{"title":"基于人工神经网络的Amazon Web Service聚类数据有效预测","authors":"P. Kaul, Hardik Agarwal, G. Raj","doi":"10.1109/ICCOMM.2018.8430126","DOIUrl":null,"url":null,"abstract":"Now a days, there are number of cab services providers which are confusing the client with number of similar kind of service options. That's why there is a need of selecting a quality service from a set of given services. It motivates us to design an approach which is efficient in providing the effective service after the data analysis of real time data developed and collected through Amazon Web Services. This paper aims at analyzing a mathematical model that is used to predict the most efficient output of a dataset of a model using Artificial Neural Network. The proposed mathematical model is made and applied on a database of real time cab services developed using Amazon Web Services to predict the effective web service. We have analyzed the real time dataset using Rapidminer. The Analysis is done on the bases of the threshold and root mean square error values obtained. We are proposing the methodology which is highly competent and accurate in obtaining the results.","PeriodicalId":158890,"journal":{"name":"2018 International Conference on Communications (COMM)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effective Prediction in Amazon Web Service Based Clustered Data Using Artificial Neural Networks\",\"authors\":\"P. Kaul, Hardik Agarwal, G. Raj\",\"doi\":\"10.1109/ICCOMM.2018.8430126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Now a days, there are number of cab services providers which are confusing the client with number of similar kind of service options. That's why there is a need of selecting a quality service from a set of given services. It motivates us to design an approach which is efficient in providing the effective service after the data analysis of real time data developed and collected through Amazon Web Services. This paper aims at analyzing a mathematical model that is used to predict the most efficient output of a dataset of a model using Artificial Neural Network. The proposed mathematical model is made and applied on a database of real time cab services developed using Amazon Web Services to predict the effective web service. We have analyzed the real time dataset using Rapidminer. The Analysis is done on the bases of the threshold and root mean square error values obtained. We are proposing the methodology which is highly competent and accurate in obtaining the results.\",\"PeriodicalId\":158890,\"journal\":{\"name\":\"2018 International Conference on Communications (COMM)\",\"volume\":\"89 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Communications (COMM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCOMM.2018.8430126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Communications (COMM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCOMM.2018.8430126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
现在,有许多出租车服务提供商,他们用许多类似的服务选项混淆了客户。这就是为什么需要从一组给定的服务中选择高质量的服务。这激励我们设计一种通过Amazon Web Services开发和收集的实时数据进行数据分析后,高效地提供有效服务的方法。本文旨在分析一个数学模型,该模型用于使用人工神经网络预测模型数据集的最有效输出。建立了该数学模型,并将其应用于基于Amazon Web services开发的实时出租车服务数据库,以预测有效的Web服务。我们使用Rapidminer分析了实时数据集。分析是在得到阈值和均方根误差值的基础上进行的。我们提出的方法在获得结果方面是高度称职和准确的。
Effective Prediction in Amazon Web Service Based Clustered Data Using Artificial Neural Networks
Now a days, there are number of cab services providers which are confusing the client with number of similar kind of service options. That's why there is a need of selecting a quality service from a set of given services. It motivates us to design an approach which is efficient in providing the effective service after the data analysis of real time data developed and collected through Amazon Web Services. This paper aims at analyzing a mathematical model that is used to predict the most efficient output of a dataset of a model using Artificial Neural Network. The proposed mathematical model is made and applied on a database of real time cab services developed using Amazon Web Services to predict the effective web service. We have analyzed the real time dataset using Rapidminer. The Analysis is done on the bases of the threshold and root mean square error values obtained. We are proposing the methodology which is highly competent and accurate in obtaining the results.