Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhar博士和kennedy博士发明。源于对鸟群捕食的行为研究 ，PSO同遗传算法类似，是一种基于叠代的优化工具。
-Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), and has Eberhar Dr. Dr. kennedy invention. Stems from the behavior of predatory birds, PSO with genetic algorithm is similar to an iterative optimization-based tools. Platform: |
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Author:叶开 |
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Description: A distributed PSOSVM hybrid system with feature selection and parameter optimization
-Abstract
This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the classification accuracy with a small and appropriate feature subset. This optimization mechanism combined the discrete PSO with the
continuous-valued PSO to simultaneously optimize the input feature subset selection and the SVM kernel parameter setting. The hybrid PSO–SVM
data mining system was implemented via a distributed architecture using the web service technology to reduce the computational time. In a
heterogeneous computing environment, the PSO optimization was performed on the application server and the SVM model was trained on the
client (agent) computer. The experimental results showed the proposed approach can correctly select the discriminating input features and also
achieve high classification accuracy.
# 2007 Elsevier B.V. All rights reserved. Platform: |
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Author:alice |
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Description: 提出了一种基于改进型微粒群算法的无线传
感器网络分簇路由算法来优化分簇过程。簇首节点的选取综合考虑候选节点和邻居节点的状态信息-Proposed a modified particle swarm algorithm based on wireless sensor network clustering routing algorithm to optimize the clustering process. Cluster head node, considering the selection of the candidate node and the neighbor node state information Platform: |
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Author:Sherry |
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Description: 针对传统推荐算法的数据稀疏性问题和推荐准确性问题，提出基于粒子群优化的项聚类推荐算法。采用粒子群优化算法产生聚类中心，在此基础上搜索目标项目的最近邻居，并产生推荐，从而提高了传统聚类算法的推荐准确性及响应速度。实验表明改进的项聚类协同过滤算法能有效提高推荐精度-Aiming at the problems that the data are sparse and the results are not accurate in traditional recommendation algorithms, this paper proposes an item clustering recommendation algorithm based on Particle Swarm Optimization(PSO) algorithm. It uses PSO to engender the cluster centers, calculates the similarity between target item and cluster centers to search the nearest neighbors of target item, and gains a recommendation, so that it improves the accuracy and the real-time performance. Experimental results indicate that the algorithm can effectively improve the accuracy of the recommendation system Platform: |
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Author:ming |
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Description: 引入能够处理混合型数据的K-prototypes聚类算法，在此基础上构造了一种基于粒子群优化算法和K-prototypes方法的混合聚类算法-this paper employs the K-prototypes clustering algorithm to deal with mixed valued data, and designs a hybrid clustering algorithm based on particle swarm optimization algorithm and K-prototypes algorithm by using the strong local search ability and fast convergence characteristic of the K-prototypes algorithm and the strong global search ability of particle swarm optimization algorithm. Platform: |
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Author:伍洁 |
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Description: 基于改进粒子群算法的C均值聚类算法研究。是一篇改进FCM算法的很好的文章。-Based on improved particle swarm algorithm of the C mean clustering algorithm research Platform: |
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Author:白鑫 |
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Description: 改进的微粒群算法来聚类高维数据，重点解决了变量加权问题，聚类质量较高。-Improved particle swarm algorithm to cluster high dimensional data, focused on solving the problem of variable weighting and clustering of high quality Platform: |
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Author:何直直 |
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Description: 义了一个欧氏距离和监督信息相混合的新的最近邻计算函数，从而将K一均值算法很好地应用于半
监督聚类问题。针对K一均值算法初始质心敏感的缺陷，用粒子群算法的搜索空间模拟聚类的欧氏空间，迭代搜
索找到较优的聚类质心，同时提出动态管理种群的策略以提高粒子群算法搜索效率。算法在UCI的多个数据集
上测试都得到了较好的聚类准确率。-Righteousness of a Euclidean distance and supervision of a mixture of new nearest neighbor calculation functions, thus the K-means algorithm applied to the semi-supervised clustering problem. K-means algorithm the initial center of mass-sensitive defect clustering in the search space of the particle swarm algorithm simulation in Euclidean space, an iterative search to find the optimum cluster centroid, and strategies to improve particle swarm optimization to dynamic management of stocks search efficiency. Algorithm on multiple datasets in the UCI tests are a good clustering accuracy. Platform: |
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Author:xz |
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Description: An efficient hybrid data clustering method based on K-harmonic means and Particle Swarm Optimization Platform: |
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Author:habib |
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Description: Application of a hybrid of genetic algorithm and particle swarm optimization
algorithm for order clustering Platform: |
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Author:habib |
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Description: Application of quantum-behaved particle swarm algorithm in clustering of genes量子行为粒子群算法在基因聚类中的应用-Application of quantum-behaved particle swarm algorithm in clustering of genes Platform: |
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Author:张人龙 |
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Description: 本文是基于最新的模糊C均值彩色图像分割方法改进得来的新算法-This article is based on the fuzzy c-means clustering color image segmentation method of the latest paper Platform: |
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Author:duo |
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Search - swarm clustering