基于粗糙集理论的权重确定方法研究

针对属性权重完全未知且属性值以专家经验给出的多属性决策问题,提出了利用属性重要度计算客观权重的分配方法。根据粗糙集中的相对正域概念,探讨了如何运用属性重要度确定各属性的客观权重。决策者可以通过经验因子的选取来调整客观权重和主观权重所占的比例,通过实例说明该方法更加有效合理。     

采用混合搜索策略的阿奎拉优化算法

针对阿奎拉优化算法(AO)存在的不足,提出一种采用混合搜索策略的阿奎拉优化算法(HAO)。首先,利用动态调整函数平衡算法的全局探索与局部开发;其次,利用混沌自适应权重来增强算法的全局搜索能力、加快算法的收敛速度;最后,设计新的个体变异概率系数,采用改进型差分变异策略,利用适应度值较优个体引领群体中其他个体开展搜索活动,保持了种群的多样性,增强了算法跳出局部最优的能力。通过八个基准测试函数和10个CEC2019测试函数,以及一个工程应用问题的数值实验仿真对所提算法进行实验验证。实验结果表明,所提算法的全局收敛速度和优化精度均得到了明显地改善,跳出局部最优的能力得到了增强。     

An e-commerce performance assessment model: Its development and an initial test on e-commerce applications in the retail sector of China

We developed a performance assessment model for e-commerce; it included indicators, indicator weights, and evaluation methods. The model has seven methods of assessing e-commerce performance and uses four criteria to compare and select the appropriate one for a particular situation. This model was tested in the retail sector of China. According to the data collected from 70 Chinese retailers, 16 indicators of e-commerce performance consisted of four constructs: marketing and sales, customer service, supply chain efficiency, and financial performance. The indicators for those constructs provide a comprehensive measurement of performance. Then weights were assigned for each indicator using a majority aggregation method. Comparison of the results from seven evaluation methods showed that discordance analysis and simple additive weighting were the best evaluation methods for the enterprises we had sampled.     

基于W-Kmeans算法的DNS流量异常检测

为了对DNS查询进行有效检测,及时发现DNS流量异常,提出了适合于检测DNS流量异常的权重Kmeans (WKmeans)算法.对CN顶级域2009年5月19日的原始查询日志抽取有用信息,提取相关的向量特征,对不同的向量特征赋予不同的权重值.利用W-Kmeans算法对查询日志进行聚类检测,并分析了算法各种参数选择的影响.5.19事件的DNS查询检测结果表明,W-Kmeans算法可以有效检测DNS流量异常的发生.     

个性化元搜索结果整合算法的研究

针对当前元搜索引擎存在的问题,提出一种个性化元搜索结果整合算法。首先对成员搜索引擎根据相应条件设定权值,对各成员搜索引擎得到的搜索结果按贡献量加权分块排序,根据用户检索词条与兴趣库和元搜索结果的文本相关度对块内搜索结果进行整合排序。实验结果表明,该算法能够满足不同用户的个性化需求,在保证了搜索结果查全率的同时提高了查准率,很大程度上改善了用户检索效果和效率。     

Multivariate relative importance: Extending relative weight analysis to multivariate criterion spaces.

For years, organizational scholars have sought effective ways to evaluate the importance of predictors included in a regression analysis. Recent techniques, such as general dominance weights and relative weights, have shown great promise for guiding evaluations of predictor importance. Nevertheless, questions remain regarding how one should investigate relative importance in the presence of a multidimensional criterion variable. The purpose of this article is to extend understanding of relative importance statistics to multivariate designs. The authors review the concept of relative importance and discuss a new procedure for calculating estimates of importance in the presence of multiple correlated criteria. Finally, a published correlation matrix is reanalyzed and a Monte Carlo simulation conducted to compare the new procedure with another technique for estimating importance. Unlike canonical solutions, which are often uninterpretable, the proposed multivariate relative weights provide an intuitive index regarding the relationship between predictors and criteria. Implications for organizational researchers are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Neural networks with sign-constrained weights

In this paper we begin by briefly reviewing recent interest in neural nets with sign-constrained weights, and outline recent progress in establishing the properties of these models. We consider the dynamics for these types of models, and show that uniform attracting states can dominate the dynamics if there is a substantial weight-sign bias. We then show that it is possible to define dynamic thresholds for a variety of learning rules which can eliminate uniform attracting states for any value of the weightsign bias.     

仙人掌多糖的提取、分离纯化及GPC法测定其分子量

研究了仙人掌多糖水提法的最佳工艺条件,以及仙人掌多糖的分离纯化.试验结果表明,提取液用Savag法脱蛋白后,采用Sephacryl S-400柱层析纯化,得到仙人掌多糖OP,经过高效凝胶渗透色谱和常压凝胶柱色谱分析表明,OP为均一多糖,高效液相凝胶色谱法测定OP分子量(Mw)为172591Da.     

Inequalities and externalities of power sector: A case of Broadlands hydropower project in Sri Lanka

The objective of the paper is to estimate environmental externalities related to a run of river project in Sri Lanka and to investigate inequity in distribution of impacts among different social groups. Diversion of the river resulted in loss of water sports (for high-income groups both local and remote), loss of historical monuments (for remote high-income groups) and recreation losses (for local poor). Removal of forest cover leads to loss of non-timber products (for local poor) and carbon storage (for remote high- and low-income groups). Loss of home garden productivity was borne by local poor groups. Benefit of the project, generation of 145 GWh annually, was a gain for the grid connected groups. The impacts were valued using various valuation methods. The base case of the cost benefit analysis resulted in NPV of US$ 11,335,730. When distributional weights are applied for different income groups, both the sign and magnitude of net benefits change. In order to be viable, the project needs diversion of at least 9% of generated electricity to the poorest households in the country. Implications for energy policy towards reducing externality and inequality impacts are also discussed.