首页|Studies from National Taipei University of Technology Further Understanding of A rtificial Intelligence (Artificial intelligence technique development for energy -efficient waste-to-energy: A case study of an incineration plant)
Studies from National Taipei University of Technology Further Understanding of A rtificial Intelligence (Artificial intelligence technique development for energy -efficient waste-to-energy: A case study of an incineration plant)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news reporting originating from Taipei, Taiwan, b y NewsRx correspondents, research stated, “The increasing heat value and complex ity of waste types in Taiwan’s incineration plants have led to reduced facility capacity and utilization rates.” Our news editors obtained a quote from the research from National Taipei Univers ity of Technology: “Traditional control systems struggle to manage rapid and irr egular fluctuations in waste heat values, often resulti ng in poor stability and prolonged response times. This study introduces an artificial intelligencebase d heat value prediction and combustion control system that enhances system effic iency and stability without equipment upgrades. The system predicts future waste heat trends, enabling precise operational adjustments. This results in shorter response times, improved combustion stability, and higher energy recovery effici ency, effectively replacing traditional control systems for more accurate waste management. Our system evaluates waste input uniformity to ensure consistent fee d and employs a Long Short-Term Memory neural network architecture to predict wa ste combustion heat values, greatly enhancing combustion stability. The model’s R2 value of 0.96 allows for optimized control parameters that reduce system resp onse times.”
National Taipei University of TechnologyTaipeiTaiwanAsiaArtificial IntelligenceEmerging TechnologiesMachine Learning
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