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We propose our framework to handle the relocation problem in the bicycle-sharing system. Our framework consists of two steps, demand forecasting step and relocation step. In demand forecasting step, we forecast the bicycle demand for each station. In relocation step, we propose an algorithm to optimize the relocation process to get the best benefit.
Now, I am going to talk about the contribution of this paper. We use multiple machine learning models such as regression, LSTM, statistics while other approaches use one type model or simple equations. We are focusing on Sejong city and are tyring to deploy our system to the Sejong bicycle-sharing system.
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