To resolve the conflict between our desire for a good smoothing effect and desire to give
additional weight to the recent change, a grey accumulating generation operator that can …

An efficient multiwavelet-based time-varying modeling scheme is proposed for time–
frequency analysis (TFA) of electroencephalogram (EEG) data. In the new multiwavelet …

Abstract Extreme Learning Machine (ELM) has proved to be well suited to different kinds of
classification and regression problems. However, failing to seek deep representation of raw …

The focus of this paper is on application of advance data analytics and deep machine
learning methods for time series forecasting of injection/production data from subsurface …

It has been widely demonstrated in forecasting that combining forecasts can improve the
forecast performance compared to individual forecasts. However, how to select the optimal …

An algebraic approach for the selection of weight coefficients for weighted moving averaging
is proposed in this paper. The algebraic complexity of the sequence transformed by …

The goal to improve prediction accuracy and robustness of predictive models is quite
important for time series prediction (TSP). Multi-model predictions ensemble exhibits …

The aim of this book is to cover various aspects of the Production and Operations Analysis.
Apart from the introduction to basic understanding of each topic, the book will also provide …

Finite-time stabilization of the driven dissipative nonlinear pendulum is investigated in this
paper. First, asymptotic and nonasymptotic convergence towards stable and unstable orbits …

Recent studies propose that different dynamical systems, such as climate, ecological and
financial systems, among others, present critical transition points named to as tipping points …