Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4961080 | Procedia Computer Science | 2017 | 5 Pages |
Abstract
Heating system is well known for its extremely complex mechanism, strong nonlinearity, large Delay, time-variance and uncertainty. We applied the BP Neural Network-Markov Prediction Model to the heat load prediction, which not only plays the BP Neural Network characteristic in accurate prediction, but also be capable of employing Markov model to predict volatility data precisely. This model has obvious advantage over other heat load prediction methods, and showed a better effect on heat load prediction.
Keywords
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Ling Xie,