The future is unknown and uncertain, but there are ways to predict future events and reap the rewards safely. One such opportunity is the application of machine learning and artificial intelligence for stock market prediction. The stock market is turbulent, yet using artificial intelligence to...

Internet of Things (IoT) enabled networks are highly vulnerable to cyber threats due to insecure wireless communication, resource constraint architecture, different types of IoT devices, and a high volume of sensor data being transported across the network. Therefore, IoT-compatible...

Evaluating and selecting suitable suppliers involves several criteria, making it a complex and difficult problem for decision-makers. Several approaches have been developed to help achieve the best possible results for selecting the most suitable suppliers. Traditionally, multi-criteria...

Supplier selection is an important process in supply chain management that sets a foundation for a long-term partnership with suppliers that can greatly contribute to the success or failure of a business. This study aims to identify, validate and propose a comprehensive list of supplier...

Early detection of heart complications is highly effective in treating patients with cardiovascular diseases. Various machine learning methods have previously been used for the early detection of heart diseases. However, existing data-driven machine learning (ML) approaches fall short of...

The Internet of Things (IoT), cloud computing, and machine learning opened an opportunity for new smart systems. These technologies have triggered huge traffic and delay by continuously transmitting telemetry data to the cloud. IoT edge choice made decision-making closer to the environment,...

Spam emails are unwanted and unsolicited messages. The major problems in email spam detection methods are low detection rates and a high likelihood of false alarms. This study proposes a hybrid correlation-based deep learning model for email spam classification using a fuzzy inference system....

Feature selection identifies the relevant features and removes the irrelevant and redundant ones, intending to obtain the best-performing feature subset. This paper proposes a new feedback feature selection system with a reinforcement learning-based method to identify the best feature subset....

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses...

The growing demand for data-driven decision-making and the emergence of new business models has led to a rise in digital technologies. As a result, businesses have become more aware of the impact of their activities on the environment, including the production of digital technologies....