{"title":"基于随机矩阵的大数据绿色挖掘算法","authors":"Wang Can-wei","doi":"10.14257/IJDTA.2016.9.12.08","DOIUrl":null,"url":null,"abstract":"Due to big data with related multi-dimensional characteristics, the effective means how to build processing mechanisms and algorithms are still problems; so that the algorithms on big data processing huge resources and time cost of computing, resulting in wasting of energy; for this problem the present study proposes a large data processing algorithm of random matrix theory application, can effectively improve the processing efficiency, thereby increasing the utilization of energy. Results show that the proposed algorithm can effectively reduce the amount of calculation, thus saving and calculating the required energy.","PeriodicalId":13926,"journal":{"name":"International journal of database theory and application","volume":"9 1","pages":"79-88"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Green Mining Algorithm for Big Data Based on Random Matrix\",\"authors\":\"Wang Can-wei\",\"doi\":\"10.14257/IJDTA.2016.9.12.08\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to big data with related multi-dimensional characteristics, the effective means how to build processing mechanisms and algorithms are still problems; so that the algorithms on big data processing huge resources and time cost of computing, resulting in wasting of energy; for this problem the present study proposes a large data processing algorithm of random matrix theory application, can effectively improve the processing efficiency, thereby increasing the utilization of energy. Results show that the proposed algorithm can effectively reduce the amount of calculation, thus saving and calculating the required energy.\",\"PeriodicalId\":13926,\"journal\":{\"name\":\"International journal of database theory and application\",\"volume\":\"9 1\",\"pages\":\"79-88\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of database theory and application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14257/IJDTA.2016.9.12.08\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of database theory and application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/IJDTA.2016.9.12.08","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Green Mining Algorithm for Big Data Based on Random Matrix
Due to big data with related multi-dimensional characteristics, the effective means how to build processing mechanisms and algorithms are still problems; so that the algorithms on big data processing huge resources and time cost of computing, resulting in wasting of energy; for this problem the present study proposes a large data processing algorithm of random matrix theory application, can effectively improve the processing efficiency, thereby increasing the utilization of energy. Results show that the proposed algorithm can effectively reduce the amount of calculation, thus saving and calculating the required energy.