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Ying Liu
Researcher at Dalian University of Technology
Publications - 21
Citations - 351
Ying Liu is an academic researcher from Dalian University of Technology. The author has contributed to research in topics: Scheduling (production processes) & Echo state network. The author has an hindex of 9, co-authored 21 publications receiving 286 citations.
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Real time prediction for converter gas tank levels based on multi-output least square support vector regressor
TL;DR: In this article, a multi-output least square support vector regressor is proposed, which considers not only the single fitting error of each tank level but also the combined one, and a particle swarm optimization is designed to determine the parameters of this model for the sake of improving the prediction accuracy.
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Prediction for noisy nonlinear time series by echo state network based on dual estimation
TL;DR: This study proposes an improved ESN model with noise addition, in which the additive noises describe the internal state uncertainty and the output uncertainty of the ESN, and proposes a nonlinear/linear dual estimation for this prediction model.
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Data-driven based model for flow prediction of steam system in steel industry
TL;DR: Experimental results using the real production data from Shanghai Baosteel show the validity and practicality of the proposed data-driven based model in providing scientific decision guidance for the steam system.
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Use of a quantile regression based echo state network ensemble for construction of prediction Intervals of gas flow in a blast furnace
TL;DR: In this article, a quantile regression-based echo state network ensemble (QR-ESNE) is modeled to construct the prediction intervals (PIs) of the blast furnace gas (BFG) generation.
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A two-stage method for predicting and scheduling energy in an oxygen/nitrogen system of the steel industry
TL;DR: Aiming at an oxygen/nitrogen system of a steel plant in China, a two-stage predictive scheduling method is proposed in this article for resolving the optimal energy decision-making problem.