Data Mining (DM) is a useful technique to discover useful patterns which lead to large searches. This method offers a reliable treatment of all developmental phases from problemanddataunderstandingthroughdatapreprocessingtodeploymentoftheresults.DM playsanimportantroleinenergyefficiency.Theconstructionindustryhasnumeroussources informationtocompareandturnthemintobeneficialinformation.Artificialneuralnetworks (ANN), fuzzy logic (FL) and neuro fuzzy (NF) are used techniques. Although the ANN and FL have many advantages, they also have certain defects. NF enjoys the advantages of both ANN and FL. In this paper, by comparing these techniques present in articles from 2009 to 2017, we have introduced four advantages for NF technique and indicated that the second advantage has been paid less attention other ones. The results reveal that the NF method is moresuccessfulthanFLandANNforpredictingthethermalefficiencyofbuildings.However, NFwithalearningphaseprovestobecomputationallyheavyandtime-consuming,especially when the number of rules, the antecedents and the model delays are high. As a result, the proposed method, using nonlinear neural Model Predictive Controllers, is the best answer to thermal control strategies.
کلید واژگان :Energy efficiency·Thermal consumption·Construction industry·Artificial neural networks·Data Mining·Fuzzy logic·Neuro fuzzy
ارزش ریالی : 600000 ریال
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