Enhanced Recurrent Neural Network for Reducing Carbon Foot Printing in Industry

Abstract

At present, green communication technology is receiving a significant research attention. The increasing research interest on green communication can also undermine the environment. Measuring the green communication intensity of various products, companies and processes is being carried out globally by following the rule that only the related effects are manageable, which is expressed as a carbon footprint. Green detections are having a direct, large-scale impact on carbon productions. The green initiatives can effectively reduce carbon productions by improving the energy efficiency. In summary, green discovery directly affect carbon production. This research work has attempted to reduce the carbon footprint energy by using Enhanced Recurrent Neural Network (ERNN). From an investment perspective, carbon footprint analysis can assist in evaluating a company’s overall and comparative performance. It can be used as a tool to manage and evaluate the performance of a company. Effective production management demonstrates the quality of operations and can provide a significant competitive advantage.