Application of Artificial Intelligence in Industrial Process Modelling and Optimization

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Bol This Special Issue aims to enable readers to understand the latest technologies in artificial intelligence in industrial process modelling and optimization. The integration of artificial intelligence (AI) into industrial process modelling and optimization has emerged as a transformative force. This Special Issue aims to explore the application of AI approaches in industrial process modelling and optimization. This Special Issue collects research on AI and extraction of bioactive compounds, AI-driven maintenance optimization for natural gas-liquid pumps, sensor data imputation for industry reactor, domain-specific manufacturing analytics framework, machine learning predictions for various fibres, predicting and understanding emergency of pipeline incidents, energy-aware industrial internet of things, decision support system, biosensors for detecting food contaminants, intelligent modelling for sintering process, and intelligent monitoring for geological drilling processes. By sharing their practice and insights into the development and application of new AI technologies, the authors of the articles in this reprint have demonstrated the application value of artificial intelligence in industrial process modelling and optimization, thus providing readers with valuable ideological inspiration in this area.

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This Special Issue aims to enable readers to understand the latest technologies in artificial intelligence in industrial process modelling and optimization. The integration of artificial intelligence (AI) into industrial process modelling and optimization has emerged as a transformative force. This Special Issue aims to explore the application of AI approaches in industrial process modelling and optimization. This Special Issue collects research on AI and extraction of bioactive compounds, AI-driven maintenance optimization for natural gas-liquid pumps, sensor data imputation for industry reactor, domain-specific manufacturing analytics framework, machine learning predictions for various fibres, predicting and understanding emergency of pipeline incidents, energy-aware industrial internet of things, decision support system, biosensors for detecting food contaminants, intelligent modelling for sintering process, and intelligent monitoring for geological drilling processes. By sharing their practice and insights into the development and application of new AI technologies, the authors of the articles in this reprint have demonstrated the application value of artificial intelligence in industrial process modelling and optimization, thus providing readers with valuable ideological inspiration in this area.


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