Artificial Neural Network for Combining Forecasts

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神经网络在成组技术方面的应用

阐述了成组技术及其在高级制造技术中的作用，在此基础上描述了神经网络在零件编码分类系统中的应用以及用神经网络设计制造单元的方法。     

统计模式识别的研究

模式识别的基本目标就是在有监督和无监督的情况下进行分类,在模式识别的各种模型中,基于统计的方法已经被广泛的研究并应用于实际.一些新的技术和方法的引入（神经网络和支持向量机方法）也促进了该领域发展,文章研究了基于统计的模式识别的进展情况,给出了模式识别的概念、原理、方法并对各种方法进行了相关的评述.     

利率市场化条件下农村信用社的困难与应对

从分析利率市场化条件下农村信用社面临的问题人手，剖析问题存在的原因，提出：为保证我国农村信用社利率市场化的顺利进行，必须认真总结农村信用社利率试点的经验和教训，在信用社产权改制、金融产品定价、建立利率风险管理机制等方面作一些探索。     

On Vector Quasi-Variational Inequality Problems in H-Space

The purpose to this paper is to study the existence problem of solutions to the vector quasi-variational inequality for vector-valued functions in H-space.     

对"晨光"体育活动的审度与思考

在总结河南省“晨光”体育活动成功经验的基础上 ,对提高学校体育的水平与质量进行了理论性论证 ,进而提出了“晨光”体育活动应推广与普及的合理化建议及可行性措施 .     

一种简易新型长光程薄层光谱电化学池

设计并制作了一种新型长光程薄层光谱电化学池，其具有光程长、灵敏度高、重现性好等特点，且组装简便，电极容易更换，溶液未补偿电阻小，溶液用量少．易清洗．电解池以石墨为工作电极，分别用循环伏安、交流阻抗技术、光谱恒电位技术对其性能进行测试，得到比较满意的结果．     

流媒体技术在继续教育平台中的应用

在阐述了流媒体技术的基本原理的基础上，通过对主流技术的分析比较提出了以WindowsMedia为技术支撑，基于组播和点播的流媒体继续教育平台解决方案，并对资源的同步控制和安全策略作简要分析，实现一个功能丰富的继续教育平台．     

仿射Weyl群(E～)6的a值5的左胞腔

Coxeter群的胞腔是1979年Kazhdan和Lusztig中定义的，这些胞腔理论在代数群的表示理论中发挥了重要的作用。对一些特殊的情况，胞腔的分类已经明确地给出了，例如，对于秩为2的群参见，对于An^-参见，对于a值4的典范型和或参见.本文利用时俭益的运算算法给出了仿射Weyl群E6^-的a值等于5的所有左胞腔。     

Using genetically-defined rodent strains for the identification of hippocampal traits relevant for two-way avoidance behavior: a non-invasive approach

Summary Genetically-defined rodent strains permit the identification of hippocampal traits which are of functional relevance for the performance of two-way avoidance behavior. This is exemplified here by analyzing the relationship between infrapyramidal mossy fibers (a tiny projection terminating upon the basal dendrites of hippocampal pyramidal neurons) and two-way avoidance learning in about 800 animals. The necessary steps include 1) identification of structural traits sensitive to selective breeding for extremes in two-way avoidance, 2) testing the robustness of the associations found by studying individual and genetical correlations between hippocampal traits and behavior, 3) establishing causal relationships by Mendelian crossing of strains with extreme structural traits and studying the behavioral consequences of such structural randomization, 4) confirming causal relationships by manipulating the structural variable in inbred (isogenic) strains, thereby eliminating the possibility of genetic linkage, and 5) ruling out the possibility of spurious associations by studying the correlations between the hippocampal trait and other behaviors known to depend on hippocampal functioning.In comparison with the classical lesion approach for identifying relationships between brain and behavior, the present procedure appears to be superior in two aspects: it is non-invasive, and it focuses automatically on those brain traits which are used by natural selection to shape behaviorally-defined animal populations, i.e., it reveals the natural regulators of behavior.