Support vector machine forecasting method improved by chaotic particle swarm optimization and its application

By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects. Foundation item: Project(70572090) supported by the National Natural Science Foundation of China     

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.     

利用网格技术构建身份证网络查询系统

由于利用假身份进行犯罪的活动越来越多,急需一个遍及各行各业各个地方的身份证查询验证系统来抑制这种现象,而现行的系统还不能满足需要。提出了利用网格技术建立身份证网络查询验证系统的设想,并论证了该系统的可行性及其优点、说明了系统结构及相关技术.     

张家口地区电子文献传递系统(EDDS)的开发研究

随着人们对信息资源的需求及文献传递工作的重视,文献传递的服务模式及发展趋势逐渐成为社会所关注的问题.本课题通过分布式文献传递的服务模式,利用完备的网络搜索系统模型,构建张家口地区高校图书馆之间的电子文献传递桥梁.     

基于语义网络的产品建模及配置方案搜索

对基于语义网络的产品建模及配置方案的搜索方法进行集成研究,以提高产品配置设计的效率.在相关本体的基础上,建立基于语义网络的产品模型结构,并据此解析用户所输入的查询语句.基于语义网络的产品模型提供一种定量与定性相结合的一致化的设计实例与需求的表达方式.进一步通过产品的语义网络模型可以获取设计需求的隐含条件,使得需求在设计方案的搜索匹配过程中被更充分地考虑.利用基于语义网络的推理技术与本体语言RDFS构造待求配置设计问题的语义网络片断,并通过语义搜索与匹配度计算排序从设计实例库中获取符合当前需求配置设计方案;同时,通过注塑机螺杆为实例的应用,证明了基于语义网络的产品模型在支持配置选型设计方案搜索方面的有效性与实用性.相对于传统的产品模型而言,基于语义网络的产品模型更关注属性之间的内部联系,经实例验证基于语义网络的产品模型使得配置设计过程更符合用户的实际需求.     

UML用例图在软件工程中的步骤设计研究

用例图作为uml的一种建模图形广泛应用在面向对象软件系统开发过程中,首先,界定了用例图在软件开发周期模型中的应用,接着,以“中国证券交易系统”中“上市公司股票发行”子用例图设计为例,详细描述了功能用例子图的绘制过程,然后,对整个软件系统的用例图的绘制过程进行了描述,给出了待开发系统的整体用例图.     

基于相似性搜索的水利普查数据融合

针对第一次全国水利普查数据融合存在的问题,提出自适应编辑距离相似性度量,通过调整编辑操作权重及启发式学习权重等措施,对传统的编辑距离进行改进,提高相似性搜索的准确性,并给出基于编辑距离的水利普查数据融合的方法和流程,算法的有效性在第一次全国水利普查数据处理中得到验证。     

融合螺旋策略的分片混沌群粒振荡搜索算法

针对标准鲸鱼算法(WOA)及部分衍生算法求解某些算例效果不佳的问题进行了研究与实验,证明了WOA"包围"过程存在零点搜索偏好陷阱;而混沌优化算法(COA)不均衡的搜索特性使得部分衍生WOA融合的混沌初始种群与群智能优化过程难以调和.为了改善上述缺陷,选用了两种混沌系统和气泡网捕猎策略,设计了一套融合式优化算法.算法采用基于适应度的基线式自适应振荡群粒划分策略指导群体行为模式,充分发挥混沌系统作用,平衡探索与收敛性能.对通用/改进算例和工程应用案例求解可知,该算法性能相较于对比组算法更优,且不存在搜索偏好.     

Two-level searching tracking algorithm based on fast Fourier transform

In order to solve the problems of appearance change, scale and rotation change in the visual tracking, a two-level searching tracking algorithm based on Fast Fourier Transform(FFT)is proposed. It achieves two-level searching by establishing the object's kernel ridge regression model in the Cartesian coordinates and log-polar coordinates, respectively, and the efficiency can be improved by transforming the operation into the frequency domain based on FFT. First, the kernel ridge regression model is constructed in the Cartesian coordinate and the object's center position is obtained by the exhaustive search method based on the circular structure matrix. Then, it transforms the object area to the log-polar coordinates and searches the shift using the kernel ridge regression model in the log-polar coordinates. Finally, the object's state is calculated according to the searching results and the object's model is updated. Experimental results indicate that the proposed algorithm not only can obtain a distinct improvement in coping with the appearance change, scale and rotation change, but also have a high tracking efficiency.     

基于信号相位搜索的WSN节点定位算法

节点定位是无线传感器网络（wireless sensor network,WSN）研究的热点问题之一,基于信号相位信息与物理距离间的关系提出了基于信号相位搜索的WSN节点定位算法。该算法首先根据节点间信号相位信息,基于余弦相似性算法原理构建目标函数,将WSN节点定位问题转换为目标函数最优解搜索问题;然后基于质心定位算法原理确定搜索初始像素单元;最后利用梯度下降法替代逐像素单元的遍历搜索,在不影响定位精度情况下进一步提高定位效率,减小定位功耗。仿真实验结果表明,该算法的各项指标良好,适用于WSN的节点定位。