Forecast of daily mean, maximum and minimum temperature time series by three artificial neural network methods

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

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...

a comparison between time series, exponential smoothing, and neural network methods to forecast gdp of iran

trend analysis of minimum, maximum, and mean daily temperature extremes in several climatic regions of iran

an increase, even moderate, in global temperature is expected to result in a change in frequency of extreme weather events like drought, heavy rainfall and storms. the study of extreme events is difficult due to the fact that it is difficult to find long-term homogeneous data series. also the delimitation of extreme events is not univocal since a parameter value that would be defined as an extr...

Availability Prediction of the Repairable Equipment using Artificial Neural Network and Time Series Models

In this paper, one of the most important criterion in public services quality named availability is evaluated by using artificial neural network (ANN). In addition, the availability values are predicted for future periods by using exponential weighted moving average (EWMA) scheme and some time series models (TSM) including autoregressive (AR), moving average (MA) and autoregressive moving avera...