دورية أكاديمية
Optimization of Adaptive Neuro-Fuzzy Inference System using Differential Evolution Algorithm for Scour Prediction around Submerged Pipes
| العنوان: | Optimization of Adaptive Neuro-Fuzzy Inference System using Differential Evolution Algorithm for Scour Prediction around Submerged Pipes |
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| المؤلفون: | Ali Reza Mahmodian, Behrouz Yaghoubi, fariborz yosevfand |
| المصدر: | International Journal of Coastal and Offshore Engineering, Vol 3, Iss 1, Pp 1-10 (2019) |
| بيانات النشر: | Iranian Association of Naval Architecture and Marine Engineering, 2019. |
| سنة النشر: | 2019 |
| المجموعة: | LCC:Ocean engineering |
| مصطلحات موضوعية: | scouring, anfis, differential evolution algorithm, submerged pipes, hybrid model, Ocean engineering, TC1501-1800, Harbors and coast protective works. Coastal engineering. Lighthouses, TC203-380 |
| الوصف: | Nowadays, a huge amount of natural resources such as gases and oil are exploited from offshore oil fields and transported by pipes located at seabed. The pipelines are exposed to waves and currents and scour may occur around them. Subsequently, stability of the pipes can be threatened, so estimation and simulation of scouring around the pipes are quite vital. In this study, a hybrid method for simulating the scour depth in the vicinity of submerged pipes was developed. In other words, the adaptive neuro-fuzzy inference system (ANFIS) and the differential algorithm were combined with each other to simulate the scour depth. In general, ANFIS is an artificial neural network acts based on the Takagi-Sugeno inference system. This model is a set of if-then rules which is able to approximate non-linear functions. In addition, the differential algorithm is a powerful evolutionary algorithm among optimization algorithms which have many applications in scientific fields. In this study, the Monte-Carlo simulation was employed for examining the ability of numerical models. To validate the modeling results, the k-fold cross validation approach was also utilized with k=6. Then, the parameters affecting the scour depth were detected and six ANFIS and hybrid models were developed for scour estimation. After that, the results of the mentioned models were examined and this analysis showed that the superior model predicts scour values in terms of all input parameters. This model has reasonable accuracy. For example, the values of R and RMSE for this model were calculated 0.974 and 0.079, respectively. Furthermore, the analysis of the modeling results indicated that the ratio of the pipe distance from the sedimentary bed to the pipe diameter (e/D) was identified as the most effective parameter. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2538-2667 2588-3186 |
| العلاقة: | http://ijcoe.org/article-1-102-en.htmlTest; https://doaj.org/toc/2538-2667Test; https://doaj.org/toc/2588-3186Test |
| الوصول الحر: | https://doaj.org/article/dca9e975967f4ea59bc090287b26478fTest |
| رقم الانضمام: | edsdoj.9e975967f4ea59bc090287b26478f |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 25382667 25883186 |
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