This study presents an intuitionistic fuzzy prey-predator model with time delay, where several toxic substances from external sources contaminate the prey and predator species. The system consists of one prey and one predator, with the logistic growth of prey species and predation terms...

The rapid increase in online risks is a reflection of the exponential growth of Internet of Things (IoT) networks. Researchers have proposed numerous intrusion detection techniques to mitigate the harm caused by these threats. Enterprises use intrusion detection systems (IDSs) and intrusion...

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....

Concrete beams are commonly used in construction projects to provide structural support. Reinforcing these beams with steel and Glass Fiber Reinforced Polymer (GFRP) can increase their strength and durability. Steel reinforcement is a traditional method used for decades, while GFRP is a newer...

Seas, marine ecosystems, and coastal regions are crucial components of our environment. Numerous scientific strategies have been adopted to boost fisheries and aquaculture productivity. This study proposes a fuzzy-logic-based model to produce fisheries in India, which ranks fourth worldwide for...

The demand for rental bikes in urban areas fluctuates, leading to localized surpluses and shortages. To address this challenge, effective bike relocation strategies are essential for ensuring equitable distribution and maximizing customer satisfaction. This study aims to employ advanced machine...

The automotive industry faces a transformative time with the advent of advanced vehicle technologies and evolving consumer preferences. This research employs predictive modeling to forecast the adoption of Euro 6d and Euro 7 compliant vehicles, Battery Electric Vehicles (BEVs), and Autonomous...

A distributed machine learning technique called federated learning allows numerous Internet of Things (IoT) edge devices to work together to train a model without sharing their raw data. Internet of Vehicular Things (IoVT) are an important tool in smart cities for moving objects, such as knowing...

The flexible job shop scheduling problem (FJSSP) is a complex optimization challenge that plays a crucial role in enhancing productivity and efficiency in modern manufacturing systems, aimed at optimizing the allocation of jobs to a variable set of machines. This paper introduces an algorithm to...

Achieving a balance between economic, environmental, and social factors in supplier selection while prioritizing business continuity poses a considerable challenge. It is imperative to guarantee that selected suppliers adhere to sustainability and resilience requirements while supporting the...