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The paper proposes a hybrid numerical-neural-network model developed based on the simulation of unheated and uncooled indoor temperature and humidity for buildings. This model is initiated with a numerical simulation and the output is then passed to a neural network for calibration. This approach utilizes both numerical and neural network models and it can analyze the influences of specific parameters on building performances without sacrificing accuracy and generalizability. An experimental...
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A predictive models were developed to determine the thermal comfort level for the academic classroom by using artificial neural networks (ANNs). The paper reports experimental and theoretical analysis on a problem of achieving a desired thermal comfort level. The proposed method focused on the classical artificial (feed forward) neural networks (ANN) and the time-series NARX feedback neural networks to achieve the thermal comfort assessed using the predicted mean vote (PMV). The field...
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The paper describes the application of a combined neuro-fuzzy model for indoor temperature dynamic and automatic regulation. The neural module of the model, an auto-regressive neural network with external inputs (NNARX), produces indoor temperature forecasts that are used to feed a fuzzy logic control unit that simulates switching the heating, ventilation and air conditioning (HVAC) system on and off and regulating the inlet air speed. To generate an indoor temperature forecast, the NNARX...
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The paper demonstrates the importance of feature selection for recurrent neural network applied to problem of one hour ahead forecasting of thermal comfort for office building heated by gas. Although the accuracy of the forecasting is similar for both the feed-forward and the recurrent network, the removal of features leads to accuracy reduction much earlier for the feed-forward network. The recurrent network can perform well even with less than 50% of features. This brings significant benefits...
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This paper presents the optimization of chillers operating using artificial neural networks and genetic algorithms. For the needs of generating chiller models, an artificial neural network was used, trained with data collected from an actual chiller. For that purpose the basic characteristics of artificial neural networks are shown as well as the process of making specific chiller models used for testing the results of application of the genetic algorithm in usage optimization. The optimal...
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This paper presents the optimization of chillers operating using artificial neural networks and genetic algorithms. For the needs of generating chiller models, an artificial neural network was used, trained with data collected from an actual chiller. For that purpose the basic characteristics of artificial neural networks are shown as well as the process of making specific chiller models used for testing the results of application of the genetic algorithm in usage optimization. The optimal...
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The actual European energy context highlights the building sector as one of the largest sectors of energy consumption. Consequently, the “Energy Performance of Buildings Directive”, adopted in 2002 and focusing on energy use in buildings, requires all the EU members to enhance their building regulations and to introduce energy certification schemes, with the aim of both reducing energy consumption and improving energy efficiency. That is why carrying out an energy performance diagnosis is...
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With the development of modern computer technology, a large amount of building energy simulation tools is available in the market. When choosing which simulation tool to use in a project, the user must consider the tool's accuracy and reliability, considering the building information they have at hand, which will serve as input for the tool. This paper presents an approach towards assessing building performance simulation results to actual measurements, using artificial neural networks (ANN)...
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The objective of this research is to investigate air flow distribution inside a light weight test room which is naturally ventilated using artificial neural networks. The test room is situated in a relatively sheltered location and is ventilated through adjustable louvres. Indoor air temperature and velocity are measured at four locations and six different levels. The outside local temperature, relative humidity, wind velocity and direction are also monitored. The collected data are used to...