Recent Innovations in Computer and Automation Engineering for Performance Improvement in the Steel Industry Production Chain: A Review by Crescenzo Pepe, Giorgia Farella, Giovanni Bartucci, Silvia Maria Zanoli

“…Efficiency enhancement of the involved sub-processes can serve as the basis of an effective roadmap for the industry’s decarbonization. Efficiency and performance can be investigated in terms of whole plants, parts of a plant, individual machines, or individual devices; in addition, efficiency and performance can be associated with different topics, e.g., energy, CO₂ emissions, sustainability, and product quality. …”
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A Triple-Optimized Extreme Learning Machine Model for Power Load Forecasting by Haoxiang Gao, Weixin Kang, Miao Fan

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Surface and subsurface characteristics of wire-electrical discharge machined Al-alloy and composite: a fundamental study on the role of machining variables by Gaurav Anand, Santanu Sardar, Satesh Sah, Ashim Guha, Ibrahim Albaijan, Debdulal Das

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Models, systems, networks in economics, engineering, nature and society by A.D. Stolyarov, V.V. Gordeev, V.I. Abramov

Machine learning-based spatio-temporal assessment of land use/land cover change in Barishal district of Bangladesh between 1988 and 2024 by Walida Zaman, H Rainak Khan Real

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Elastic Modulus Prediction of Ultra-High-Performance Concrete with Different Machine Learning Models by Chaohui Zhang, Peng Liu, Tiantian Song, Bin He, Wei Li, Yuansheng Peng

“…However, research systematically comparing different machine learning models under the same conditions, especially for ultra-high-performance concrete (UHPC), remains limited. …”
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Prediction of Optimum Operating Parameters to Enhance the Performance of PEMFC Using Machine Learning Algorithms by Arunadevi M, Karthikeyan B, Anirudh Shrihari, Saravanan S, Sundararaju K, R Palanisamy, Mohamed Awad, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Abdulrahman Al Ayidh, Hany S. Hussein, Mahmoud M. Hussein, Ahmed I. Omar

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Application of machine learning with gradient descent method for load forecasting: a performance analysis by Saroj Kumar Panda, Manoj Kumar Panda

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Analysis of surface roughness and machining performance of AZ91 magnesium alloy cut by WEDM by Levent Urtekin, Faik Yılan, İbrahim Baki Şahin, Kadir Gök

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Numerical Investigation on Vibration Performance of an Improved Switched Reluctance Machine with Double Auxiliary Slots by Zhengyuan Gao, Shanming Wang, Zhiguo An, Pengfei Sun

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Predictive modeling of electrochromic performance in ammonium metatungstate solutions using machine learning algorithms by Bocheng Jiang, Honglong Ning, Muyun Li, Rihui Yao, Chenxiao Guo, Yucheng Huang, Zijie Guo, Dongxiang Luo, Dong Yuan, Junbiao Peng

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Advanced evaluation of performance of machine learning models for soapstock splitting optimisation under uncertainty by Bartosz Szeląg, Krzysztof Barbusiński, Michał Stachura, Przemysław Kowal, Adam Kiczko, Eldon R. Rene

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Machine Learning-Based Carbon Compliance Forecasting and Energy Performance Assessment in Commercial Buildings by Aditya Ramnarayan, Felipe de Castro, Andres Sarmiento, Michael Ohadi

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The Effects of Cutting Pick Parameters on Cutting Head Performance in Tunneling–Bolting Combined Machines by Bo Ning, Mingzhu Li, Jinhua Zhang

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Performance evaluation of machine learning based voting classifier system for human activity recognition by Sonika Jindal, Monika Sachdeva, Alok K. S. Kushwaha

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Impact of Channel and System Parameters on Performance Evaluation of Frequency Extrapolation Using Machine Learning by Michael Neuman, Daoud Burghal, Andreas F. Molisch

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Using Machine Learning and Analytical Modeling to Predict Poly-Crystalline PV Performance in Jordan by Sinan S. Faouri, Salah Abdallah, Dana Helmi Salameh

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Machine Learning-Based Prediction Performance Comparison of Marshall Stability and Flow in Asphalt Mixtures by Muhammad Farhan Zahoor, Arshad Hussain, Afaq Khattak

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Remote Sensing of Grasslands: Performance Comparison of Radar and Optical Data in Machine Learning Classification by K. Christofi, C. Chrysostomou, I. Tsardanidis, M. Mavrovouniotis, G. Guerrisi, C. Kontoes, D. G. Hadjimitsis, D. G. Hadjimitsis

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Hybrid Symbolic Regression and Machine Learning Approaches for Modeling Gas Lift Well Performance by Samuel Nashed, Rouzbeh Moghanloo

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