THREE CRITICAL POINTS THEOREM AND ITS APPLICATIONS

In this paper, by use of the pseudo-gradient vector field, the three critical points theorem in [2] is extended to the C1 function in the Ba-nach space, and therefore the three critical, points theorem in [5] is strengthened and the existence of the saddle point of the C2 function is discussed.     

Design of Vision System Based on Service Robot

A vision system based on the service robot is involved. In the system, picture signal is acquired by the picture sensor OV7635. Frame memory AL422B is used as data buffer memory, while CPLD controlled the time order DSP performed. In the software system of image processing, to accomplish color image segmentation and recognition, the threshold vector judgment and improved seed-fill algorithm is introduced, and the image geometric moment is calculated during the segmenting. In order to achieve a vision servo system which composed of image-based feedback and adaptive compensation, the deduced matrix-based Jacobian from the image moment is taken as image feature. Adopted the TFT LCD is adopted to straightly disolav the result of vision recognition and vision tracing.     

基于KPCA-WLSSVM的建筑能耗预测模型

为降低建筑能耗影响因素间复杂相关性对模型性能的影响,建立了一种基于KPCA-WLSSVM的建筑能耗预测模型。利用核主元分析(KPCA)对输入变量进行数据压缩,消除变量之间的相关性,简化模型结构;进一步采用加权最小二乘支持向量机(WLSSVM)方法建立建筑能耗预测模型,同时结合一种新型混沌粒子群-模拟退火混合优化(CPSO-SA)算法对模型参数进行优化,以提高模型的预测性能及泛化能力。通过将KPCA-WLSSVM模型方法应用于某办公建筑能耗的预测中,并与WLSSVM、LSSVM及RBFNN模型相比,实验结果表明,KPCA-WLSSVM模型方法能有效提高建筑能耗预测精度。     

OPTIMAL CONDITIONS OF DIFFRENTIAL MULTIOBJECTIVE PROGRAMMING IN BANACH SPACES

In this paper,by the use of Farkas lemma and its inve-rse proposition,the generalized Kuhu-Tuoker conditions for the existanceof strong minimum point in differential multiobjective programming inBanach spaces and the existance of sufficient condition of weak Paretominimum Foint are derived.     

EXISTENCE OF A BASIC OPTIMAL SOLUTION FOR LINEAR VECTOR EXTREME VALUE PROBBEM

In this paper, the concept of basic for linear vector extreme value problem is introduced in the partially ordered vector space. Some properties and results of the linear programming are generalized. And the existaence therom of basic optimal solution is proved.     

基于LS-SVM的小水电站年发电量智能预测模型

针对小水电站年发电量序列的特点,将最小二乘支持向量机(least squares support vector machine,LS-SVM)回归模型引入年发电量预测领域,并给出了相应的过程和算法。与常规基于人工神经网络(artificial neural net-works,ANN)的智能预测方法比较,该模型优点是明显的:①将神经网络迭代学习问题转化为直接求解多元线性方程;②整个训练过程中有且仅有一个全局极值点,确定了预测的稳定性。最后,一个实际的预测例子表明:该模型实现容易、预测准确,适用于小水电站预测。     

数字化电机调速系统中神经元控制器的应用

神经网络具有自学习、自适应能力，用于控制时可不依赖控制对象的数学模型。为此，基于单神经元设计出用于交流电机矢量控制的自适应磁链和转速控制器，并应用于由数字信号处理器(DSP)实现的交流电机矢量控制系统中，实验表明：此方法设计的控制器结构简单，易于数字化实现，控制系统动态性能良好。     

基于最小二乘支持向量机模型预测田面糙率

田面糙率是影响地面灌溉质量的重要参数。基于最小二乘支持向量机建立了两类4个田面糙率预测模型,并进行了验证。结果表明第一类模型预测值(即作物地采用LSSVM-N-I3、裸地采用LSSVM-N-I1,翻耕地采用LSSVM-N-I2)相对误差最大值为9.7%;第二类模型预测值(即LSSVM-N-II模型)相对误差最大值为10.5%,由此可见两类模型都具有较高的预测精度,可以用于田面糙率的预测。