This paper presents a mini-review on our previous work presented in ref. [1-6] in which the neural networks (NNs) were used for estimating and then detecting the robot’s collisions with the human operator during the cooperation task. This review investigates and compares the designed NN...

Black-box algorithms with outstanding performance have been widely used in various fields; however, the lack of interpretability leads to great difficulties in troubleshooting and model improvement, hence severely confining the practical application. In response, we propose a framework that...

This article predicts the likelihood of a country being sanctioned by Basel for not adhering to anti-money laundering (AML) standards. Multiple machine learning algorithms were used to identify the strongest risk predictors, resulting in Basel sanctions against a country. In terms of sanction...

In recent years, the number of research in autonomous vehicles and Advance driver assistance system (ADAS) are increased to provide the user a safe driving experience. One of the most difficult maneuver like lane change need be predicted earlier to avoid collision between the vehicles and for...

Productivity and efficiency analyses have been indispensable tools for evaluating firms’ performance in the banking sector. In this context, the use of Artificial Neural Networks (ANNs) has been recently proposed in order to obtain a globally flexible functional form which is capable of...

This paper applies computational intelligence methods to exchange rate forecasting. In particular, it employs neural network methodology in order to predict developments of the Euro exchange rate versus the U.S. Dollar and the Japanese Yen. Following a study of our series using traditional as...

The Coronavirus Disease 2019 (COVID-19) continues to be a constant threat in 2022 and is important to design appropriate vaccination campaigns to face next pandemic impacts driven by new variants. This study develops a Machine Learning experiment that shows, between countries, a rapid reduction...

This paper initiates a non-linear fractional unit root test also known as autoregressive neural network–fractional integration (ARNN–FI) test. The test is based on a new multilayer perceptron of a neural network process which is applied in Yaya et al. (2021). Further, to investigate the...

The groundwater is among the most priceless resources. The continual depletion of water is among the major factors impacting the development of the economy and society. The utilization of the water will depend on how easily it can be reached. The problem of water scarcity is a result of...