Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.     

模糊综合评判理论在研究性学习系统中的研究及应用

介绍了工程数学中的模糊综合评判理论以及相应树型向量推理算法,并将模糊综合推理机制运用到研究性学习系统中进行研究型应用。该系统中运用模糊综合评判对学习效果进行合理评判,得出综合成绩,以其作为改进研究性学习模式的参考评证,从而使研究性学习过程良性发展。     

遗传算法与文本特征选择方法相结合的研究

对文本特征选择的传统方法进行了深入分析并对各自的优缺点进行了详细的对比;其次,通过利用遗传算法自身的寻优特点,把它与传统特征选择方法相结合,并得出了算法。最后,在对各自算法进行了分析,表明了在性能上有了明显的提高。     

改革实践教学模式、培养学生综合能力──增设给水排水专业质量检测实习的体会

对给排水专业在优化专业教学体系,深化专科教学模式及教学内容改革中,实施的四次大型综合性实践教学,进行了认真总结．经过改变随课跟进的实验教学旧模式,在教学计划中增设了“水质指标综合测试与水质评价”实习内容使分散的教学实验得以“水质监测与评价”为骨架,有机穿插在实践教学中,为专科学校培养复合应用型人才,进行了有益的探索与实践,并获得较好效果．     

基于网络的主题协作学习模式的探索

以微型计算机原理及应用课程网络教学改革为例,详细介绍一种基于网络资源利用的主题协作学习的模式,并提出网络环境下学生学习态度、网络教学环境、教师指导和自我评价表质量等建议。     

Suitability evaluation of urban construction land based on geo-environmental factors of Hangzhou, China

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management. With the support of Geographic Information Systems (GIS), grid analysis, and geo-spatial analysis techniques, four factor groups comprising nine separate subfactors of geo-environmental attributes were selected to be used in the evaluation of the suitability level for construction land in Hangzhou. This was based on K-means clustering and back-propagation (BP) neural network methods due to their advantages in fast computing, unique adaptive capacity, and self-organization. Simultaneously, the evaluation results based on K-means clustering and BP neural network were compared and analyzed, and the accuracy evaluation was set. The results showed that the geo-environmental suitability evaluation results of construction land based on K-means clustering and BP neural network were similar in terms of the distribution and scale of construction land suitability level. At the same time, the results of the two evaluation methods were consistent with the variability in suitability level, engineering geology, and hydrogeology of Hangzhou. The results also showed that the real advantage of the methods proposed in this paper lies in their capacity to streamline the mapping process and to ensure that the results are consistent throughout. The suitability level of the urban construction land based on the geo-environment in Hangzhou was divided into four construction sites: land for building super high-rise and high-rise buildings, land for building multistorey buildings, land for low-rise buildings, and nonbuilding land. The results of the suitability evaluation for each category will provide a scientific basis for decision-making in urban development in Hangzhou.     

Using Semantic Classification Trees for WSD

This paper describes the evaluation of a WSD method withinSENSEVAL. This method is based on Semantic Classification Trees (SCTs)and short context dependencies between nouns and verbs. The trainingprocedure creates a binary tree for each word to be disambiguated. SCTsare easy to implement and yield some promising results. The integrationof linguistic knowledge could lead to substantial improvement.     

用水信用与风险管理系统

系统采用Oracle数据库作为开发平台,VB.net为开发工具研制而成。系统借鉴银行和电力企业信用等级评价的规则,结合水司水费收缴的历史纪录及各客户的实际情况,运用自动采集程序,从原有的营销系统和财务系统自动录入数据,再通过优化的模糊概率、神经网络程序,对用户进行交纳水费信用等级评定,建立客户交纳水费风险预警机制。     

对中央部门机关政府采购开展绩效评价的几点思考

中央部门机关政府采购绩效评价,应该以党和国家关于缋效管理和政府采购的一系列重要文件为指导,针对政府采购工作全过程,以绩效目标为牵引,以绩效指标和评价标准为重点,以完善的评价组织方法为推动力,贴近实际、注重实效,按照事前、事中、事后三个阶段,客观评定中央部门机关政府采购工作投入产出比,以及工作的效益和效率情况,为政府采购工作的开展提供借鉴.