农业工程2025，Vol.15Issue(9)：20-26,7.DOI:10.19998/j.cnki.2095-1795.202509304
基于改进加权聚类算法的小麦种质推荐模型
Wheat germplasm recommendation model based on improved weighted clustering algorithm
摘要
Abstract
With growing wheat germplasm resources data,how to help breeding experts to obtain wheat germplasm efficiently and ac-curately has become an urgent issue.For this problem,a clustering algorithm-based wheat germplasm recommendation model was pro-posed.Wheat germplasm dataset was clustered using K-means to identify cluster centers of dataset.Cluster group was found to which breeding experts'germplasm data belonged,and then the nearest neighbor algorithm was used to derive wheat germplasm required by ex-perts.Considering different contributions degree of wheat germplasm attribute features,gray weighted K-means clustering algorithm(GWK-means)was proposed.When calculating similarity of wheat germplasm by Euclidean distance,weight of wheat germplasm at-tributes were determined by grey correlation analysis,increasing distance between different clusters,improving accuracy and running speed of clustering algorithm,and providing a strong support for recommendation model.Experimental results on wheat germplasm dataset showed that average accuracy of the top 5 recommended wheat germplasm results and germplasm required by breeding experts reached more than 94%.关键词
小麦种质资源/灰色关联分析/聚类/GWK-means/推荐模型Key words
wheat germplasm resources/gray correlation analysis/cluster/GWK-means/recommendation model分类
农业科技引用本文复制引用
苏楠,司海平,李若璞,李艳玲,方沩,闫文敬..基于改进加权聚类算法的小麦种质推荐模型[J].农业工程,2025,15(9):20-26,7.基金项目
河南省科技研发计划联合基金项目(应用攻关类)(242103810028) （应用攻关类）
河南省重点研发专项(251111211300、231111110100) （251111211300、231111110100）
河南省教育厅高等学校重点项目(25A520044) （25A520044）
河南省杰出外籍科学家工作室项目(GZS2024006) （GZS2024006）
