Building on a longitudinal dataset of 245 small firms covering the period of the Global
Financial Crisis, this study uses, in combination with fuzzy clustering, the N-State …

This article investigates the performance of three models-Autoregressive Integrated Moving
Average (ARIMA), Threshold Autoregressive Moving Average (TARMA) and Evidential …

Departing from the long debates on the role of faith/belief, recent interdisciplinary research
has turned to characterize the features of the psychophysical processes underlying …

Learning Classifier Systems (LCSs) are a kind of evolutionary machine learning algorithms
that provide highly adaptive components to deal with real world problems. They have been …

Abstract Random Permutation Set is a newly proposed method for handling uncertainty,
which considers the order of the elements in evidence. However, how to fuse RPSs …

In this article, data-driven self-calibration algorithms for the Internet of Things-based gas
concentration monitoring systems embedded with low-cost gas sensors are designed. The …

This study demonstrates a novel form of business analytics, respecting the quality of the data
available (allowing incompleteness in the data set), as well as engaging with the uncertainty …

The questions such as 'what is reality?'or 'what does reality mean?'are fundamental in neo-
platonic discussions. However, this crucial topic is not reflected only within the boundaries of …

Influence in Twitter has become recently a hotresearch topic since this micro-blogging
service is widelyused to share and disseminate information. Some users aremore able than …

Ignorance within non-cooperative games, reflected as a player's uncertain preferences
towards a game's outcome, is examined from a Bayesian point of view. This topic has had …