Since tremendous resources are consumed in the architecture, engineering, and
construction (AEC) industry, the sustainability and efficiency in this field have received …

This work aims to provide a broad overview of computational techniques belonging to the
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …

Spiking neural P (SNP) systems are a class of distributed and parallel neural-like computing
models that are inspired by the mechanism of spiking neurons and are 3rd-generation …

Determining the optimal number of hidden nodes and their proper initial locations are
essentially crucial before the wavelet neural networks (WNNs) start their learning process. In …

Wind is an essential, clean and sustainable renewable source of energy; however, wind
speed is stochastic and intermittent. Accurate wind power generation forecasts are required …

Efficient and reliable storage, analysis, and transmission of medical images are imperative
for accurate diagnosis, treatment, and management of various diseases. Since quantum …

Although the practicability of using wavelet neural networks (WNNs) in nonlinear function
approximation has been addressed extensively, selecting the optimal number of hidden …

Chaotic time series exist in nature, such as in the field of meteorology or physics, with
unpredictable features caused by their inherent high complexity and nonstationary motion …

To improve the prediction accuracy of chaotic time series, deep extraction of the system
evolutionary patterns is a key problem in modeling. In this paper, we propose a deep …

Reliability of spare parts inventory in the company is one of the most significant challenges
in the field of maintenance and repairs, but on the other hand, the liquidity crisis resulting …