基于改进蚁群算法的果蔬运输车辆路径优化的研究

针对果蔬易腐的特点,提出了果蔬保质期时间窗,将其作为约束条件,对果蔬运输车的路径进行优化,建立了针对果蔬配送路径的优化模型,并采用改进蚁群算法对模型进行求解.仿真试验结果表明,模型及算法可以有效地优化果蔬配送路线.     

生鲜农产品冷链物流车辆配送路径优化研究

针对生鲜农产品易变质、易腐蚀的特性,探索冷链物流配送路径的优化方法。首先通过对固定成本、运输成本、货损成本、惩罚成本和能耗成本的研究,建立了以总成本最小为目标函数的农产品冷链物流车辆配送路径优化模型,然后采用改进的蚁群算法对模型进行设计,最后通过实例分析,运用MATLAB软件编写算法程序,求解结果验证了设计的模型的合理性和可行性。     

基于改进蚁群算法的低碳冷链物流配送模型优化与应用

实现持续低碳化发展是冷链物流技术创新与优化的重要方向。基于成本约束视角,将冷链物流存储、配运、交付诸环节的运营成本和碳排放成本纳入企业总成本目标函数,构建冷链物流配送路径优化模型,使用蚁群算法与遗传算法变异算子结合求解,提高了算法迭代收敛速度。以医药冷链物流配送为例进行算法仿真优化与分析,验证了降低物流成本与节能减排可协同优化,获得良好的经济效益。模型和算法对环境可持续视角下的冷链物流配送路径问题有理论和实践意义。     

求解粮食调运问题的两阶段优化算法

粮食调运优化问题过去已有研究,但是当问题较为复杂时,传统算法就要花费大量时间而且准确性也难以保证.针对这一缺陷,本文对已有的粮食调运模型进行改进,并基于该改进模型提出了一个解决粮食调运优化问题的两阶段求解方法,在第一阶段,由图搜索算法产生所有可行的运输路线,并根据约束条件对搜索树进行剪枝;在第二阶段,采用蚁群算法从第一阶段产生的可行路线集合中选取最佳路线,使总的运输成本最低.经过实例测试,该算法在粮食调运过程中具有较好的效果.     

基于灰色系统理论水产养殖投入产出优化模型研究

建立了基于灰色系统理论的投入产出优化模型,并将其运用于水产养殖的投入产出分析。在获得投入、产出系数后,利用GM（1,1）模型预测最终水产养殖的需求量（上下限）、资源保证程度（最高量和最低量）;然后通过定性分析与定量研究,对未来各阶段投入产出系数进行修正和设计灰色投入产出优化模型;最后进行模型计算,取得多种可供选择的优化方案并进行综合论证评价后确定最满意方案。该模型做到了方法互补,求解比较容易而且便于灰靶决策。     

基于行人动力学模型的人桥竖向动力相互作用

基于行人动力学模型，研究了人桥竖向动力相互作用。行人动力学模型采用以行人步频和体重表示的刚度质量阻尼（SMD）模型，人行桥假定为Euler-Bernoulli梁模型，建立人桥竖向动力相互作用控制方程。采用状态空间法进行非比例阻尼系统瞬时模态的求解，得到系统的时变频率和阻尼比；利用变步长四阶五级Runge-Kutta-Felhberg算法求解时变控制方程，对比分析考虑人桥竖向动力相互作用和只在人行荷载作用下人行桥的动力响应。结果表明：考虑人桥动力相互作用，人行桥自振频率略有降低，阻尼有显著增大；当行人以人行桥的频率行走时，考虑人桥竖向动力相互作用结构的动力响应比不考虑人桥相互作用显著降低。     

SEEIP核心企业局域智慧能源网络框架及优化配置方法

智慧节能工业园区（SEEIP）的核心企业能源配置对产业集群的循环经济节能降耗具有重要作用。针对SEEIP建设与既有工业园区核心企业能源系统的智慧化改造，提出一种基于信息和通信技术（ICT）的局域智慧能源网络框架，并给出了能源生产模块、能源转换模块与能源蓄存模块中各种能源介质及品位的能量计算数学模型。以经济成本与环境影响为目标的函数，给出了SEEIP企业能源网络系统配置的优化模型，并采用改进的差异演化算法（DE）结合数据库查询技术求解该混合整数非线性规划（MINLP）优化问题，给出企业能源系统最佳配置方案，以满足用户冷、热、电需求。     

H5亚型高致病性禽流感病毒的全球传播与进化

旨在研究H5 亚型高致病性禽流感病毒的暴发、传播及进化规律，探索不同宿主、宿主行为、地理环境等因素对疾病传播与进化的影响，以期为该疾病未来预防与控制提供建议和理论支持。研究中利用空间分析技术、系统进化分析技术，研究了全球H5 亚型高致病性禽流感疫情（2004—2015 年）的时空爆发、传播和进化规律。结果表明：H5 亚型高致病性禽流感病毒在2004—2008 年出现集中暴发及大面积扩散后，于2011—2015 年出现第二次大面积暴发，同时伴随多种禽流感亚型。此外，对不同地区病毒的遗传差异进行分析，发现地理隔离会造成病毒在区域内鲜有进化或暴发；而病毒在一个地区持续性存在并感染不同宿主，导致病毒的进化及遗传的多样性。研究认为，地理隔离、宿主行为等因素是造成有些地区如南亚、北美洲，病毒遗传差异较小，而有些地区如东北亚、中国等病毒的遗传差异显著的原因之一。     

大豆KCS基因的克隆及结构预测

以大豆叶片总RNA为模板,利用RT-PCR方法,克隆获得大豆KCS基因序列。采用生物信息学方法对其进行预测分析,结果表明:大豆KCS基因的CDS序列长度为1533bp,编码510个氨基酸;大豆KCS基因编码的蛋白质理论分子量为57.1kD,等电点为9.03;该基因编码的蛋白具有两个完全跨膜结构;没有信号肽;其蛋白质二级结构中α螺旋占47.65%,无规则卷曲占35.88%,β折叠占16.47%;在进化关系上,与油茶、菟葵、苜蓿的亲缘关系相对较近,该研究结果可为大豆KCS基因结构和功能的进一步研究提供理论参考。     

风电齿轮箱传动误差分析及振动噪声预估

针对一级行星两级平行轴风电齿轮传动系统，综合考虑齿轮时变啮合刚度、啮合阻尼、传递误差等因素，建立31个自由度的弯扭轴耦合集中参数动力学模型，采用变步长Runge-Kutta法对系统动力学微分方程进行求解，得出齿轮传动系统各级传动误差；借助软件建立风电齿轮箱刚柔耦合动力学模型，并导入传动误差，采用模态叠加法求得齿轮箱轴承支反力，并将其作为声振耦合模型的边界条件，采用声学有限元法对风电齿轮箱进行振动噪声预估，并与试验结果对比分析，两者吻合良好。     

改进的粒子群算法及在数值函数优化中应用

为提高粒子群算法的优化能力，提出了一种改进的粒子群优化算法。在该算法中，采用Beta分布初始化种群，采用逆不完全伽马函数更新惯性权重，在速度更新式中，引入了基于差分进化的新算子，对于粒子的越界处理，采用了基于边界对称映射的新方法。以50个不同类型的数值函数作为优化实例，基于威尔柯克斯符号秩检验的测试结果表明，该算法明显优于普通粒子群优化算法、差分进化算法、人工蜂群优化算法和量子行为粒子群算法。     

Application of improved genetic algorithm to locating and sizing of distributed generation

A Prüfer-coded genetic algorithm based on the decimal number of nodes is proposed and it is used to solve collaborative optimization planning of access solution of distributed generation(DG)and structure of distribution network.Using graph theory to generate theoretically feasible topology structureand the access nodes and the installed capacity of distributed generation are coded by the Prüfer number.The coding method makes the distribution network operation structure and the access solution of DG combine into the evolution problem of the same chromosomal gene.The length of the chromosome coding of this method is shorter than binary encoding.This solution takes full advantage of the Prüfer-coded to improve computational efficiency and convergence rateand makes some restrictions and improvements in some key parts of the algorithm to solve the problem illegal solution.Finallyfeasibility and superiority of the algorithm is validated by a case study.     

Restoration algorithm with wavelength reservation collision avoidance in ASON

Aiming at the problem of link fault restoration in ASON, an improved equalizing routing algorithm (ERA) is introduced to proportion the load at the routing phase. In order to solve the easy blocking problem for the network without wavelength converter because of the wavelength continuity constraint, the algorithm WRCA is proposed at the wavelength assignment phase. This algorithm is realized by adding collision detection object (CDO) in the path message of the resource reservation protocol with traffic engineering extension (RSVP TE). Depending on the value of the CD flag, different wavelength selection strategies are applied at the destination node, and the blocks resulting from wavelength reservation collision are reduced. The simulation experiments compare four wavelength assignment algorithms with the same routing algorithm ERA. The results show that compared with the traditional first fit algorithm (FF) and random fit algorithm (RD), the FF and RD employing CD scheme can effectively reduce the blocking ratio of the whole network, and enhance the practical applicability of the restoration algorithms.     

Learning the BN Structure Based on the Sum of Mutual Information

The Crossing Entropy is defined to scale the similar level of two probability distribution. In many papers on learning BN structure,the Crossing Entropy was used as an indicator of measuring the learning accuracy of an algorithm.The known scoring metrics for learning BN structure is analyzed in this paper,then a new scoring metrics Sum of Mutual Information is proposed based on the information theory.At last,two algorithm for learning BN structure by SIM is represented.     

Improved WPAN meshed adaptive tree routing algorithm

To expand network coverage and enhance the reliability of wireless personal area network (WPAN), the problem of address overflow resulting from applying the meshed adaptive tree algorithm in large scale mesh network wis studied. By dividing the entire network into smaller sub networks, the subarea meshed adaptive tree wis constructed. An improved meshed adaptive tree routing algorithm wis proposed employing the hierarchical topology structure of the subarea meshed adaptive tree. Experimental results show that the algorithm expands the network coverage without increasing the routing overhead and the network load. It also effectively reduces the end to end delay and increases the packet delivery ratio and communication efficiency. It maintains a good performance in the networks with different scales and provides a theoretical basis for enhancing the coverage and reliability of WPAN.     

On-demand routing algorithm based on load balancing and mobility prediction in wireless mobile Ad hoc network

The traditional routing protocol for wireless mobile ad hoc networks is unable to achieve balanced energy consumption and could not adapt to the dynamic topology changes well.A novel on-demand rooting algorithm is proposed based on load balancing and mobility prediction.The proposed rooting algorithm excludes the unstable links in routing discovery,and allows the node with more energy forward the routing request packet preferentially.In addition,it adopts the active local routing recovery strategy by predicting the link connection time,and finishes the repair work before the link being actually failure.The simulation experiments demonstrate that,comparing with the traditional AODV protocol,with slight increase of the rooting control overhead,the proposed algorithm increases the average packet delivery ratio,decreases the average end-to-end delay of the data packets,and achieves load balancing in the network and prolong the life-span of the network,which shows the proposed algorithm is highly practical.     

Markov Logic Networks with its application in De duplication

In order to solve the limitation that the traditional De duplications are mostly used for a specific field and only address one aspect of a problem,a scheme based on Markov Logic Networks (MLNs)is proposed, which is a new Statistical Relational Learning (SRL) model. With its advantage of computing the probability distribution of worlds to serve for the inference, the De duplication is formalized. Discriminative learning algorithm is adopted for Markov Logic Networks weights, MC SAT algorithm is adopted for inference. It shows how to capture the essential features of different aspects in De duplication with a small number of predicate rules and also combines these rules together to compose all kinds of model. The experiment results prove that the method based on Markov Logic Networks not only covers the original Fellegi Sunter model, but also achieves a better result than the traditional methods based on Clustering Algorithms and Similarity Measures in De duplication. It reveals that the Markov Logic Networks can play an important part in practical application.     

智能视频分析的车辆异常行为检测方法

为验证公司自主研发的呋喃它酮代谢物化学发光微粒子检测试剂盒的检测效果,用化学发光微粒子免疫法和高效液相色谱串联质谱法对猪肉、鸡肉、鱼肉、虾4个样品中呋喃它酮代谢物残留量进行检测,比对两种方法试验结果间的差异。结果表明,使用直接竞争CLIA试剂盒检测动物性食品中呋喃它酮代谢物残留量,其特异性强,灵敏度较高,在猪肉、鸡肉、鱼肉、虾样品中0.2、0.4、0.8μg/kg 3个水平的加标回收率均在94.0%~101.0%之间,变异系数均小于15%,最低检测限分别为86.24、84.09、84.51、88.12 ng/kg;此方法与高效液相色谱串联质谱法检测实际样品的阴、阳性判断结果一致,其结果稳定、可靠,可满足现场快速检测动物组织中呋喃它酮代谢物残留的要求。