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Based on analyzing the statistical properties of a real large-scale workload, domain knowledge, which provides extended information about workload changes, is embedded into artificial neural networks (ANN) for linear regression to improve prediction accuracy. Furthermore, the regularization with noisy is combined to improve the generalization ability of artificial neural networks. The experiments demonstrate that the model can achieve more accuracy of workload prediction, provide more adaptive resource for higher resource cost effectiveness and have less impact on the QoS.<\/jats:p>","DOI":"10.4018\/jitr.2018100109","type":"journal-article","created":{"date-parts":[[2018,8,24]],"date-time":"2018-08-24T12:08:11Z","timestamp":1535112491000},"page":"137-154","source":"Crossref","is-referenced-by-count":7,"title":["Domain Knowledge Embedding Regularization Neural Networks for Workload Prediction and Analysis in Cloud Computing"],"prefix":"10.4018","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7782-1876","authenticated-orcid":true,"given":"Lei","family":"Li","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Min","family":"Feng","sequence":"additional","affiliation":[{"name":"21CN Co., Ltd., Guangzhou, China"}]},{"given":"Lianwen","family":"Jin","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Shenjin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Lihong","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"}]},{"given":"Jiakai","family":"Gao","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}]}],"member":"2432","reference":[{"journal-title":"Technical Analysis from A to Z","year":"2001","author":"S. 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