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用于建筑能耗的 lightGBM （主题） – 11 – 所有数据库
Source: webvpn.ujs.edu.cn
Article summary:
1. A novel method for predicting large-scale building energy consumption based on a hybrid model of Prophet-LightGBM is presented.
2. The prediction accuracy is evaluated using RMSE and MAPE, and the results of the hybrid model are compared to those of single models.
3. Particle swarm optimization algorithm is used to calculate the corresponding coefficients of the hybrid model.
Article analysis:
The article provides a detailed description of a novel method for predicting large-scale building energy consumption based on a hybrid model of Prophet-LightGBM. The prediction accuracy is evaluated using RMSE and MAPE, and the results of the hybrid model are compared to those of single models. Particle swarm optimization algorithm is used to calculate the corresponding coefficients of the hybrid model.
The article appears to be reliable in terms of its content, as it provides an accurate description of the proposed method and its evaluation process. However, there are some potential biases that should be noted. For example, while the article does mention that this method can be used in energy conservation fields, it does not provide any evidence or data to support this claim. Additionally, while it mentions that particle swarm optimization algorithm is used to calculate coefficients for the hybrid model, it does not provide any details about how this algorithm works or why it was chosen over other algorithms that could have been used instead. Furthermore, while international patent classifications are provided at the end of the article, there is no discussion about how these classifications relate to or impact the proposed method in any way.
In conclusion, while this article appears to be reliable in terms of its content and descriptions, there are some potential biases that should be noted when evaluating its trustworthiness and reliability.