptive projection method show that it scores satisfying speedup.