基于粒子群优化灰色模型的电力系统负荷预测

在分析灰色GM(1,1)模型局限性的基础上,应用粒子群优化算法的非线性全局寻优能力来求解灰色模型参数值,提出了基于粒子群优化算法的灰色模型,并给出了负荷预测的实例.预测结果表明基于粒子群优化算法的灰色模型具有较高的预测精度和较广泛的应用范围.     

应用动态泛回归神经网络的在线负荷预测

电力系统负荷变化受多方面因素的影响,因此负荷曲线呈现出强烈的非线性.为实现非线性的电力负荷在线预测,应用递推更新的样本数据集训练泛回归神经网络,构成动态泛回归神经网络.该动态神经网络训练方便快捷,能够满足在线预测的实时性的要求.仿真表明预测值较观测值有一定滞后,但均能尾随观测值而变化,达到了预期的目的.     

Application of ACO algorithm in protein structure prediction

The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.     

Effective prediction of DEA model by neural network

In this paper,a fast neural network model for the forecasting of effective points by DEA model is proposed,which is based on the SPDS training algorithm.The SPDS training algorithm overcomes the drawbacks of slow convergent speed and partially minimum result for BP algorithm.Its training speed is much faster and its forecasting precision is much better than those of BP algorithm.By numeric examples,it is showed that adopting the neural network model in the forecasting of effective points by DEA model is valid.     

基于最小一乘能量预测的冰球式蓄冷系统

提出将近似最小l1模递推算法应用于冰球式蓄冷系统的能量预测,所提算法对干扰和量测噪声不敏感,具有较强鲁棒性;同时引入遗忘因子,通过对新旧测量数据予以不同权重,用时变系统来近似实际系统.在系统实现上,利用组态王实现数据采集、友好人机界面设计,利用MATLAB完成复杂的预测算法,充分发挥组态软件在工业控制上组态方便、开发周期短和MATLAB强大数值计算功能的优势,两者之间通过DDE技术实现数据实时通信.实际运行表明,所提预测算法成功应用于冰蓄冷系统能量预测.     

On-line least squares support vector machine algorithm in gas prediction

Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions. The Support Vector Machine (SVM) is a new machine learning algorithm that has excellent properties. The least squares support vector machine (LS-SVM) algorithm is an improved algorithm of SVM. But the common LS-SVM algorithm, used directly in safety predictions, has some problems. We have first studied gas prediction problems and the basic theory of LS-SVM. Given these problems, we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm, based on LS-SVM. Finally, given our observed data, we used the on-line algorithm to predict gas emissions and used other related algorithm to com- pare its performance. The simulation results have verified the validity of the new algorithm.     

基于Matlab的某化工区区域环境空气质量模型系统的建立

大气环境影响评价是环境影响评价的一项重要内容,而其中最主要的部分就是计算各种大气扩散模式下的地面污染浓度,然后据此结果做出评价．为方便工作人员进行区域环境空气质量的预测,使用Matlab软件编制了一套区域环境空气质量模型系统软件．     

井下节流气井的生产动态预测

以单井开采系统为研究对象,采用温度、压力解耦建模与数值耦合方式,以井口油压为控制条件,通过油嘴控制流量和下游温度,建立井下节流气井的井筒-气藏流动耦合的生产动态预测模型,利用试井解释结果或生产动态历史拟合,预测气井的生产流量、压力变化,同时描述生产过程中的井筒非线性温度剖面、压力剖面,从而全面掌握节流气井的生产动态,并可进一步扩展应用于多相流动和复杂井眼轨迹情况.     

抓住创新机遇应对金融危机

我们对今明两年做了预测,今年保8没有问题,而且会超过8,明年是8．5左右。8．5的预测是基于未来的出口会比现在好,私人部门尤其是房地产的投资会加快,而政府的投资增速会明显下降,如果我们在这个基础上再给一些财政刺激,增速会更快。我们一定要保增长,但在保增长与调结构之间需要寻求一个平衡点。     

基于信息熵和贝叶斯方法的就业指导辅助决策技术

为了提高对大学生就业指导辅助决策的准确性和客观性,研究了基于数据挖掘技术进行就业指导辅助决策的技术及其实现的关键方法,根据学生基本信息和就业的历史记录,基于信息论的不确定性描述方法,分析了不同就业岗位上学生各类基本素质的重要程度,再根据属性重要程度提取影响就业的主要属性,在此基础上使用朴素贝叶斯算法进行就业预测分析,实践表明,按照文中提出的方法进行专业化就业指导,方法可行,结果符合实际情况．