The developed surrogate models are then utilized to forecast production for any input distribution of permeability using Monte Carlo simulations.
The wavelet analysis was utilized to capture multiscale data characteristics, while a real neural network (RNN) was utilized to forecast crude oil prices at different scales.
It is found that for developing and developed economies, forecasted EEC trends are significantly different, as expected, and IPSO ANN model can be utilized to forecast long-term EEC up to 2030 with mean absolute percentage error of 1.94 and 1.51% for Iran and the U.S., respectively.
In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component.
Firstly an ELM is utilized to forecast the short-term wind power.
A stacked denoising autoencoder (SDA) model, a class of deep neural networks (DNN), and its extended version are utilized to forecast the daily electricity price profile.
In [19], several methods with some economic data as inputs are utilized to forecast the monthly average price, and the best mean absolute percentage error (MAPE) in these methods is 12.97%.
Subsequently, this model is utilized to forecast the real pattern of genes' differential expression.
In this study, four methods of forecasting using artificial intelligence (artificial neural networks with radial basis function, adaptive neuro-fuzzy inference system, artificial neural network-genetic algorithm hybrid and artificial neural network-particle swarm optimization) are utilized to accurately forecast short-term wind speed data for Tehran, Iran.
Companies can now be digitally-equipped to gather detailed information internally and utilize predictive analytics to forecast more accurately and quickly.
Meanwhile, LSSVM is utilized to establish forecasting models of the trend component and main components, where their parameters are optimized by PSO algorithm.
