Multi-objective optimal approach for injection molding based on surrogate model and particle swarm optimization algorithm

An integrated optimization strategy based on Kriging model and multi-objective particle swarm optimization(PSO) algorithm was constructed.As a new surrogate model technology,Kriging model has better fitting precision for nonlinear problem.The Kriging model was adopted to replace computer aided engineering(CAE) simulation as fitness function of multi-objective PSO algorithm,and the computation cost can be reduced greatly.By introducing multi-objective handling mechanism of crowding distance and mutation oper...     

基于粒子群算法的投影寻踪分类模型研究

投影寻踪分类模型将高维分析问题的数据投影到最佳投影方向上,将其转化为一维问题进行分析研究,其实质是一种降维处理技术,以达到在低维空间分析高维非线性数据的目的．寻找最佳投影方向是一个优化搜索过程,PSO算法可以有效地应用于投影寻踪分类模型中最佳投影方向的搜索．用最佳投影方向计算样本数据的最佳投影值,根据K-均值聚类算法对投影值进行聚类,获取聚类结果．     

多子种群PSO优化SVM的网络流量预测

针对网络流量的时变性和非平稳性特点,为提高网络流量预测精度,提出一种“多子种群”机制的粒子群算法和支持向量机的网络流量预测模型（Multi-Subpopulation Particle Swarm Opti-mization and Support Vector Machine,MSPSO-SVM）.首先支持向量机（Support Vector Machine,SVM）参数编码成粒子位置串,并根据网络训练集的交叉验证误差最小作为参数优化目标,然后通过粒子间信息交流找到最优SVM参数,并引入“多子种群”机制,解决粒子群优化（Particle SwarmOptimization,PSO）算法的早熟停滞缺陷,最后根据最优参数建立网络流量预测模型,并采用实际网络流量数据进行仿真测试.结果表明,相对于其他预测模型,MSPSO-SVM可以获得更优的SVM参数,网络流量预测精度得以提高,更加适用于复杂多变的网络流量预测.     

基于粒子群优化SVM的高速公路交通事件检测

为了更加准确地检测出高速公路上的偶发性交通事件,采用一种粒子群优化SVM参数的高速公路交通事件检测算法,提升事件检测效果。文中运用高速公路实测数据集（L880）,对支持向量机算法进行分类性能测试,并且采用改进的粒子群优化算法对支持向量机的参数进行优化,进而利用测试集数据对该模型进行验证比较,获得满意的检测效果。     

Optimal linear phase finite impulse response band pass filter design using craziness based particle swarm optimization algorithm

An efficient method is proposed for the design of finite impulse response (FIR) filter with arbitrary pass band edge, stop band edge frequencies and transition width. The proposed FIR band stop filter is designed using craziness based particle swarm optimization (CRPSO) approach. Given the filter specifications to be realized, the CRPSO algorithm generates a set of optimal filter coefficients and tries to meet the ideal frequency response characteristics. In this paper, for the given problem, the realizations of the optimal FIR band pass filters of different orders have been performed. The simulation results have been compared with those obtained by the well accepted evolutionary algorithms, such as Parks and McClellan algorithm (PMA), genetic algorithm (GA) and classical particle swarm optimization (PSO). Several numerical design examples justify that the proposed optimal filter design approach using CRPSO outperforms PMA and PSO, not only in the accuracy of the designed filter but also in the convergence speed and solution quality.     

基于粒子群的城市交通信号两级模糊控制

针对城市交通流的特点,设计一种单交叉口多相位两级模糊控制器,有效地减少控制规则数,实现相序、绿信比、周期随交通状况而自适应变化,并采用粒子群算法对模糊控制器的隶属度函数进行优化。仿真结果表明,该系统能有效地提高交叉口的通行能力,减少车辆平均延误。     

基于差分进化算法的区域OD矩阵反推分析

利用极大熵模型反推OD分布矩阵,引入差分进化算法来求解极大熵模型。采用差分进化算法,与传统方法相比,能够提高求解极大熵模型的速度与精度,从而提高OD矩阵推算的准确度。最后,利用简单实例分析该使用方法的有效性。     

一种基于进化博弈论的云计算虚拟计算资源配置模型

目前针对云计算的资源配置策略研究多关注于云计算资源提供商状况,研究云计算资源提供商的虚拟资源调度管理策略,可以提高云计算资源的可靠性和资源利用率.本文针对云应用提供商,提出基于进化博弈论的自适应资源配置模型,以性能目标为进化博弈目标,通过该模型得到最优的资源分配策略.对比实验结果显示,本模型能有效减少资源的使用.     

基于人工鱼群算法的移动通信网络基站覆盖优化问题

基站覆盖优化问题是移动通信网络优化的核心问题．针对网络节点严重冗余，基站之间相互干扰的情况，提出了一个移动通信网络基站最优覆盖模型，并利用人工鱼群算法对移动通信网络基站覆盖优化问题进行求解，得到了最优设计方案．最后选取某城市核心区域对模型与算法进行了验证，仿真结果表明：本文提出的方法提高了移动通信网络基站的覆盖率，减少了节点冗余，从而达到减少网络建设成本，提高网络规划效率和准确度的网络优化目的．     

Optimization for PID controller of cryogenic ground support equipment based on cooperative random learning particle swarm optimization

Cryogenic ground support equipment (CGSE) is an important part of a famous particle physics experiment — AMS-02. In this paper a design method which optimizes PID parameters of CGSE control system via the particle swarm optimization (PSO) algorithm is presented. Firstly, an improved version of the original PSO, cooperative random learning particle swarm optimization (CRPSO), is put forward to enhance the performance of the conventional PSO. Secondly, the way of finding PID coefficient will be studied by using this algorithm. Finally, the experimental results and practical works demonstrate that the CRPSO-PID controller achieves a good performance.     

Research of order allocation model based on cloud and hybrid genetic algorithm under ecommerce environment

For massive order allocation problem of the third party logistics (TPL) in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm (GA), implementing cloud deployable MapReduce (MR) code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming (MIP) as fitness function to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform (LIP) in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.     

Intelligent optimization of the structure of the large section highway tunnel based on improved immune genetic algorithm

As in the building of deep buried long tunnels, there are complicated conditions such as great deformation, high stress, multi-variables, high non-linearity and so on, the algorithm for structure optimization and its application in tunnel engineering are still in the starting stage. Along with the rapid development of highways across the country, It has become a very urgent task to be tackled to carry out the optimization design of the structure of the section of the tunnel to lessen excavation workload and to reinforce the support. Artificial intelligence demonstrates an extremely strong capability of identifying, expressing and disposing such kind of multiple variables and complicated non- linear relations. In this paper, a comprehensive consideration of the strategy of the selection and updating of the concentration and adaptability of the immune algorithm is made to replace the selection mode in the original genetic algorithm which depends simply on the adaptability value. Such an algorithm has the advantages of both the immune algorithm and the genetic algorithm, thus serving the purpose of not only enhancing the individual adaptability but maintaining the individual diversity as well. By use of the identifying function of the antigen memory, the global search capability of the immune genetic algorithm is raised, thereby avoiding the occurrence of the premature phenomenon. By optimizing the structure of the section of the Huayuan tunnel, the current excavation area and support design are adjusted. A conclusion with applicable value is arrived at. At a higher computational speed and a higher efficiency, the current method is verified to have advantages in the optimization computation of the tunnel project. This also suggests that the application of the immune genetic algorithm has a practical significance to the stability assessment and informationlzation design of the wall rock of the tunnel.     

可计算均衡模型在东北振兴区域经济发展战略中的应用

在分析东北地区经济特征和国内外关于可计算一般均衡模型研究成果的基础上,提出了东北地区利用可计算均衡模型制定经济发展战略的构想和相关的研究问题,为振兴东北区域经济提供决策支持。     

基于成本分析的区域配送中心优化选址模型

区域配送中心选址是否得当对其后期运营成本影响很大,本文将针对配送中心从设计规划到项目寿命期结束所涉及到的诸多成本因素进行分析,从配送中心营运角度对配送线路优化处理,使配送成本最低,这样得出的方案才更符合实际情况;把初期建设成本分摊到项目寿命期内进行比较,使配送中心选址的可比性更强;弥补了以往最短路径法只考虑节约运输费用,未考虑土地使用成本、基础设施建设成本的不足.     

边坡岩体中地下水优化排水机理研究

基于对岩体边坡中地下水的存在性态及作用机理分析 ,提出了实用排水模型 ;建立了排水微分控制方程 ,通过敏感性分析求解此方程而得到岩体中地下水的优化排水方向 .此成果在岩体边坡地下水渗流、库岸边坡岩体中地下水的有效排泄、岩体滑坡有效排水等方面具有重要的实用价值 ,丰富了岩体水力学及山地灾害学的科学内涵     

基于成本分析的区域配送中心优化选址模型

区域配送中心选址是否得当对其后期运营成本影响很大,本文将针对配送中心从设计规划到项目寿命期结束所涉及到的诸多成本因素进行分析,从配送中心营运角度对配送线路优化处理,使配送成本最低,这样得出的方案才更符合实际情况;把初期建设成本分摊到项目寿命期内进行比较,使配送中心选址的可比性更强;弥补了以往最短路径法只考虑节约运输费用,未考虑土地使用成本、基础设施建设成本的不足.     

湖南省水资源承载力分析

采用动力学模型对湖南省未来20年各行各业的需水量进行预测,并从人口和经济承载力两个方面对湖南省水资源承载能力进行分析和评价．分析结果表明,湖南省水资源可承载能力并不理想,水资源承载能力不足以维持经济和社会的稳定发展．针对分析结果提出了提高湖南省水资源可承载能力的措施．     

基于Mapinfo的路径选择系统开发研究

武警部队处突时,如何选择最优路径,在最短的时间内安全到达指定地点一直是值得研究的问题。在分析道路权重的基础上,建立最优路径选择的路段效用函数及算法,基于Mapinfo平台,利用VB编程实现最优路径选择。     

斐波那契数列在静态数据调度算法中的应用

数据调度算法在视频点播系统中扮演举足轻重的作用,本文在经典递归函数（俗称摩天大楼算法）的基础上提出了一种新的视频分段算法,并在100～600 Mbit/s服务器网卡带宽模式下,对新算法、摩天大楼算法和金字塔算法及近年的广义沟槽斐波那契算法进行了仿真.通过分析实验数据中对各个算法的启动时延和磁盘存储需求,对代理服务器中热点视频分段的命中率进行了比较,获得了更好的网络传输效果.