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Research of Evaluation Indices for Short-Term Load Forecasting Errors for Optimizing the Operation of Cold Storage Air Conditioning Systems
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inferredcites →https://doi.org/10.1016/j.apenergy.2014.04.016openalex-extracted
Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques
inferredcites →https://doi.org/10.1016/j.apenergy.2017.12.051openalex-extracted
Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks
inferredcites →https://doi.org/10.1016/j.apenergy.2019.02.052openalex-extracted
Deep learning-based feature engineering methods for improved building energy prediction
inferredcites →https://doi.org/10.1016/j.apenergy.2021.117238openalex-extracted
Attention-based interpretable neural network for building cooling load prediction
inferredcites →https://doi.org/10.1016/j.applthermaleng.2017.09.007openalex-extracted
Effect of input variables on cooling load prediction accuracy of an office building
inferredcites →https://doi.org/10.1016/j.enbuild.2007.08.006openalex-extracted
Optimal design and operation of a thermal storage system for a chilled water plant serving pharmaceutical buildings
inferredcites →https://doi.org/10.1016/j.enbuild.2013.03.035openalex-extracted
Re-evaluation of building cooling load prediction models for use in humid subtropical area
inferredcites →https://doi.org/10.1016/j.enbuild.2016.12.016openalex-extracted
Input variable selection for thermal load predictive models of commercial buildings
inferredcites →https://doi.org/10.1016/j.enbuild.2017.03.042openalex-extracted
A study on energy performance of 30 commercial office buildings in Hong Kong
inferredcites →https://doi.org/10.1016/j.enbuild.2017.04.038openalex-extracted
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
inferredcites →https://doi.org/10.1016/j.enbuild.2017.11.002openalex-extracted
Model input selection for building heating load prediction: A case study for an office building in Tianjin
inferredcites →https://doi.org/10.1016/j.enbuild.2018.06.050openalex-extracted
A hybrid method of dynamic cooling and heating load forecasting for office buildings based on artificial intelligence and regression analysis
inferredcites →https://doi.org/10.1016/j.enbuild.2019.05.043openalex-extracted
Cooling load prediction and optimal operation of HVAC systems using a multiple nonlinear regression model
inferredcites →https://doi.org/10.1016/j.energy.2019.116085openalex-extracted
Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms
inferredcites →https://doi.org/10.1016/j.eswa.2008.01.039openalex-extracted
A simple and fast algorithm for K-medoids clustering
inferredcites →https://doi.org/10.1016/j.jclepro.2019.05.085openalex-extracted
Development and evaluation of cooling load prediction models for a factory workshop
inferredcites →https://doi.org/10.1016/j.rser.2017.04.095openalex-extracted
A review of data-driven building energy consumption prediction studies
inferredcites →https://doi.org/10.1016/j.solener.2017.04.064openalex-extracted
Towards a standardized procedure to assess solar forecast accuracy: A new ramp and time alignment metric
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