一种基于改进蚁群算法与GIS的多约束配送中心选址方法

针对单一指派约束和容量约束的设施选址问题（Single Source Capacitated Facility Location Problem, SSCFLP）,建立了一种基于改进蚁群算法与GIS的配送中心选址方法。构建了以总成本费用最小为目标的配送中心选址模型;提出了适合求解SSCFLP问题的改进双层蚁群算法,将求解过程划分为彼此关联的设施选择层和需求指派层2层蚁群,采用改进的全局信息素更新策略加强双层蚁群交流,并对迭代最优解的指派关系进行局部优化;将方法应用于汽车配送中心的选址,利用GIS工具构建选址空间。实验结果表明,该选址方法能找到质量较好的选址及指派结果,对于求解同类问题具有较强的借鉴意义。     

二重结构编码算法求解背包问题的分析及改进

给出了背包问题的数学模型,分析了解决该问题的二重结构编码的混合遗传算法,在此基础上通过引入价值密度的概念并与局部搜索算法相结合对算法进行了改进,并通过大量的数值试验充分证明了改进后的二重结构编码算法的有效性有了一定的提高.     

一种改进的Apriori挖掘算法

针对制约Apriori算法效率的瓶颈问题,提出了一种基于Apriori的改进算法,算法只需要遍历一次事务数据库,避免了Aprori算法多次扫描事务数据库和产生大量的候选项集,同时利用项集的有序性改进了判断连接的方式,优化了连接步骤,减少了判断时间.实验结果表明,改进的Apriori算法在运行效率上有一定的提高.     

免疫遗传算法及其在VRP中的应用

物流配送车辆路径问题（VRP）是一类典型的NP问题。在基本遗传算法的基础上,根据生物的免疫系统原理,提出一种改进的算法——免疫遗传算法。在算法中构造一种基于抗体浓度的群体多样性保持策略,引入免疫算子和免疫记忆库。将该算法应用于求解VRP问题,实验结果表明算法可以实现解的多样性,避免出现早熟收敛,可以有效防止进化过程中最优解退化的可能,是求解车辆路径问题的一种有效的算法。     

一种改进型聚类算法应用于科学数据挖掘

聚类是数据挖掘中很重要的一部分.提出一种新的算法,不仅能避免最终的结果陷入局部解而且不用预知类别就可以对大批的数据进行分类,同时可以很容易的找出噪声数据.实验证明了这种算法在科学数据挖掘中是很有效的.     

基于小波去噪和图像分割技术的改进NAS-RIF盲图像复原算法

针对非负和支持域受限递归逆滤波算法(NAS-RIF)的缺点,提出了一种改进方案.首先,应用小波去噪技术,保持了退化图像边缘特征,抑止噪声,提高退化图像的信噪比;其次,在每次迭代中,利用图像分割技术找到准确的目标支持域,并用背景的均值取代非均匀背景;还采用重置共轭梯度法加快了算法的收敛速度.实验结果表明,改进后的算法具有更好的复原效果和更快的收敛速度.     

加权关联规则的改进算法

关联规则挖掘在许多领域已有广泛的应用,目前存在许多发现关联规则的算法,但这些算法都认为项目对规则的重要性相同.然而在现实中各个项目的重要性往往不同,决策者往往优先考虑利润较高的项目,而忽略利润较低的项目.分析现有的加权关联规则存在的问题,提出了一种新的加权关联规则模型.     

An improved CHC algorithm for damage diagnosis of offshore platforms

1 Introduction Health monitoring of structures, especially large spacestructures intended for long-term operation, is essential indeveloping short-term or long-term repair plans. Becausethe maintenance, replacement, and time out of service arecostly, it i…     

An improved Markov chain model based on autocorrelation and entropy techniques and its application to state prediction of water resources

According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.     

An improved algorithm of simulation on air-sea turbulent heat fluxes in China seas

With a global GSSTF2 and NCEP/NCAR reanalysis database and observation data at the Yong Xing station of Xisha Island in the South China Sea, we simulated the turbulent sensible and latent heat flux at sea surface in Chinese and neighboring seas (hereafter termed as China seas) using a common bulk method with some improved parameters. Comparing the simulated results with the observed and reanalyzed data, the improvement yielded higher accuracy, a smaller mean square deviation within 10 W/m2, and a smaller average relative error at about 25%. In addition, spatial resolution was improved to 0.1°×0.1°. The simulation is able to replay the main features of regional and seasonal variation in turbulent heat fluxes, and also the general pattern of heat flux changes during the summer monsoon outbreak in the South China Sea.     

贝叶斯算法在反垃圾邮件应用中的改进方案

在反垃圾邮件的过滤技术中,贝叶斯算法是使用最为广泛的方法之一.在充分分析贝叶斯算法在垃圾邮件过滤技术中原理及方法的基础上,指出了在过滤中文垃圾邮件应用中的不足之处,然后给出了一个可行的改进方案.改进方案将邮件视为句间有序,句子内部关键词无序但句间具有相关性,从而可以得到比传统方法较好的实验结果;而且由于减少了传统方法处理时信息的丢失,这样也可以达到改善实验结果的目的.