A novel artificial bee colony algorithm with Powell's method

Artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose a modified search equation which is applied to generate a candidate solution in the onlookers phase to improve the search ability of ABC. Further, we use the Powell's method as a local search tool to enhance the exploitation of the algorithm. The new algorithm is tested on 22 unconstrained benchmark functions and 13 constrained benchmark functions, and are compared with some other ABCs and several state-of-the-art algorithms. The comparisons show that the proposed algorithm offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all test functions.     

漳河水库入库径流序列变化趋势分析

依据漳河水库1963-2008年入库径流资料,采用R/S分析方法和M ann-Kendall参数秩次相关检验法对其未来入库径流变化趋势进行了分析。结果表明:①水库流域未来径流量将呈缓慢下降的趋势,且未来1月和7月的径流量变化趋势的随机性成份可能很大,应采取必要对策和措施,以应对未来可能出现的干旱或暴雨洪涝等自然灾害。②1995年为突变点,前后两个系列的统计特征值均具有明显的差异,已经不符合"一致性"的要求。③对于20世纪70~80年代的持续枯水期,应理解为这只是其径流丰枯周期变化中的一个枯水期。④流域人类活动日趋频繁,使得流域下垫面条件发生了较大的变化,对入库径流量有较大的影响。     

高职计算机专业学生评价体系的探索

在德国职业教育的影响下,高职计算机专业教育开始推行任务驱动,工作过程导向的教育模式,但是其教育评价体系还没有与教学模式相统一,实现与对应就业岗位需求的完美结合。高职计算机专业教育评价体系包含了很多方面,本文主要从学生学习效果的评价体系进行探索。     

浅谈计算机硬盘数据丢失原因及恢复

本文主要对计算机硬盘数据丢失的原因、恢复软件的应用方法进行分析。     

关联规则挖掘在教学评价中的应用研究

教学评价是院校最重要的工作之一,而科学的评教方法又显得尤为重要。本文介绍一种更适合于关系型数据库关联规则挖掘的、基于SQL的频繁项关联规则挖掘算法,并将其应用于教学评价。通过对大量的样本数据进行试验,得出了应用以往传统的教学评价方法所无法得到重要的教学参考信息。     

Using anatomical knowledge expressed as fuzzy constraints to segment the heart in CT images

Segmenting the heart in medical images is a challenging and important task for many applications. In particular, segmenting the heart in CT images is very useful for cardiology and oncological applications such as radiotherapy. Although the majority of methods in the literature are designed for ventricle segmentation, there is a real interest in segmenting the heart as a whole in this modality. In this paper, we address this problem and propose an automatic and robust method, based on anatomical knowledge about the heart, in particular its position with respect to the lungs. This knowledge is represented in a fuzzy formalism and it is used both to define a region of interest and to drive the evolution of a deformable model in order to segment the heart inside this region. The proposed method has been applied on non-contrast CT images and the obtained results have been compared to manual segmentations of the heart, showing the good accuracy and high robustness of our approach.     

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。     

项目教学法在开放教育《VB程序设计》辅导中的应用

开放教育教学辅导中“项目教学法”,就是精心设计辅导项目、传授规范知识、优化教学过程和注重操作技能的培养