Developing a Novel Method for Estimating the Speed of Sound in Biodiesel Known as Grey Wolf Optimizer Support Vector Machine Algorithm.

Journal: BioMed research international
Published Date:

Abstract

In the current study, our goal was to obtain a robust model to predict the speed of sound in biodiesel. For this purpose, an extensive databank has been extracted from previously published papers. Then, a Support Vector Machine (SVM) has been optimized by Grey Wolf Optimization (GWO) method to analyze these data and determine the correlation between speed of sound in biodiesel and its related properties including pressure, temperature, molecular weight, and normal melting point. The results were very satisfactory because the values of statistical parameters and RMSE were obtained 1 and 1.4024, respectively. Here, this is the first time that the sensitivity analysis is used to estimate this target value. This analysis shows that the pressure widely affects the output values with relevancy factor 87.92. Also, our proposed method is highly accurate than other machine learning methods used in papers employed for this objective.

Authors

  • Zhenzhen Lv
    School of Electrical and Information Engineering, Anhui University of Technology, Maanshan, Anhui 243002, China.
  • Ming Hu
    Department of Civil and Environmental Engineering and Earth Sciences, College of Engineering, University of Notre Dame, Notre Dame, IN, 46556, USA.
  • Yixin Yang
    School of Electrical and Information Engineering, Anhui University of Technology, Maanshan, Anhui 243002, China.
  • Jeren Makhdoumi
    Department of Educational Science, Payame Noor University, Damghan, Iran.