Research graph
References from Sensitivity analysis to reduce duplicated features in ANN training for district heat demand prediction. Local targets link to admitted publications; unresolved targets remain external evidence.
Calibration of building energy models for retrofit analysis under uncertainty
10.1016/j.enbuild.2011.12.029 · 2012 · External reference
Design and analysis of electrical energy storage demonstration projects on UK distribution networks
10.1016/j.apenergy.2014.09.027 · 2015 · External reference
Heating and cooling building energy demand evaluation; a simplified model and a modified degree days approach
10.1016/j.apenergy.2014.04.067 · 2014 · External reference
Prediction of optimum heating timing based on artificial neural network by utilizing BEMS data
10.1016/j.jobe.2018.11.012 · 2019 · External reference
Operational supply and demand optimisation of a multi-vector district energy system using artificial neural networks and a genetic algorithm
10.1016/j.apenergy.2018.11.001 · 2019 · External reference
A review on the prediction of building energy consumption
10.1016/j.rser.2012.02.049 · 2012 · External reference
A review on applications of ann and SVM for building electrical energy consumption forecasting
10.1016/j.rser.2014.01.069 · 2014 · External reference
The use of tuff stone cladding in buildings for energy conservation
10.1016/j.conbuildmat.2005.01.064 · 2006 · External reference
Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings
10.1016/j.enbuild.2015.11.045 · 2016 · External reference
Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks
10.1016/j.apenergy.2019.02.056 · 2019 · External reference
State of the art in building modelling and energy performances prediction: a review
10.1016/j.rser.2013.03.004 · 2013 · External reference
A review on the basics of building energy estimation
10.1016/j.rser.2013.11.040 · 2014 · External reference
Dynamic thermal performance of conventional and alternative building wall envelopes
10.1016/j.jobe.2018.11.002 · 2019 · External reference
A review of computer tools for analysing the integration of renewable energy into various energy systems
10.1016/j.apenergy.2009.09.026 · 2010 · External reference
Unresolved reference
External reference
Prediction of building energy consumption by using artificial neural networks
10.1016/j.advengsoft.2008.05.003 · 2009 · External reference
On the use of artificial neural networks to model household energy consumptions
10.1016/j.egypro.2017.08.149 · 2017 · External reference
Application of neural networks and sensitivity analysis to improved prediction of trauma survival
10.1016/s0169-2607(99)00046-2 · 2000 · External reference
Unresolved reference
2007 · External reference
A review of data-driven building energy consumption prediction studies
10.1016/j.rser.2017.04.095 · 2018 · External reference
10.1016/j.egyai.2020.100010 · 2020 · Admitted local publication
Prediction of residential building energy consumption: a neural network approach
10.1016/j.energy.2016.10.066 · 2016 · External reference
Artificial neural network modeling and analysis of photovoltaic/thermal system based on the experimental study
10.1016/j.enconman.2019.02.066 · 2019 · External reference
Unbiased sensitivity analysis and pruning techniques in neural networks for surface ozone modelling
10.1016/j.ecolmodel.2004.07.015 · 2005 · External reference
Using artificial neural networks for temporal and spatial wind speed forecasting in Iran
10.1016/j.enconman.2016.02.041 · 2016 · External reference
Artificial neural network optimisation for monthly average daily global solar radiation prediction
10.1016/j.enconman.2016.04.101 · 2016 · External reference
Forecasting diurnal cooling energy load for institutional buildings using artificial neural networks
10.1016/j.enbuild.2015.12.050 · 2016 · External reference
Analysis and validation of 24 hours ahead neural network forecasting of photovoltaic output power
10.1016/j.matcom.2015.05.010 · 2017 · External reference
A physical hybrid artificial neural network for short term forecasting of PV plant power output
10.3390/en8021138 · 2015 · External reference
Two-way interaction of input variables in the sensitivity analysis of neural network models
10.1016/j.ecolmodel.2005.11.008 · 2006 · External reference
Ranking importance of input parameters of neural networks
10.1016/s0957-4174(98)00041-4 · 1998 · External reference
Sensitivity analysis for minimization of input data dimension for feedforward neural network
1994 · External reference
Comparison of feature selection techniques for ann-based voltage estimation
10.1016/s0378-7796(99)00061-9 · 2000 · External reference
Feature selection for time series prediction–a combined filter and wrapper approach for neural networks
10.1016/j.neucom.2010.01.017 · 2010 · External reference
Demand forecasting for a mixed-use building using agent-schedule information with a data-driven model
10.3390/en13040780 · 2020 · External reference
Sensitivity and uncertainty analysis of complex models of disease transmission: an HIV model, as an example
1994 · External reference
Back-propagation neural networks for modeling complex systems
10.1016/0954-1810(94)00011-s · 1995 · External reference
Application of neural networks to modelling nonlinear relationships in ecology
10.1016/0304-3800(95)00142-5 · 1996 · External reference
Illuminating the ǣblack boxǥ: a randomization approach for understanding variable contributions in artificial neural networks
10.1016/s0304-3800(02)00064-9 · 2002 · External reference
Artificial neural networks as empirical models for estimating phytoplankton production
10.3354/meps139289 · 1996 · External reference
Use of some sensitivity criteria for choosing networks with good generalization ability
10.1007/bf02309007 · 1995 · External reference
Sensitivity evaluation of environmental models using fractional factorial experimentation
10.1016/0304-3800(95)00066-6 · 1996 · External reference
Plackett–Burman technique for sensitivity analysis of many-parametered models
10.1016/s0304-3800(01)00271-x · 2001 · External reference
Energy analysis of a building using artificial neural network: a review
10.1016/j.enbuild.2013.06.007 · 2013 · External reference
Unresolved reference
2016 · External reference
Unresolved reference
2017 · External reference
Learning representations by back-propagating errors
10.1038/323533a0 · 1986 · External reference
Analysis of learning rate and momentum term in backpropagation neural network algorithm trained to predict pavement performance
10.1016/s0965-9978(98)00071-4 · 1999 · External reference
Predicting electricity consumption in a building using an optimized back-propagation and Levenberg–Marquardt back-propagation neural network: case study of a shopping mall in china
10.1016/j.scs.2018.05.050 · 2018 · External reference
District heating network demand prediction using a physics-based energy model with a Bayesian approach for parameter calibration
10.3390/en12183408 · 2019 · External reference
District heat demand prediction using artificial neural network with data of sample building
2019 · External reference
10.1021/ac5018265
10.1021/ac5018265 · 2014 · External reference
Interval regression analysis by quadratic programming approach
10.1109/91.728436 · 1998 · External reference
Non-linear projection to latent structures revisited: the quadratic PLS algorithm
10.1016/s0098-1354(98)00283-x · 1999 · External reference
Non-linear projection to latent structures revisited (the neural network PLS algorithm)
10.1016/s0098-1354(99)00291-4 · 1999 · External reference
