Improved water quality prediction accuracy and reduced computational complexity are vital
for ensuring a precise control over the water quality in intensive pearl breeding. This paper …

Load forecasting is a critical element of power system operation, involving prediction of the
future level of demand to serve as the basis for supply and demand planning. This paper …

In this article, a new multivariate radial basis functions neural network model is proposed to
predict the complex chaotic time series. To realize the reconstruction of phase space, we …

This study aims to examine the fundamental forces driving stock returns and volatility across
the international stock markets. Logistic regression analysis is used to investigate possible …

To replace costly and time‐consuming experimentation in laboratory, a novel solubility
prediction model based on chaos theory, self‐adaptive particle swarm optimization (PSO) …

Specifying the number and locations of the translation vectors for wavelet neural networks
(WNNs) is of paramount significance as the quality of approximation may be drastically …

Massive parallel arrays of discrete actuators are forceregulated robots that undergo
continuous motions despite being commanded through a large but finite number of states …

This study is proposed the application of hybridization model using Group Method of Data
Handling (GMDH) and Discrete Wavelet Transform (DWT) in time series forecasting. The …

В данной статье описана структура нечеткой вейвлет-нейронной сети (НВНС) для
прогнозирования временных рядов. НВНС создана на основе ряда набора нечетких …