Related references
Note: Only part of the references are listed.Research on energy-saving optimization of commercial central air-conditioning based on data mining algorithm
Jie Yang et al.
ENERGY AND BUILDINGS (2022)
Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms
Badr Chegari et al.
ENERGY AND BUILDINGS (2021)
Predicting energy cost of public buildings by artificial neural networks, CART, and random forest
Marijana Zekic-Susac et al.
NEUROCOMPUTING (2021)
An artificial neural network (ANN) expert system enhanced with the electromagnetism-based firefly algorithm (EFA) for predicting the energy consumption in buildings
Dac-Khuong Bui et al.
ENERGY (2020)
Novel swarm-based approach for predicting the cooling load of residential buildings based on social behavior of elephant herds
Hossein Moayedi et al.
ENERGY AND BUILDINGS (2020)
Regression and independence based variable importance measure
Xinmin Zhang et al.
COMPUTERS & CHEMICAL ENGINEERING (2020)
Optimal modification of heating, ventilation, and air conditioning system performances in residential buildings using the integration of metaheuristic optimization and neural computing
Zhanjun Guo et al.
ENERGY AND BUILDINGS (2020)
Energy efficient building envelope using novel RBF neural network integrated affinity propagation
Yongming Han et al.
ENERGY (2020)
Artificial neural network structure optimisation for accurately prediction of exergy, comfort and life cycle cost performance of a low energy building
Ivan Garcia Kerdan et al.
APPLIED ENERGY (2020)
Energy performance prediction of vapor-injection air source heat pumps in residential buildings using a neural network model
Zhichao Wang et al.
ENERGY AND BUILDINGS (2020)
Predicting residential energy consumption using CNN-LSTM neural networks
Tae-Young Kim et al.
ENERGY (2019)
Building energy performance forecasting: A multiple linear regression approach
G. Ciulla et al.
APPLIED ENERGY (2019)
Support vector regression for predicting building energy consumption in southern China
Zhitong Ma et al.
INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS (2019)
A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction
Kangji Li et al.
ENERGY AND BUILDINGS (2018)
Design Optimization Considering Variable Thermal Mass, Insulation, Absorptance of Solar Radiation, and Glazing Ratio Using a Prediction Model and Genetic Algorithm
Yaolin Lin et al.
SUSTAINABILITY (2018)
Application of Multi-Objective Genetic Algorithm Based Simulation for Cost-Effective Building Energy Efficiency Design and Thermal Comfort Improvement
Yaolin Lin et al.
FRONTIERS IN ENERGY RESEARCH (2018)
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
Muhammad Waseem Ahmad et al.
ENERGY AND BUILDINGS (2017)
A relevant data selection method for energy consumption prediction of low energy building based on support vector machine
Subodh Paudel et al.
ENERGY AND BUILDINGS (2017)
A comparison of approaches to stepwise regression on variables sensitivities in building simulation and analysis
Mengchao Wang et al.
ENERGY AND BUILDINGS (2016)
The performance prediction of ground source heat pump system based on monitoring data and data mining technology
Lei Yan et al.
ENERGY AND BUILDINGS (2016)
Using multiple regression analysis to develop energy consumption indicators for commercial buildings in the US
Shideh Shams Amiri et al.
ENERGY AND BUILDINGS (2015)
Estimation models of heating energy consumption in schools for local authorities planning
Alfonso Capozzoli et al.
ENERGY AND BUILDINGS (2015)
Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy
Rishee K. Jain et al.
APPLIED ENERGY (2014)
Multi-model prediction and simulation of residential building energy in urban areas of Chongqing, South West China
Shazia Farzana et al.
ENERGY AND BUILDINGS (2014)
On the development of multi-linear regression analysis to assess energy consumption in the early stages of building design
Somayeh Asadi et al.
ENERGY AND BUILDINGS (2014)
Principal component analysis of the electricity consumption in residential dwellings
Demba Ndiaye et al.
ENERGY AND BUILDINGS (2011)
A data-driven approach for steam load prediction in buildings
Andrew Kusiak et al.
APPLIED ENERGY (2010)
Methodology to estimate building energy consumption using EnergyPlus Benchmark Models
Nelson Fumo et al.
ENERGY AND BUILDINGS (2010)
Applying support vector machine to predict hourly cooling load in the building
Qiong Li et al.
APPLIED ENERGY (2009)
Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks
Geoffrey K. F. Tso et al.
ENERGY (2007)