酸碱中和反应中pH值的单神经元自适应控制研究

基于酸碱中和反应过程中pH值变化的动态模型,设计单神经元自适应控制器,解决化工生产过程中pH值的PID控制所存在的调节时间长、超调量大和系统抗干扰性差的问题。在相同条件下与PID控制器进行对比实验,实验结果表明单神经元自适应控制器明显改善pH值过程控制系统的动态性能,该控制系统具有较强的自适应性与鲁棒性。     

机器人足球比赛系统中的机器人任务分配方法

针对基于遗传算法的多机器人任务分配方法中,由于初始种群是随机产生不能很好地表征整个解空间,而容易陷入局部最优解的问题,提出一种新的多机器人任务分配方法。该方法根据机器人效用函数值来确定个体基因,从而产生初始种群,并引进分层遗传算法来实现具有不同最优基因的群体分开演化。仿真实验表明,该方法比传统的遗传算法有更高的寻优效率和更快的收敛速度。     

基于Eclipse实现油藏数值模拟自动控制的方法

在应用研究Eclipse软件的基础上,提出利用Eclipse软件提供的关键字实现油藏数值模拟生产作业的自动控制的两种新方法。实例研究表明,利用关键字ACTIONX实现自动控制的方法更为简便实用。     

河道生态基流生态经济价值及其时间变化研究

为了解决普遍采用单方水资源价值计算河道生态基流价值的缺陷,以及探索河道生态基流价值定量化计算新方法,采用水力学方法将河道生态基流从径流量中分离出来,并确定河道生态基流对应水面面积,进而采用当量因子法计算河道生态基流价值和并探索分析了河道生态基流价值的时间变化特征。以渭河干流宝鸡段为例进行研究,结果表明:渭河干流宝鸡段的丰水年、平水年以及枯水年的年平均河道生态基流量分别为5.82 m~3/s、3.59 m~3/s和2.76 m~3/s。近21 a来,该段河道生态基流价值在时间上总体呈下降趋势,该价值多年平均值为5.61亿元,单方河道生态基流价值为6.27元/m~3,单方价值与价值总量变化趋势相反。河道生态基流价值年内变化具有明显的周期性,总体呈倒"V"字型,汛期河道生态基流价值比非汛期大,单方河道生态基流价值与之相反。通过相同区域以及相近区域的河道生态基流价值研究成果以及价值变化特征的对比分析,证明研究成果较为合理。该方法可为河道生态基流合理保障提供定量化依据。     

Arnold置乱在零水印中的二次复用

为了提高水印的鲁棒性和减小对应版权信息的大小,本文提出了一种基于Arnold变换、DWT和SVD的零水印算法。该算法将载体图像进行DWT变换,对低频子带进行分块SVD;比较置乱后的最大奇异值的大小,若大于则对应位为1,否则为0;将结果与预处理过的水印做异或运算,得密钥矩阵。该矩阵为检测水印提供密钥。实验证明,本算法对图像压缩、滤波、模糊、噪声及脏图具有良好的鲁棒性。     

Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch

Economic dispatch is carried out at the energy control center to find out the optimal output of thermal generating units such that power balance criterion is met, unit operating limits are satisfied and the fuel cost is minimized. With growing environmental awareness and strict government regulations throughout the world, it has become essential to optimize not only the total fuel cost but also the harmful emissions, both, under static as well as dynamic conditions. The static environment economic dispatch finds the optimal output of generating units for a fixed load demand at a given time, while the dynamic environmental economic dispatch schedules the output of online generators with changing power demands over a certain time period (normally one day) so as to minimize these two conflicting objectives, simultaneously. In this paper, the price penalty factor approach is employed for simultaneous minimization of cost and emission. The generator ramp rate constraints, non-convex and discontinuous nature of cost function and the large number of generators in practical power plants, make this problem very difficult to solve. Here, a fuzzy ranking approach is employed to identify the solution which offers the best compromise between cost and emission objectives.     

A balanced solution of a fuzzy soft set based decision making problem in medical science

The purpose of this paper is two folded. Firstly, the concept of mean potentiality approach (MPA) has been developed and an algorithm based on this new approach has been proposed to get a balanced solution of a fuzzy soft set based decision making problem. Secondly, a parameter reduction procedure based on relational algebra with the help of the balanced algorithm of mean potentiality approach has been used to reduce the choice parameter set in the parlance of fuzzy soft set theory and it is justified to the problems of diagnosis of a disease from the myriad of symptoms from medical science. Moreover the feasibility of this proposed method is demonstrated by comparing with Analytical Hierarchy Process (AHP), Naive Bayes classification method and Feng's method.     

Equations of state for hard-sphere fluids

Equations of state and contact values of hard-sphere radial distribution functions (rdf's) which are given by a linear combination of the Percus— Yevick and scaled-particle virial expressions are considered. In the one-component case the mixing coefficient() is, in general, a function of the volume fraction. In mixtures the coefficient( _i ,d _i ), in general, depends upon the volume fraction _i , and diameterd _i , of each species,i andj. For the contact valuesY _ij of the rdf's, the mixing coefficients _ij ( _k ) also depend on speciesi andj. Density expansions for the exact for the one-component hard-sphere fluid are obtained and compared with several approximations made in earlier works and in our own work, as well as with simulations. For a mixture, it turns out that one cannot obtain the exact fourth virial coefficient by using a linear combination of the Percus-Yevick and scaled-particle virial expressions forY _ij unless one allows _ij to depend on mole fractionsx _i even at the zeroth order of its density expansion. We also find that _ij must depend on particle speciesi andj in order to satisfy the exact limits obtained earlier by Sung and Stell. A new equation of state for the binary hard-sphere mixture which satisfies all the exact limits we have considered is suggested.Paper presented at the Tenth Symposium on Thermophysical Properties, June 20–23, 1988, Gaithersburg, Maryland, U.S.A.     

SVD域的图像高斯噪声强度估计

精确估计图像或视频中的噪声强度对于后续的信号处理是至关重要的先决条件。通过对含噪图像的奇异值特性的研究,提出一种精确的SVD域的图像噪声强度估计算法。该算法对噪声强度估计提出了创新的解决方法:1)利用奇异值的尾部数据进行噪声强度估计,这样达到尽可能地降低图像信息对噪声估计的干扰;2)对含噪图像加入已知强度的高斯白噪声,以计算噪声估计时需要设置的与图像内容相关的参数,因此该算法可以自适应图像的结构,能够广泛地适应各种类型的图片。实验结果表明SVD域噪声强度估计算法适用于各种图片类型,而且在极大的噪声强度范围内都能够稳定精确地估计噪声强度。