Affiliation:
1. a Department of Civil Engineering, Delhi Technological University, Delhi 110042, India
2. b Department of Civil Engineering, Methodist College of Engineering, Hyderabad 500001, India
Abstract
ABSTRACT
Achieving an accurate estimation of the flow resistance in open channel flows is crucial for resolving several critical engineering difficulties. In instances when there is excessive flow on both banks of a river, it results in the breach of the primary channel, leading to the discharge of water into the adjacent floodplain. The alteration of floodplain geometry occurs as a consequence of agricultural and developmental practises, leading to the emergence of compound channels that exhibit converging, diverging, or skewed characteristics throughout the course of the flow. The efficacy of conventional equations in accurately forecasting flow resistance is limited due to their heavy reliance on empirical approaches. As a result of this phenomenon, there persists a significant need for methodologies that possess both novelty and precision. The objective of this work is to use the support vector machine (SVM) technique for the estimation of the Manning's roughness coefficient in a compound channel with converging floodplains. Statistical indicators are used to validate the constructed models in the experimental investigation, enabling the assessment of their performance and efficacy. The findings indicate a significant correlation between the Manning's roughness coefficient predicted by SVM and both experimental data and prior research outcomes.
Reference48 articles.
1. Bhattacharya A. K. 1995 Mathematical Model of Flow in A Meandering Channel. PhD Thesis, Indian Institute of Technology Kharagpur, India.
2. Estimation of water's surface elevation in compound channels with converging and diverging floodplains using soft computing techniques;Bijanvand;Water Supply,2023
3. Comparison of constitutive flow resistance equations based on the Manning and Chezy equations applied to natural rivers
4. Support vector regression applied to magnetic resonance imaging: An approach to predicting hepatic iron concentration;Borges;Journal of Digital Imaging,2016
5. Periodical turbulent structures in compound channels;Bousmar,2002