Abstract

Viscosity of mixed oil is an important parameter which is required in transportation and production processes of mixed crude oils. There is no universal and general model for prediction of viscosity of mixed oils at different conditions. Hence, developing simple, accurate and general models for prediction of mixed oil viscosity is of great importance. In this work three computer based models named MLP-NN, PSO-RBF and Hybrid-ANFIS were developed for prediction of viscosity of mixed oils. A number of 513 experimental data covering wide ranges of influencing parameters were utilized to develop the models. The accuracy of predictions of the developed models was examined by using different statistical quality measure approaches as well as comparing their results with predictions of literature models. Results showed that the developed models present accurate predictions and are superior to literature models. The predictions of MLP-NN model were also better than Hybrid-ANFIS and PSO-RBF models.

摘要

混合油的粘度是混合原油的运输和生产过程中所需的重要参数。没有通用和通用的模型可以预测不同条件下混合油的粘度。因此，开发用于预测混合油粘度的简单，准确和通用的模型非常重要。在这项工作中，开发了三种基于计算机的模型MLP-NN，PSO-RBF和Hybrid-ANFIS，用于预测混合油的粘度。利用513个涵盖广泛影响参数的实验数据来开发模型。通过使用不同的统计质量度量方法以及将其结果与文献模型的预测进行比较，检查了已开发模型的预测的准确性。结果表明，所开发的模型可以提供准确的预测，并且优于文献模型。MLP-NN模型的预测也优于Hybrid-ANFIS和PSO-RBF模型。