基于核变换的近邻传播聚类算法的金融市场分析  

Financial Market Analysis Based on Kernel Transformation Affinity Propagation clusteringalgorithm

作　　者：荀振宇 王卫涛 Xun Zhenyu;Wang Weitao(The First Military Representative Office of the Maritime Equipment Shenyang Bureau in Dalian,Dalian 116000;713th Research Institute China Ship Building Industry Corporation,Zhengzhou 450000)

机构地区：[1]海装沈阳局驻大连地区第一军事代表室,辽宁大连116000 [2]中船重工第七一三研究所,河南郑州450000

出　　处：《科学与信息化》2020年第5期37-40,共4页Technology and Information

摘　　要：本文设计了基于改进的近邻传播聚类算法的金融市场分析案例.首先,本文提出了基于属性权重以及核变换的WHAP算法.WHAP算法首先计算出样本集每维特征的权重值,然后根据每维权重值计算出样本点之间的距离,再然后通过核函数将样本点之间的距离进行映射变换计算出相似度矩阵,最终计算出解聚类结果;然后,本文结合Spring boot、Redis、Vue、MySQL搭建出一套应用开发系统,该系统进行数据的选择同时将数据量化为WHAP算法可处理的数据集,然后将此数据集作为该算法的输入样本集,再然后通过计算将聚类结果转换为页面可视化数据,最终通过聚类结果为金融市场提供有效的参考方案.This article designs a financial market analysis case based on improved Affinity Propagation clustering algorithm.First,this paper proposes an WHAP algorithm based on attribute weights and kernel transformation.The WHAP algorithm first calculates the weight value of each dimension of the sample set,then calculate the distance between the sample points according to the weight value of each dimension,Then use the kernel function to map the distance between the sample points to calculate the similarity matrix,Finally calculate the clustering results;Second,This article combines Spring Boot,Redis,Vue,and MySQL to build a set of application development systems,The system selects data and quantizes the data into a dataset that can be processed by the WAP algorithm,This data set is then used as the input sample set for the algorithm,The clustering results are then converted into page visualization data by calculation,Finally,provide effective reference solutions for financial markets through clustering results.

关 键 词：权重 核函数 Springboot 金融市场 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]