多媒体图像数据投影聚类融合算法优化研究

Multimedia Projection Image Data Fusion Algorithm Clustering Optimization Research

提出基于粒子群的多媒体图像数据投影聚类融合优化算法,首先利用误差反传的梯度下降训练,选取出多媒体图像数据投影的聚类成员,为后续聚类融合提供准确的数据基础;其次计算每个多媒体图像数据投影基聚类算法被选入优化基聚类子集的概率;最后利用粒子群算法进行全局寻优,实现对多媒体图像数据投影聚类融合算法的优化.通过实验验证分析,结果表明,所提算法可以提高多媒体图像数据投影融合质量和聚类准确率.

In this paper, a multimedia projection image data clustering based on particle swarm optimization algorithm fusion, first using the gradient descent of error back propagation training, selection of multimedia projection image data clustering members, provide accurate data foundation for the subsequent clustering fusion; A comprehensive evaluation of the definition of diversity and correctness and then use standard, realize the selectivity of multimedia projection image data clustering fusion; Finally on this basis using the particle swarm algorithm of global optimization for its optimization. Through the experiment analysis, the results show that the proposed algorithm can improve the quality of multimedia projection image data fusion and clustering accuracy.