evaluating the performance of artificial neural network model in downscaling daily temperature, precipitation and wind speed parameters

Performance evaluation of artificial neural networks in statistical downscaling of monthly precipitation (Case study: Minab watershed)

scour 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...

Downscaling of daily precipitation

Downscaling of daily precipitation with a stochastic weather generator for the subtropical region in South China Y. D. Chen, X. Chen, C.-Y. Xu, and Q. Shao Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, Hong Kong, China State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China Department of Geosci...

Downscaling Temperature and Precipitation: A Comparison of Regression-Based Methods and Artificial Neural Networks

A comparison of two statistical downscaling methods for daily maximum and minimum surface air temperature, total daily precipitation and total monthly precipitation at Indianapolis, IN, USA, is presented. The analysis is conducted for two seasons, the growing season and the non-growing season, defined based on variability of surface air temperature. The predictors used in the downscaling are in...

Hourly Wind Speed Prediction using ARMA Model and Artificial Neural Networks

In this paper, a comparison study is presented on artificial intelligence and time series models in 1-hour-ahead wind speed forecasting. Three types of typical neural networks, namely adaptive linear element, multilayer perceptrons, and radial basis function, and ARMA time series model are investigated. The wind speed data used are the hourly mean wind speed data collected at Binalood site in I...

Evaluating the capabilities of Logistic Model Tree in predicting the occurrence probability of daily precipitation

Due to the location of Iran in arid and semi-arid regions and the inhomogeneous distribution of precipitation, predicting the occurrence of precipitation is important, therefore, researchers are implementing novel methods to identify and predict this parameter accurately. Thus the purpose of the current study is to investigate the capabilities of Logistic Model Tree (LMT) in predicting the occu...