التفاصيل البيبلوغرافية
| العنوان: |
Anticipate Manning’s Coefficient in Meandering Compound Channels |
| المؤلفون: |
Abinash Mohanta, Kanhu Charan Patra, Bibhuti Bhusan Sahoo |
| المصدر: |
Hydrology; Volume 5; Issue 3; Pages: 47 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2018 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
doubly meandering compound channel, Group Method of Data Handling, multivariate adaptive regression spline, Manning’s roughness coefficient, support vector regression, discharge, error analysis, box and whisker plot |
| جغرافية الموضوع: |
agris |
| الوصف: |
Estimating Manning’s roughness coefficient ( n ) is one of the essential factors in predicting the discharge in a stream. Present research work is focused on prediction of Manning’s n in meandering compound channels by using the Group Method of Data Handling Neural Network (GMDH-NN) approach. The width ratio ( α ) , relative depth ( β ) , sinuosity ( s ) , Channel bed slope ( S o ) , and meander belt width ratio ( ω ) are specified as input parameters for the development of the model. The performance of GMDH-NN is evaluated with two different machine learning techniques, namely the support vector regression (SVR) and multivariate adaptive regression spline (MARS) with various statistical measures. Results indicate that the proposed GMDH-NN model predicts the Manning’s n satisfactorily as compared to the MARS and SVR model. This GMDH-NN approach can be useful for practical implementation as the prediction of Manning’s coefficient and subsequently discharge through Manning’s equation in the compound meandering channels are found to be quite adequate. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
https://dx.doi.org/10.3390/hydrology5030047 |
| DOI: |
10.3390/hydrology5030047 |
| الاتاحة: |
https://doi.org/10.3390/hydrology5030047 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.580A85F2 |
| قاعدة البيانات: |
BASE |