Modeling, Implementing and Evaluation a Decision Support System Used for Choosing the Best HVAC System in The Buildings, Case Study in Iraq

Ahmed Ahmed - University of Baghdad, Baghdad, Iraq
Hussein Ali Salah - University of Baghdad, Baghdad, Iraq

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The life cycle cost of a building is affected by the heating, ventilation, and air conditioning (HVAC) system chosen by the Life Cycle Costs (LCC). Quality, constructability, appearance of the structure's interior and exterior, HVAC size and weight, and LCC are some of the criteria influencing the choice. Methods: To monitor a project's progress based on energy savings, standard measures such as cost variance (CV) and schedule variation have used an idea when tracking the performance of intelligent buildings. Also, as described in the article, this research compared the decision-making limits of Building Information Modelling (BIM) and (MCDM). Analysis: The conventional approach cannot reveal information regarding divergence from the expected level of performance. Based on the outcomes of the construction cost variables, the key finding was the observation of 12 efficient elements. Finding and Novelty: According to the R, a building's most valuable features are its (Energy Saving Features, Warranties, Budget, Protect Your Unit, SEER Ratings, and Home Square Footage). The findings of Actual value (AV) and planned value (PV) were significantly different, as noted by the Multi-Criteria Decision Maker (MCDM). The new method also makes it possible to track project costs and timetables more accurately. The paper will characterize the HVAC Decision Support System's architecture (HVACDSS). Also, a case study of action modeling is provided, and the preliminary findings are addressed. Six criteria characteristics are used by the HVACDSS technique by an analysis of building construction conducted using the WEKA mining tool (decision tree).


Data Mining; Multi-Criteria Decision Maker; WEKA mining tool; Decision Support System; Building Information Modelling; HVACDSS

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