Related Experiment Video
Updated: Dec 26, 2025

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
Published on: September 26, 2017
Granular computing-neural network model for prediction of longitudinal dispersion coefficients in rivers
Behzad Ghiasi1, Hossein Sheikhian2, Amin Zeynolabedin3
1School of Environment, College of Engineering, University of Tehran, Tehran, Iran
Abstract:
Successful application of one-dimensional advection-dispersion models in rivers depends on the accuracy of the longitudinal dispersion coefficient (LDC). In this regards, this study aims to introduce an appropriate approach to estimate LDC in natural rivers that is based on a hybrid method of granular computing (GRC) and an artificial neural network (ANN) model (GRC-ANN). Also, adaptive neuro-fuzzy inference system (ANFIS) and ANN models were developed to investigate the accuracy of three credible artificial intelligence (AI) models and the performance of these models in different LDC values. By comparing with empirical models developed in other studies, the results revealed the superior performance of GRC-ANN for LDC estimation. The sensitivity analysis of the three intelligent models developed in this study was done to determine the sensitivity of each model to its input parameters, especially the most important ones. The sensitivity analysis results showed that the W/H parameter (W: channel width; H: flow depth) has the most significant impact on the output of all three models in this research.
Related Concept Videos
Typical Model Studies
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Design Example: Creating a Hydraulic Model of a Dam Spillway
Rapidly Varying Flow
Distribution and Dispersion
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...