Predicting Runoff Chloride Concentrations in Suburban Watersheds Using an Artificial Neural Network (ANN)
نویسندگان
چکیده
منابع مشابه
predicting developmental disorder in infants using an artificial neural network.
early recognition of developmental disorders is an important goal, and equally important is avoiding misdiagnosing a disorder in a healthy child without pathology. the aim of the present study was to develop an artificial neural network using perinatal information to predict developmental disorder at infancy. a total of 1,232 mother-child dyads were recruited from 6,150 in the original data of ...
متن کاملrunoff estimation using artificial neural network method
runoff is one of the major components of calculating water resource processes and is the main issue in hydrology. many concept models are used to predict the amount of runoff, which in most cases depend on topographical and hydrological data. conventional models are not appropriate for areas in which there is little hydrological data. changes in runoff are nonlinear, meaning it is time & space ...
متن کاملDaily Runoff Forecasting using Artificial Neural Network
Rainfall-Runoff is the most important hydrological variables used in most of the water resources applications. Watershed based planning and management requires thorough understanding hydrological process and accurate estimation of runoff. An Artificial Neural Network (ANN) methodology was employed to forecast daily runoff for the Kadam watershed of G-5 sub-basin of Godavari river basin. On the ...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Artificial Neural Network Modeling for Predicting of some Ion Concentrations in the Karaj River
The water quality of the Karaj River was studied through collecting 2137 experimental data set gained by 20 sampling stations. The data included different parameters such as T (temperature), pH, NTU (turbidity), hardness, TDS (total dissolved solids), EC (electrical conductivity) and basic anion, cation concentrations. In this study a multi-layer perceptron artificial neural network model was d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Hydrology
سال: 2020
ISSN: 2306-5338
DOI: 10.3390/hydrology7040080