School of Electrical and Information Engineering, Anhui University of Technology, Maanshan, Anhui 243002, China.
Department of Educational Science, Payame Noor University, Damghan, Iran.
Biomed Res Int. 2021 Jul 2;2021:5368987. doi: 10.1155/2021/5368987. eCollection 2021.
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.
在当前的研究中，我们的目标是获得一个稳健的模型来预测生物柴油中的声速。为此，从以前发表的论文中提取了一个广泛的数据库。然后，使用灰狼优化（GWO）方法对支持向量机（SVM）进行了优化，以分析这些数据并确定生物柴油中的声速与其相关性质（包括压力、温度、分子量和正常熔点）之间的相关性。结果非常令人满意，因为统计参数 和 RMSE 的值分别为 1 和 1.4024。在这里，这是第一次使用敏感性分析来估计这个目标值。该分析表明，压力对输出值的影响很大，相关因子为 87.92。此外，与用于该目标的其他机器学习方法相比，我们提出的方法具有更高的准确性。
