基于邻域粗糙集的不完整决策系统特征选择算法

针对不完整决策系统属性约简算法时间复杂度较高问题,基于正域不变条件下,决策系统分类能力保持不变原则,提出不完整决策系统前向顺序特征选择算法.该算法从约简集为空集开始,根据在约简集合中加入各属性后对正域影响程度大小将属性降序排列,采用顺序前向搜索,选择当前最佳特征加入特征约简集合,确定最佳特征子集.将该算法扩展到基于邻域...     

基于服务质量的Web服务优化选择算法及仿真

提出一种基于服务非功能属性的Web服务优化选择的多目标遗传算法.考虑到在服务选择时组合方案中的控制结构、具体服务之间的关联性和多个服务质量指标之间的折衷这三方面的约束,对服务选择建立分层模型给出优化选择的形式化定义.在此基础上,采用多目标遗传算法求解优化服务选择.首先设计了适合的染色体编码方式,以表示可行的服务选择方案...     

基于蚂蚁算法的中国邮路问题

针对中国邮路问题中先寻找奇数度结点,再进行奇数度结点之间路线添加的问题,引入了蚂蚁算法,通过其随机概率选择和最短路线激励策略,有效地解决了结点之间的最短路线的问题,避免了常规方法中必须先进行奇数度结点匹配的问题.算法易于实现,实验仿真表明算法耗时短、效率高.     

数据仓库中实视图的选取

基于AND-OR ViewGraph,应用视图选择的代价模型,提出了利用遗传算法实现实视图选择的方法和策略,实验结果证明这种算法结果更优效率更高.     

一种基于免疫抗体聚类算法的复杂函数寻优

通过在克隆选择过程中引入抗体聚类机制,提出了一种用于复杂多模函数优化的新算法.通过聚类将抗体群分成多个子种群来实现其克隆选择策略,加速克隆扩增,从而提高抗体成熟力及亲和性.采用了混合超变异算子,使其能快速获取全局及局部最优.实验仿真结果表明:该算法对复杂函数寻优的过程是相当有效的,具备良好的全局和局部收敛可靠性.     

产业发展理论回顾及应用研究——以盐城市盐都区产业发展定位为例

产业发展定位合理与否,关系到城市产业发展策略的选择,影响到城市化进程的速度与质量.以盐城市盐都区为例,回顾了城市产业发展中的经典理论与常用理论,如产业结构演变理论、区域分工理论和产业发展阶段理论,以期为产业发展理论的合理应用起到抛砖引玉的示范作用.     

Space use by two arboreal rodent species in a Neotropical cloud forest

Studying animal space use patterns can help increase our understating of ecological processes such as competition and community dynamics. To quantify space and habitat use in an isolated and patchy cloud forest community in Mexico, we evaluate the vertical stratification, home range and habitat selection of two arboreal rodents: Habromys schmidlyi and Reithrodontomys microdon. Using live-traps at ground level and different forest strata, we radio-equipped nine individuals of H. schmidlyi and seven of R. microdon, and evaluated fine-scale space use and broad-scale habitat selection between cloud forest and oak forest. We found an average home range of 0.24 ha for R. microdon males and 0.72 ha for females, with a preference for higher canopy in the cloud forest. For H. schmidlyi the home range was 0.83 ha for males and 0.29 ha for females, with a preference for the understory level in the cloud forest. Home range is three-dimensional for these rodents, so we estimate that on average, individuals of both species used eight trees in the time they were tracked. We characterised the vegetation at the trap sites, and used recursive partitioning to relate the presence of different plants with the probability of finding these two species and Peromyscus aztecus, a third rodent species also present in the area and considered in our analysis of habitat use. The highest probability of finding R. microdon (96%) was related to the presence of Brachythecium occidentale and Renauldia mexicana, while H. schmidlyi (95%) was found in close proximity to Fabronia ciliaris and Everniastrum. We highlight the importance of arboreal trapping in biodiversity assessments, and the role of arboreal rodents in maintaining tropical forest ecosystems. We suggest that these rodent species could avoid or reduce competition by using the vertical strata differentially, and that H. schmidlyi and R. microdon can be biological indicators for cloud forest management and conservation.     

Dynamic Model Averaging and CPI Inflation Forecasts: A Comparison between the Euro Area and the United States

The paper forecasts consumer price inflation in the euro area (EA) and in the USA between 1980:Q1 and 2012:Q4 based on a large set of predictors, with dynamic model averaging (DMA) and dynamic model selection (DMS). DMA/DMS allows not solely for coefficients to change over time, but also for changes in the entire forecasting model over time. DMA/DMS provides on average the best inflation forecasts with regard to alternative approaches (such as the random walk). DMS outperforms DMA. These results are robust for different sample periods and for various forecast horizons. The paper highlights common features between the USA and the EA. First, two groups of predictors forecast inflation: temporary fundamentals that have a frequent impact on inflation but only for short time periods; and persistent fundamentals whose switches are less frequent over time. Second, the importance of some variables (particularly international food commodity prices, house prices and oil prices) as predictors for consumer price index inflation increases when such variables experience large shocks. The paper also shows that significant differences prevail in the forecasting models between the USA and the EA. Such differences can be explained by the structure of these respective economies. Copyright © 2015 John Wiley & Sons, Ltd.     

马尾松种子园优良家系选择研究

对广西南宁地区林科所种子园,藤县大芒界种子园和贵港市覃塘种子园的440个马尾松(P inusm asson ianaL am b.)自由授粉子代进行年度和地点重复的半胞子代测定试验,以本地马尾松等11个对照来分析马尾松自由授粉子代的遗传变异规律,并根据遗传稳定性和材积生长快慢,采用性状表现水平分析法从中选择出优良家系。结果表明,440个参试家系中有20.0%~98.0%的家系树高比对照大8.3%~67.7%,有5.5%~99.0%的家系胸径比对照大11.4%~106.9%、有9.1%~99.0%的家系材积比对照大29.2%~484.6%。评选出适合在广西普遍推广的广普性优良家系64个,局部推广的局部性优良家系48个,需淘汰的家系83个;选择出的优良家系在11年生子代林中,材积生长量比对照大64.71%~94.51%。用子代林数据估算马尾松各性状的家系遗传力,树高遗传力为0.306~0.724,胸径为0.174~0.686,单株材积为0.286~0.677。     

一种改进的嵌入式特征选择算法及应用

针对非线性多分类问题,提出了一个改进的嵌入最小-最大值特征选择算法,并与支持向量机算法结合,提出了针对复杂的组合优化问题的启发式算法.为验证方法的有效性,在钢板缺陷识别工程数据集上进行了实验,表明所提出的方法具有较高的求解速度和预测准确度.