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1.
为了支持服务系统最大限度地实现顾客期望的服务价值,提出了一种面向价值的组合服务优化方法。该方法是基于面向价值的组合服务分析的结果,利用人工蜂群算法(ABC),通过对组合服务中影响价值实现的服务要素进行替换,得到组合服务的优化方案。实验结果表明文中的面向价值的组合服务优化方法能够以最小的优化代价、最大限度地保障服务系统的价值实现。  相似文献   

2.
支持向量机的训练需要求解一个带约束的二次规划问题,但在数据规模很大情况下,经典训练方法将变得很困难。本文提出一种基于改进的混合蛙跳算法的SVM训练算法。针对混合蛙跳算法搜索速度慢且容易陷入局部极值的缺陷,将模拟退火思想引入到混合蛙跳算法中,提出一种改进的混合蛙跳算法。该算法保持了混合蛙跳算法参数少和容易实现的特点,同时通过模拟退火的降温过程来提高算法的进化速度和精度。实验结果表明,该算法能显著提高收敛速度,并能有效克服局部极值,在SVM训练中具有良好效果。  相似文献   

3.
针对移动机器人路径规划中算法搜索能力不强且易陷入停滞的问题,文中提出了一种基于混合蛙跳算法的移动机器人路径规划方法。首先利用蚁群算法在栅格地图中生成一定数量的路径,然后引入混合蛙跳算法,子群内进行Memetic进化,最坏青蛙根据与子群最优青蛙或全局最优青蛙的路径交点栅格进行路径更新,并对最终生成的最优路径进行优化处理,以消除不必要的拐点,保证机器人路径运行的安全性。二维环境下的仿真实验表明,提出的混合蛙跳算法能在有效避开障碍物的同时快速地规划出一条通往目标点的优化路径,且效果令人满意。  相似文献   

4.
支持向量机是一种基于统计学习理论的新型机器学习算法,在高维特征空间中寻找最优分类超平面,具有很好的分类精度和泛化性能.支持向量机的训练需要求解一个带约束的二次规划问题,针对数据规模很大情况下经典训练方法变得很困难的缺点,提出一种基于改进混合蛙跳算法的支持向量机分类器参数优化方法,既提高了混合蛙跳算法的收敛速度和精度,又能借助混合蛙跳算法的全局随机搜索能力,为支持向量机参数的优化选择提供一条有效途径.本文提取情感语句的韵律特征、音质特征和混沌特征参数,提出一种基于改进蛙跳算法的数据融合方法,并利用基于改进蛙跳算法的支持向量机进行实用语音情感的识别研究.在实验中比较了PCA方法、BP神经网络和数据融合方法用于语音情感识别的识别率,研究结果表明本文所提的各项改进机制能有效提升情感识别率,为实用语音情感的识别提供一种新方法和新思路.  相似文献   

5.
赵力 《电子器件》2012,35(6):699-703
提出了一种基于改进混合蛙跳算法的SVM训练算法。该算法保持了混合蛙跳算法参数少和容易实现的特点,同时通过模拟退火的降温过程来提高算法的进化速度和精度。并用耳语情感语音识别实验来验证提出的基于改进混合蛙跳算法的SVM的有效性。实验结果表明,提出的新的模型的实验结果明显好于传统的SVM方法,证明了该方法的有效性。  相似文献   

6.
提出了一种利用混合蛙跳算法(SFLA)优化最小二乘支持向量机(LSSVM)算法的混合优化算法,并将其应用到多峰Brillouin散射谱的特征提取中。SFLA-LSSVM混合优化算法利用SFLA对LSSVM算法中的惩罚因子C和核函数中的核宽度σ进行寻优,避免了LSSVM算法陷入局部最优导致的Brillouin频移误差较大。通过对相同信噪比、不同线宽以及相同线宽、不同信噪比2种情况下的多峰Brillouin散射谱仿真分析以及实验验证,拟合适应度为0.0067,拟合度为99.99%,Brillouin频移误差为0.18 MHz。实验结果表明SFLA-LSSVM混合优化算法能够精确地对多峰Brillouin散射谱进行拟合,同时该算法具有拟合精度高、均方误差小、运行速度快的特点,为多峰Brillouin散射谱的特征提取提供了一种新方法。  相似文献   

7.
曹向东  毛永毅 《电视技术》2016,40(3):103-106
在OFDM通信系统中,为了解决非线性的目标跟踪问题,提出了基于改进混合蛙跳算法(SFLA)和粒子滤波算法(PF)相结合的方法来研究动态目标跟踪技术.首先利用高斯变异的局部搜索能力强和柯西变异的全局搜索能力强等优点对混合蛙跳算法进行改进,然后用改进后的混合蛙跳算法来优化粒子滤波算法进行动态跟踪,其优点不需要重采样步骤,有效地保持了粒子的多样性和有效性.仿真结果表明,该算法能够有效实现动态目标跟踪,并且跟踪效果优于同等条件下的混合蛙跳算法和粒子滤波算法.  相似文献   

8.
作为电力系统的重要一部分,发电机励磁控制系统能够保证维持端电压稳定以及提高电力系统整体运行的稳定性。针对电力系统越来越复杂,维持电力系统稳定性尤为重要,文章提出用混合蛙跳算法、权重改进蛙跳算法、遗传算法整定PID参数。最后实验结果表明,权重改进蛙跳算法能有效地获得最优的参数组合,使PID控制效果能够满足系统性能要求。  相似文献   

9.
为提高云制造服务组合的流程寻优质量、效率和稳定性,提出一种基于改进人工蜂群算法的云制造服务组合优化方法。首先,建立了云制造服务组合场景下的3种服务协同质量计算方法;然后,构建了一种融合服务协同质量的云制造服务组合优化模型;最后,设计了一种具有多搜索策略岛屿模型的人工蜂群算法,实现最优云制造服务组合流程的求解。实验结果表明,所提算法在组合流程的寻优质量、效率和稳定性方面均优于当前流行的人工蜂群改进算法和其他群智能算法。  相似文献   

10.
在移动Ad Hoc网中,由于节点以及网络拓扑结构的动态性,服务组合性能往往比在静态网络环境中更不稳定.为了提高服务组合的可靠性,大量的研究工作关注最小化服务组合的中断次数以及服务组合的重组,而对于在服务进行组合之前就预先判断服务的可靠性的研究较少.本文旨在利用移动预测技术结果,在服务组合使用之前寻找具有较低失效风险的服务组合方案,提出了失效风险模型以衡量服务组合的可靠性,并且在该模型的基础上设计了3种算法用于求解服务组合.本文还进行了相应的实验来评估所提出算法的特点.  相似文献   

11.
改进混合蛙跳算法求解旅行商问题   总被引:21,自引:0,他引:21  
罗雪晖  杨烨  李霞 《通信学报》2009,30(7):130-135
以旅行商问题(TSP)为例,引入调整序思想设计了局部搜索策略,同时在全局信息交换过程中加入变异操作,提出一种改进混合蛙跳算法求解TSP问题.实验结果表明,与遗传算法和粒子群优化算法相比较,改进混合蛙跳算法在求解TSP问题上具有更好的搜索性能和顽健性.  相似文献   

12.
服务功能链是网络功能虚拟化的重要支撑,为了构建满足功能和性能需求的服务功能链,需要建立服务的性能模型,从而产生基于性能的服务组合优化问题。一种基于性能模型的服务组合优化问题被建模,并针对复杂约束情况下的无效解干扰,提出了改进的模拟退火算法,该算法包含基于层次属性的产生函数和基于偏离度的目标函数。仿真结果表明,该算法提高了21%的服务组合成功率,同时降低了组合成本和时间消耗。仿真结果验证了所提算法的有效性。  相似文献   

13.
顾英杰  贾振红  覃锡忠  杨杰  庞韶宁 《通信技术》2011,44(2):118-119,122
实现了基于混合蛙跳与模糊C-均值结合的图像分割算法。克服了由于FCM算法易受初始聚类中心和隶属度矩阵的影响而使图像分割效果不理想的缺陷。蛙跳算法(SFLA)是一种全新的后启发式群体优化算法,具有高效的计算性能和优良的全局搜索能力。实验表明:该方法与FPSO结合既提高了图像分割的效率又能得到更好的图像分割效果。  相似文献   

14.
Due to the increasing growth of objects and problems such as increased traffic, overload, delay in response, and low search volume in the service discovery process in the complex Social Internet of Things (SIoT) environment, we provide an effective mechanism in the service discovery process by grouping objects based on common criteria that help us improve service search performance. In this article, we present a new method for clustering objects so that we can group objects that have common services and can work together. Hence, we create a set of different associations for the type of service and reciprocal cooperation of objects. With its help, instead of a global network search, we can perform service searches locally more efficiently and ensure the accuracy and correctness of searches and their answers. Then, we have provided a new mechanism for the service discovery process. In addition, we categorized communities based on their size to compare our proposed algorithm with other approaches using factors such as modularity in SIoT. Finally, we achieved sufficient efficiency in service discovery (86.81% and 88.28%) and demonstrated better performance of the proposed approach in identifying communities.  相似文献   

15.
随着工业互联网、车联网、元宇宙等新型互联网应用的兴起,网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中,存在服务功能链映射效率低与部署资源开销大等问题,联合考虑节点激活成本、实例化开销,以最小化平均部署网络成本为优化目标建立了整数线性规划模型,提出基于改进灰狼优化算法的服务功能链映射(improved grey wolf optimization based service function chain mapping,IMGWO-SFCM)算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径(K shortest path,KSP)问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略,较好地平衡了其全局搜索及局部搜索能力,实现服务功能链映射方案的快速确定。仿真结果显示,该算法在保证更高的服务功能链请求接受率下,相较于对比算法降低了11.86%的平均部署网络成本。  相似文献   

16.
Aiming at previous research primarily focused on constructing service paths with a single objective,for exam-ple,latency minimization,cost minimization or load balance,which ignored the overall performance of constructed ser-vice paths,a multi-objective service path constructing algorithm based on discrete particle swarm optimization (MOPSO) was proposed.To promote the convergence rate and improve constructing performance,the criterions for selecting can-didate physical nodes and paths were explored,and a particle position initialization and update strategy (PIFC) was de-signed.Simulation experiments show that the proposed algorithms can improve the overall quality of service paths and increase the success rate and long-term average revenue.  相似文献   

17.
One of the most critical issues in using service‐oriented technologies is the combination of services, which has become an important challenge in the present. There are some significant challenges in the service composition, most notable is the quality of service (QoS), which is more challenging due to changing circumstances in dynamic service environments. Also, trust value in the case of selection of more reliable services is another challenge in the service composition. Due to NP‐hard complexity of service composition, many metaheuristic algorithms have been used so far. Therefore, in this paper, the honeybee mating optimization algorithm as one of the powerful metaheuristic algorithms is used for achieving the desired goals. To improve the QoS, inspirations from the mating stages of the honeybee, the interactions between honeybees and queen bee mating and the selection of the new queen from the relevant optimization algorithm have been used. To address the trust challenge, a trust‐based clustering algorithm has also been used. The simulation results using C# language have shown that the proposed method in small scale problem acts better than particle swarm optimization algorithm, genetic algorithm, and discrete gbest‐guided artificial bee colony algorithm. With the clustering and reduction of the search space, the response time is improved; also, more trusted services are selected. The results of the simulation on a large‐scale problem have indicated that the proposed method is exhibited worse performance than the average results of previous works in computation time.  相似文献   

18.
To address the problem of load imbalance among edge servers and quality of service degradation caused by dynamic changes of user locations in mobile edge computing networks,a mobility aware edge service migration algorithm was proposed.Firstly,the optimization problem was formulated as a mix integer nonlinear programming problem,with the goal of minimizing the perceived delay of user service request.Then,the delay optimization problem was decoupled into the edge service migration and edge node selection sub-problems based on the Lyapunov optimization approach.Thereafter,the fast edge decision algorithm was proposed to optimize the resource allocation and edge service migration under a given radio access strategy.Finally,the asynchronous optimal response algorithm was proposed to iterate out the optimal radio access strategy.Simulation results validate the proposed algorithm can reduce the perceived delay under the service migration cost constraint while comparing with other existing algorithms.  相似文献   

19.
In view of the problem of trust relationship in traditional trust-based service recommendation algorithm,and the inaccuracy of service recommendation list obtained by sorting the predicted QoS,a trust expansion and listwise learning-to-rank based service recommendation method (TELSR) was proposed.The probabilistic user similarity computation method was proposed after analyzing the importance of service sorting information,in order to further improve the accuracy of similarity computation.The trust expansion model was presented to solve the sparseness of trust relationship,and then the trusted neighbor set construction algorithm was proposed by combining with the user similarity.Based on the trusted neighbor set,the listwise learning-to-rank algorithm was proposed to train an optimal ranking model.Simulation experiments show that TELSR not only has high recommendation accuracy,but also can resist attacks from malicious users.  相似文献   

20.
To improve user experience of composite Web services, a user-aware quality of service (QoS) based Web services composition model is proposed. Under such model, a Web services selection method based on quantum genetic algorithm is proposed. This algorithm uses quantum bit encoding, dynamic step-length quantum gate angle adjustment, neighborhood service search and dynamic punishment strategy to expand search scope and speed up convergence. Simulation experiment shows that this algorithm is more efficient than other existing algorithms in Web services selection.  相似文献   

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