THE EFFECT OF KERNEL FUNCTION ON PRODUCT QUALITY PREDICTION BY SUPPORT VECTOR REGRESSION

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SHOKRI S.; SADEGHI M.T.; AHMADI MARVAST M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Seminar Paper

Paper Information

Seminar: CHEMICAL ENGINEERING CONGRESS AND EXHIBITION
Year:2014 | Issue:8

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Title

THE EFFECT OF KERNEL FUNCTION ON PRODUCT QUALITY PREDICTION BY SUPPORT VECTOR REGRESSION

Author(s)

SHOKRI S. | SADEGHI M.T. | AHMADI MARVAST M. | Issue Writer Certificate

Keywords

KERNEL FUNCTION

SOFT SENSORS

MACHINE LEARNING

SUPPORT VECTOR REGRESSION (SVR)

SULFUR CONTENT

HYDRODESULFURIZATION PROCESS

Abstract

SOFT SENSORS CAN BE USED INSTEAD OF HARDWARE ANALYZERS IN DIRECT MEASUREMENT. SINCE HARDWARE ANALYZERS ARE USUALLY EXPENSIVE AND DIFFICULT TO MAINTAIN. MOREOVER, WHEN HARDWARE SENSORS ARE NOT AVAILABLE, SOFT-SENSORS ARE KEY TECHNOLOGIES FOR PRODUCING HIGH QUALITY PRODUCTS. SUPPORT VECTOR REGRESSION (SVR) IS AN EFFICIENT MACHINE LEARNING TECHNIQUE CAN BE USED FOR SOFT SENSOR DESIGN IN CHEMICAL PROCESSES. ONE OF THE MOST IMPORTANT FACTORS IN FORECASTING PERFORMANCE OF SVR IS KERNEL FUNCTION. IN THIS STUDY, SVR MODEL IS EVALUATED AS PREDICTOR THE REACTOR PRODUCT QUALITY IN HDS PROCESS WITH FOUR DIFFERENT KERNELS NAMELY LINEAR KERNEL, POLYNOMIAL KERNEL, SIGMOID KERNEL AND RADIAL BASIS FUNCTION (RBF) KERNEL. ALSO GENETIC ALGORITHM (GA) WAS USED TO OPTIMIZE THE MODEL PARAMETERS. THE RESULTS SHOW THAT THE RBF KERNEL PRODUCES THE BEST PERFORMANCE INFORECASTING OF SULFUR CONTENT. THE PROPOSED METHOD PROVIDES A ROBUST TOOL TO PREDICT THE SULFUR CONTENT OF THE HDS PRODUCT IN A WIDE RANGE OF SULFUR CONTENT WITH GOOD ACCURACY.

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APA: Copy

SHOKRI, S., SADEGHI, M.T., & AHMADI MARVAST, M.. (2014). THE EFFECT OF KERNEL FUNCTION ON PRODUCT QUALITY PREDICTION BY SUPPORT VECTOR REGRESSION. INTERNATIONAL CHEMICAL ENGINEERING CONGRESS AND EXHIBITION. SID. https://sid.ir/paper/915212/en

Vancouver: Copy

SHOKRI S., SADEGHI M.T., AHMADI MARVAST M.. THE EFFECT OF KERNEL FUNCTION ON PRODUCT QUALITY PREDICTION BY SUPPORT VECTOR REGRESSION. 2014. Available from: https://sid.ir/paper/915212/en

IEEE: Copy

S. SHOKRI, M.T. SADEGHI, and M. AHMADI MARVAST, “THE EFFECT OF KERNEL FUNCTION ON PRODUCT QUALITY PREDICTION BY SUPPORT VECTOR REGRESSION,” presented at the INTERNATIONAL CHEMICAL ENGINEERING CONGRESS AND EXHIBITION. 2014, [Online]. Available: https://sid.ir/paper/915212/en

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