A big data urban growth simulation at a national scale: configuring the GIS and neural network based land transformation model to run in a high performance …
Abstract The Land Transformation Model (LTM) is a Land Use Land Cover Change (LUCC)
model which was originally developed to simulate local scale LUCC patterns. The model …
model which was originally developed to simulate local scale LUCC patterns. The model …
Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm
JP Donate, X Li, GG Sánchez, AS de Miguel - Neural Computing and …, 2013 - Springer
Time series forecasting is an important tool to support both individual and organizational
decisions (eg planning production resources). In recent years, a large literature has evolved …
decisions (eg planning production resources). In recent years, a large literature has evolved …
Evolutive design of ARMA and ANN models for time series forecasting
The evolutionary design of time series forecasters is a field that has been explored for
several years now. In this paper, a complete design and training of ARMA (Auto-Regressive …
several years now. In this paper, a complete design and training of ARMA (Auto-Regressive …
Forecasting seasonal time series with computational intelligence: On recent methods and the potential of their combinations
M Štěpnička, P Cortez, JP Donate… - Expert Systems with …, 2013 - Elsevier
Accurate time series forecasting is a key issue to support individual and organizational
decision making. In this paper, we introduce novel methods for multi-step seasonal time …
decision making. In this paper, we introduce novel methods for multi-step seasonal time …
[HTML][HTML] Application of ANFIS hybrids to predict coefficients of curvature and uniformity of treated unsaturated lateritic soil for sustainable earthworks
Unsaturated lateritic soils are complex soils to work with due to moisture effects. So, the
determination of its properties requires lots of time, labor and equipment. For this reason, the …
determination of its properties requires lots of time, labor and equipment. For this reason, the …
[HTML][HTML] Oil-price forecasting based on various univariate time-series models
GA Tularam, T Saeed - American Journal of Operations Research, 2016 - scirp.org
Time-series-based forecasting is essential to determine how past events affect future events.
This paper compares the performance accuracy of different time-series models for oil prices …
This paper compares the performance accuracy of different time-series models for oil prices …
Analysis of the impact of clustering techniques and parameters on evolutionary-based hybrid models for forecasting electricity consumption
Electricity is undeniably one of the most crucial building blocks of high-quality life all over the
world. Like many other African countries, Nigeria is still grappling with the challenge of the …
world. Like many other African countries, Nigeria is still grappling with the challenge of the …
Enhanced fuzzy-filtered neural networks for material fatigue prognosis
Although fuzzy-filtered neural networks (FFNN) have been used in pattern classification
because of their unique characteristics in feature extraction, they usually have poor …
because of their unique characteristics in feature extraction, they usually have poor …
Time series forecasting using differential evolution-based ANN modelling scheme
S Panigrahi, HS Behera - Arabian Journal for Science and Engineering, 2020 - Springer
Over the past few decades, time series forecasting (TSF) has been predominantly performed
using different artificial neural network (ANN) models. However, the performance of ANN …
using different artificial neural network (ANN) models. However, the performance of ANN …
Evolutionary optimization of sparsely connected and time-lagged neural networks for time series forecasting
JP Donate, P Cortez - Applied Soft Computing, 2014 - Elsevier
Time series forecasting (TSF) is an important tool to support decision making (eg, planning
production resources). Artificial neural networks (ANNs) are innate candidates for TSF due …
production resources). Artificial neural networks (ANNs) are innate candidates for TSF due …