The Future of Industrial Design: Incorporating Water Energy Solutions for Green Manufacturing Using an Enhanced Adaptive Neuro-Fuzzy Inference System with Red Deer Algorithm
DOI:
https://doi.org/10.52152/4314Keywords:
Water Energy, Green Manufacturing, Sustainable Industrial Design, ANFIS, RDAAbstract
In response to the increasing demand for sustainable energy solutions in industrial design, this study proposes an Enhanced Adaptive Neuro-Fuzzy Inference System (ANFIS) optimized by the Red Deer Algorithm (RDA) to enhance the efficiency and adaptability of water-based energy systems for green manufacturing. The ANFIS model is employed to accurately predict and optimize complex nonlinear relationships in water energy utilization, while the RDA enhances parameter tuning to achieve superior system performance. Real-time adaptive control is realized through the proposed approach, minimizing operational costs and improving the reliability of energy systems. Key factors such as energy conversion efficiency, water flow dynamics, and environmental impacts are integrated into machine learning-driven predictive models for comprehensive system analysis. Comparative results demonstrate that the ANFIS-RDA framework significantly outperforms traditional optimization methods in energy savings and resource utilization, offering a transformative pathway towards carbon-negative, energy-efficient, and eco-friendly industrial production processes.
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