estimation of the suspended sediment loud of karaj river using fuzzy logic and neural networks

Suspended Sediment Estimation and Forecasting using Artificial Neural Networks

The methods available in the literature for sediment concentration estimation are complicated and time consuming and necessitate cumbersome parameter estimation procedures. In this study, artificial neural networks (ANNs) are used to forecast and estimate sediment concentration values. The forecasting results obtained using previously observed sediment values were close to the real ones. The se...

the use of appropriate madm model for ranking the vendors of mci equipments using fuzzy approach

abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...

Comparison and evaluation of intelligent models for river suspended sediment estimation (case study: Kakareza River, Iran)

Sediment transport constantly influences river and civil structures and the lack ofinformation about its exact amount makes management efforts less effective. Hence,achieving a proper procedure to estimate the sediment load in rivers is important. We usedsupport vector machine model to estimate the sediments of the Kakareza River in LorestanProvince and the results were compared with those obta...

Modeling Suspended Sediment Prediction in River Using a Fuzzy Logic and Multi Linear Regression Approaches

Suspended Sediment Estimation for Rivers using Artificial Neural Networks and Sediment Rating Curves

The methods available for sediment concentration and flux estimation are largely empirical, with sediment rating curves being the most widely applied. In this study, a comparison is made between artificial neural networks (ANNs) and sediment rating curves for two rivers with very similar catchment areas and characteristics in the north of England. Data from one river are used to estimate sedime...

Prediction of Suspended Sediment Concentration in River Flow Using Artificial Neural Networks

Building a numerical model in not an easy task. In addition to its need for verification, it requires special skills and experiences in mathematics, computer programming and may take long period to be ready for operation and prediction. On the other hand, artificial neural network ANN) prediction models are more efficient in predictions once they are trained from examples or patterns. These typ...