Prediction intervals for the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) via the LUBE method.- Analysis and Modeling of Information Security Information Security Systems in Industry 4.0.- Using Non-linear Integral Models in Automatic Control and Measurement Systems for Sensors’ Input Signals’ Recovery.- Neural Network Method and Algorithm for Document Detection Based on Signaling Analysis.- Using fuzzy probabilistic implication in Z-set based inference.- Accounting experience between fuzzy integral and Z-numbers.- The Impact of In-Store Environment on Purchase Intention in Supermarkets.- A recurrent method for structural-parametric identification of fuzzy neural networks.- Voltage Control System for Electrical Networks Based on Fuzzy Sets.- Algorithms for the Synthesis of Optimal Linear-Quadratic Stationary Controllers.

This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy.

This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.

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