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Prediction of critical parameters for automation of kiln process using DNN regression

By: Fernando, Warnakulasuriya kalugamage Cashiyan Pramod PrimalkaContributor(s): Prof. D.P. Chandima [supervisor] | Prof. A.G.B.P. Jayasekara [supervisor]Language: English Publisher: [2022]Description: xii, 74p. : charts, ill., col. photos., tables, CD-ROMSubject(s): CLINKER MANUFACTURING | ROTARY KILN SYSTEM | DEEP NEURAL NETWORK | REGRESSION MODEL | MACHINE LEARNING | KILN PROCESS AUTOMATION | KILN BEHAVIORAL PATTERNS | ELECTRICAL ENGINEERING - Dissertation | INDUSTRIAL AUTOMATION - Dissertation | MSc in Industrial AutomationOnline resources: Click here to access online Dissertation note: Department of Electrical Engineering Faculty of Engineering University of Moratuwa 2022
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Thesis Thesis Library, University of Moratuwa
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Thesis Collection
681.5(043) (Browse shelf) DEE 06/54 LB/TH/15/2022 Not For Loan (Restricted Access) TH4765

M.Sc. in Industrial Automation

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Department of Electrical Engineering Faculty of Engineering University of Moratuwa 2022

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