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Accurate prediction and stabilization of blast furnace temperatures are crucial for optimizing the efficiency and productivity of steel production.
Learning representations by back-propagating errors
David E. Rumelhart, Geoffrey E. Hinton, and Ronald J. Williams · 1986
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Learning to forget: Continual prediction with lstm
Felix A Gers, Jürgen Schmidhuber, and Fred Cummins · 2000
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A predictive system for blast furnaces by integrating a neural network with qualitative analysis
Jian Chen · 2001
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Prediction of silicon content in blast furnace hot metal using partial least squares (PLS)
Tathagata Bhattacharya · 2005
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Use of PCI in blast furnaces
Anne M Carpenter · 2006
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Forecasting with many predictors
James H Stock and Mark W Watson · 2006
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Modelling on blast furnace process and innovative ironmaking technologies
Mansheng Chu, Jun-ichiro Yagi, and Fengman Shen · 2006
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Pattern recognition and machine learning (information science and statistics)
Christopher M Biship · 2007
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Nonlinear prediction of the hot metal silicon content in the blast furnace
Henrik Saxén and Frank Pettersson · 2007
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An application of prediction model in blast furnace hot metal silicon content based on neural network
Dong Qiu, De-Jiang Zhang, Wen You, Niao-Na Zhang, and Hui Li · 2009
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Quantum computation and quantum information
Michael A Nielsen and Isaac L Chuang · 2010
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Analysing blast furnace data using evolutionary neural network and multiobjective genetic algorithms
A Agarwal, U Tewary, F Pettersson, S Das, Henrik Saxen, and Nirupam Chakraborti · 2010
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Nonlinear modeling method applied to prediction of hot metal silicon in the ironmaking blast furnace
Antti Nurkkala, Frank Pettersson, and Henrik Saxen · 2011
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Data-driven time discrete models for dynamic prediction of the hot metal silicon content in the blast furnace—A review
Henrik Saxen, Chuanhou Gao, and Zhiwei Gao · 2012
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Quantum support vector machine for big data classification
Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
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Intelligent multivariable modeling of blast furnace molten iron quality based on dynamic AGA-ANN and PCA
Meng Yuan, Ping Zhou, Ming-liang Li, Rui-feng Li, Hong Wang, and Tian-you Chai · 2015
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Multivariable dynamic modeling for molten iron quality using online sequential random vector functional-link networks with self-feedback connections
Ping Zhou, Meng Yuan, Hong Wang, Zhuo Wang, and Tian-You Chai · 2015
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Deep learning
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio · 2016
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Quantum algorithms: an overview
Ashley Montanaro · 2016
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Process monitoring of iron-making process in a blast furnace with PCA-based methods
Bo Zhou, Hao Ye, Haifeng Zhang, and Mingliang Li · 2016
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Comparative performance evaluation of blast furnace flame temperature prediction using artificial intelligence and statistical methods
Yasin Tunckaya and Etem Köklükaya · 2016
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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Quantum neuron: an elementary building block for machine learning on quantum computers
Yudong Cao, Gian Giacomo Guerreschi, and Alán Aspuru-Guzik · 2017
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Analysis of the relationship between productivity and hearth wall temperature of a commercial blast furnace and model prediction
Kexin Jiao, Jianliang Zhang, Qinfu Hou, Zhengjian Liu, and Guangwei Wang · 2017
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Quantum computing in the NISQ era and beyond
John Preskill · 2018
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Quantum machine learning: a classical perspective
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, and Leonard Wossnig · 2018
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Supervised learning with quantum computers
Maria Schuld and Francesco Petruccione · 2018
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Prediction of the hot metal silicon content in blast furnace based on extreme learning machine
Haigang Zhang, Sen Zhang, Yixin Yin, and Xianzhong Chen · 2018
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Catboost: gradient boosting with categorical features support
Anna Veronika Dorogush, Vasily Ershov, and Andrey Gulin · 2018
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PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm, Josh Izaac, Maria Schuld, Christian Gogolin, M Sohaib Alam, et al · 2018
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Quantum machine learning in finance: Time series forecasting
Dimitrios Emmanoulopoulos and Sofija Dimoska · 2022
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Quantum methods for neural networks and application to medical image classification
Jonas Landman, Natansh Mathur, Yun Yvonna Li, Martin Strahm, Skander Kazdaghli, Anupam Prakash, and Iordanis Kerenidis · 2022
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Predictive modeling of the hot metal silicon content in blast furnace based on ensemble method
Dewen Jiang, Xinfu Zhou, Zhenyang Wang, Kejiang Li, and Jianliang Zhang · 2022
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Incremental data-uploading for full-quantum classification
Maniraman Periyasamy, Nico Meyer, Christian Ufrecht, Daniel D Scherer, Axel Plinge, and Christopher Mutschler · 2022
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Machine learning models for predicting and controlling the pressure difference of blast furnace
Dewen Jiang, Zhenyang Wang, Kejiang Li, Jianliang Zhang, and Song Zhang · 2023
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Furnace heat prediction and control model and its application to large blast furnace
Zhuang-nian Li, Man-sheng Chu, Zheng-gen Liu, Gen-ji Ruan, and Bao-feng Li · 2019
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Deep learning for blast furnaces: Skip-dense layers deep learning model to predict the remaining time to close tap-holes for blast furnaces
Keeyoung Kim, Byeongrak Seo, Sang-Hoon Rhee, Seungmoon Lee, and Simon S Woo · 2019
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Quantum algorithms for deep convolutional neural networks
Iordanis Kerenidis, Jonas Landman, and Anupam Prakash · 2019
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q-means: A quantum algorithm for unsupervised machine learning
Iordanis Kerenidis, Jonas Landman, Alessandro Luongo, and Anupam Prakash · 2019
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Supervised learning with quantum-enhanced feature spaces
Vojtěch Havlíček, Antonio D Córcoles, Kristan Temme, Aram W Harrow, Abhinav Kandala, Jerry M Chow, and Jay M Gambetta · 2019
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Quantum machine learning in feature hilbert spaces
Maria Schuld and Nathan Killoran · 2019
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Parameterized quantum circuits as machine learning models
Marcello Benedetti, Erika Lloyd, Stefan Sack, and Mattia Fiorentini · 2019
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Predictive modeling of the hot metal sulfur content in a blast furnace based on machine learning
Song Zhang, Dewen Jiang, Zhenyang Wang, Fei Wang, Jianliang Zhang, Yanbing Zong, and Shuigen Zeng · 2023
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Machine learning-based regression models for ironmaking blast furnace automation
Ricardo A Calix, Orlando Ugarte, Tyamo Okosun, and Hong Wang · 2023
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Artificial intelligence and machine learning for quantum technologies
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An exponentially-growing family of universal quantum circuits
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Attention mechanism-based deep learning for heat load prediction in blast furnace ironmaking process
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A hybrid quantum-classical model for stock price prediction using quantum-enhanced long short-term memory
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Variational measurement-based quantum computation for generative modeling
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Towards interpretable quantum machine learning via single-photon quantum walks
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Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
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