District heater load forecasting based on machine learning and parallel CNN-LSTM attention

Prediction of residential district heating load based on machine learning: A case study

(2021) Ziqing Wei et al.   ENERGY

Predicting hourly heating load in a district heating system based on a hybrid CNN-LSTM model

(2021) Jiancai Song et al.   ENERGY AND BUILDINGS

Real-time power prediction approach for turbine using deep learning techniques

(2021) Lei Sun et al.   ENERGY

Building thermal load prediction through shallow machine learning and deep learning

(2020) Zhe Wang et al.   APPLIED ENERGY

Analysis of CO2 emission reduction contribution and efficiency of China’s solar photovoltaic industry: Based on Input-output perspective

(2020) Fang-rong Ren et al.   ENERGY

Heating load prediction based on attention long short term memory: A case study of Xingtai

(2020) Guixiang Xue et al.   ENERGY

Heat demand forecasting algorithm for a Warsaw district heating network

(2020) Teresa Kurek et al.   ENERGY

Predicting residential energy consumption using CNN-LSTM neural networks

(2019) Tae-Young Kim et al.   ENERGY

Multi-step ahead forecasting of heat load in district heating systems using machine learning algorithms

(2019) Puning Xue et al.   ENERGY

Thermal load forecasting in district heating networks using deep learning and advanced feature selection methods

(2018) Gowri Suryanarayana et al.   ENERGY

Field validation study of a time and temperature indexed autoregressive with exogenous (ARX) model for building thermal load prediction

(2017) Riasat Sarwar et al.   ENERGY

Electric load forecasting methods: Tools for decision making

(2009) Heiko Hahn et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Development and validation of regression models to predict monthly heating demand for residential buildings

(2008) Tiberiu Catalina et al.   ENERGY AND BUILDINGS