| 基于数据最优分区间相似度算法及应用 |
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| 引用本文： | 詹棠森,林卫中.基于数据最优分区间相似度算法及应用[J].数学的实践与认识,2009,39(20). |
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| 作者姓名： | 詹棠森 林卫中 |
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| 作者单位： | 景德镇陶瓷学院,信息工程学院,江西,景德镇,333403 |
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| 基金项目： | 国家自然科学基金，赣财教[2008]147号省科技厅项目支持，校基金支持 |
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| 摘 要： | 通过定义了一种基于数据最优分区间相似度算法,利用学习样本得单位相似度向量,并得各维数据的最优分区间.利用最优分区间得预测样本与学习样本的单位相似度向量,从而得预测样本的预测值.通过实例表明,算法所预测的结果相对误差可达百分位,并且本算法能应用到其它数据处理中,具有较广泛的通用性.
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| 关 键 词： | 最优分区间 单位相似度向量 预测 |
Similarity Algorithm and Its Application on the Data Optimization Partition |
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| ZHAN Tang-sen,LIN Wei-zhong.Similarity Algorithm and Its Application on the Data Optimization Partition[J].Mathematics in Practice and Theory,2009,39(20). |
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| Authors: | ZHAN Tang-sen LIN Wei-zhong |
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| Abstract: | A algorithm of similarity on the data optimization partition is definited, unit similarity vector and data optimization partition are got through study samples. Using optimization partition, the unit similarity vector between forecast samples and study samples is computated, and prediction value of prediction sample is gained. The examples show that the Relative error of results got by the algorithm has the one-thousandth, and the algorithm can be applied on other data and has widespread versatility. |
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| Keywords: | optimization partition unit similarity vector similarity agorithm prediction |
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