Good health is extremely important for athletes who engage in strenuous physical activities, such as football. They must develop a healthy body before participating in vigorous activities and competitions. Although researchers have presented a wide range of analytical approaches emphasizing...

Methods based on artificial neural network (ANN) or deep neural network (DNN) applications have been proposed to predict job cycle time effectively. However, the predicting mechanism of ANNs (or DNNs) is often difficult to understand and communicate. This problem has hindered their acceptability...

Healthcare fraud is intentionally submitting false claims or producing misinterpretation of facts to obtain entitlement payments. Thus, it wastes healthcare financial resources and increases healthcare costs. Subsequently, fraud poses a substantial financial challenge. Therefore, supervised...

Despite the growth in CRM installations, e-CRM projects still have a significant failure rate, even after substantial investments in CRM technology. High rates of failure mean that the current requirements for developing and designing CRM need to be analysed. It's not enough to just look at data...

The study's objective is to check whether the predictive power of Machine Learning Techniques is better than Logistic Regression in predicting the bankruptcy of firms and that the same predictive power of ascertaining bankruptcy improves when a proxy for uncertainty is added to the model as a...

In the euro area, monetary policy is conducted by a single central bank for 20 member countries. However, countries are heterogeneous in their economic development, including their inflation rates. This paper combines a New Keynesian model and a neural network to assess whether the European...

Background: Over the past decade, the potential advantages of employing deep learning models and leveraging auxiliary data in data-driven end-to-end (E2E) frameworks to enhance inventory decision-making have gained recognition. However, current approaches predominantly rely on feed-forward...

This paper identifies the most significant learning factors impacting undergraduate academic performance using artificial neural networks (ANNs) and controlled student data collection. As higher education becomes increasingly common and important, finding the best ways to help students optimize...