基于语言结构和情感极性的虚假评论识别

随着电子商务的发展,识别网络中的虚假评论意义重大。传统的启发式策略或全监督学习算法不能有效地解决该问题。虚假评论与真实评论在语言结构和情感极性上存在差异,提出基于遗传算法对语言结构及情感极性特征进行优化选择,并利用选取的特征结合无监督硬、软聚类算法对虚假评论进行识别。实验结果验证了所提算法的有效性。     

Implementing optimized pairings with elliptic nets

In this paper,we use elliptic nets to implement the optimized Ate pairings and optimal pairings on the Barreto-Naehrig curves with embedding degree 12.In order to do the arithmetic of elliptic curves over finite fields with elliptic nets,we first give some basic properties of elliptic nets associated to elliptic curves over finite fields and the expression of Miller function in terms of elliptic nets.Then we give formulae to compute some optimized pairings with elliptic nets,which is a new method to implement pairings.This method with elliptic nets has time complexity comparable to Miller’s algorithm and it can be optimized.     

A new parallel lattice reduction algorithm for BKZ reduced bases

In order to implement the original BKZ algorithm in parallel,we describe it in terms of parallelism and give its parallel implementation scheme.Then we analyze the efficiency of algorithm’s parallel implementation and show that the speedup factor of BKZ algorithm in parallel is extremely low.Therefore we present a new parallel lattice reduction algorithm suitable for multiprocessor computer architecture.The new algorithm can obtain a BKZ reduced basis and the parallel speedup is effective.Also with the practical results,although the computational complexity increases compared with the original BKZ algorithm,we still indicate that the new algorithm performs well in parallel and the time cost in parallel is less.At the same time,we show that the length of the shortest vector is smaller.     

Optimal resource allocation for transmission diversity in multi-radio access networks： a coevolutionary genetic algorithm approach

The next generation wireless communication systems aim at supporting enhanced diversified network access and data transmission abilities via the cooperative integration and unified management of various radio access technologies(RATs).The resource allocation is the core component leading the network system and mobile terminals to the service robustness and performance maximization.In this paper,a numeric optimization model for optimizing terminals’transmission power and allocated RAT bandwidth for maximizing system capacity is proposed with the focal consideration of the multi-radio transmission diversity for parallel transmission through multiple links from diferent RATs,and diferent terminal characteristics on RAT supports.Also,we design a centralized and periodic scheduling algorithm including an improved coevolutionary genetic algorithm for efciently solving the optimization problem.Simulation results demonstrate that our propose algorithm can distinctly enhance the system performance and improve the computational efciency.     

Variable partial-update NLMS algorithms with data-selective updating

We note that some existing algorithms are based on the normalized least-mean square （NLMS） algorithm and aim to reduce the computational complexity of NLMS all inherited from the solution of the same optimization problem, but with different constraints. A new constraint is analyzed to substitute an extra searching technique in the set-membership partial-update NLMS algorithm （SM-PU-NLMS） which aims to get a variable number of updating coefficients for a further reduction of computational complexity. We get a closed form expression of the new constraint without extra searching technique to generate a novel set-membership variable-partial-update NLMS （SM-VPU-NLMS） algorithm. Note that tile SM-VPU-NLMS algorithm obtains a faster convergence and a smaller mean-squared error （MSE） than the existing SM-PU-NLMS. It is pointed out that the closed form expression can also be applied to the conventional variable-step-size partial-update NLMS （VSS-PU-NLMS） algorithm. The novel variable-step-size variable-partial-update NLMS （VSS-VPU-NLMS） algorithm is also verified to get a further computational complexity reduction. Simulation results verify that our analysis is reasonable and effective.     

无线环境中不均匀广播算法研究

阿查里亚的多盘碟片算法实现了在一段广播时间内,将热门数据分发次数多于较冷门的数据,即不均匀广播,在降低用户等待时间方面提供了很好的表现。然而,移动设备必须不断地调整无线广播频道去检查数据,消耗了大量的能量。在广播的文件上使用索引技术,可以在无显著增加等待时间的前提下,大大降低移动设备的能量消耗。本文在多盘广播算法的基础上,提出一种倾斜索引(SI)的高效不均匀索引。这种算法根据用户的倾斜访问模式建立了一个索引树,在一个广播循环内,多次分发热门索引节点,少分发非热门索引节点。     

金沙江下游梯级水库汛期运行水位协同浮动调度研究

为验证梯级水库汛期运行水位协同浮动调度模型方法的合理性与普适性,在金沙江流域开展实例分析。首先考虑洪水预见期变化,应用动态多目标算法高效求解调度模型;然后评价汛期运行水位协同浮动调度的风险与效益;最后推求乌东德、白鹤滩、溪洛渡、向家坝水库的汛期运行水位协同浮动关系。研究结果表明：相比年汛限水位静态控制调度方案,梯级水库汛期运行水位协同浮动调度方案在不增加防洪风险前提下,各水库汛期运行水位均可适当抬升,汛期多年平均发电量和电站弃水减少量的最高值(改善率)可达1071亿kWh(11.1%)和649亿m³(14.3%),有效提高了洪水资源利用水平,综合效益巨大。     

湖南省农业干旱灾害风险区划研究

基于自然灾害风险理论和旱灾物理成因,考虑干旱的危险性、承灾体的暴露性、环境的脆弱性以及抗旱减灾能力等方面的要素,运用“自下而上”的区划方法,对湖南省农业干旱灾害风险进行了区划。以县级行政区为最小区划单元,选取9个评价指标并利用层次分析法构建农业干旱灾害风险指数,采用基于GN算法的区域区划方法,将湖南省划分为5个干旱灾害风险等级和12个分布区,其中常德市、衡阳市、郴州市等地部分地区风险较高;划分结果与湖南省水稻生产干旱灾害风险区划的结果多数相同,验证了区划结果的合理性。     

具有成本约束的设备投资木桶—贪婪优化算法研究

针对以经验为主的混合流水车间设备购置策略所导致的生产不平衡问题,提出了一种木桶—贪婪算法。该算法在固定设备成本的约束下,以产线生产节拍最快为目标,利用木桶效应的补短板思路识别出瓶颈工序,并在此基础上针对产线内多种类产品瓶颈工序不一致的特性引入贪婪思想。然后,基于实际产线案例对比不同算法的求解结果,木桶—贪婪算法相比穷竭搜索算法以及改进遗传算法在求解质量和效率方面具有一定优势。最后,以实际产线为背景,利用Plant Simulation仿真进行产线改造前后对比,验证了提出的算法在实际生产中的可行性和有效性。     

受强弱关系理论启发的改进人工蜂群算法

针对原人工蜂群算法在寻优过程中存在收敛精度不高、容易陷入局部最优的问题,提出一种改进人工蜂群算法(SWT-ABC)。将社会学中强弱关系模型化并引入多子群矩阵式蜂群结构,定义了强关系个体从三个方向随机引导搜索,加快算法收敛速度和提高收敛精度;为增强算法跳出局部最优的能力,定义了弱关系个体交互以实现子群间信息交流来提升种群多样性;增加侦查蜂反向学习机制并确定合适的蜜源上限,能有效提升目标函数评价次数的利用效率。通过基准测试函数的数值实验并与12种改进算法进行对比,改进后的人工蜂群算法收敛精度更高、全局寻优能力更强,并且在高维优化问题求解中仍具备良好的收敛性能。