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A B S T R A C T K E Y W O R DPurpose: The objective of this study is to develop a predictive model for calculating the amount of cooling load for the different setback temperatures during the setback period. An artificial neural network (ANN) is applied as a predictive model. The predictive model is designed to be employed in the control algorithm, in which the amount of cooling load for the different setback temperature is compared and works as a determinant for finding the most energy-efficient optimal setback temperature. Method: Three major steps were conducted for proposing the ANN-based predictive model -i) initial model development, ii) model optimization, and iii) performance evaluation. Result: The proposed model proved its prediction accuracy with the lower coefficient of variation of the root mean square errors (CVRMSEs) of the simulated results (Mi) and the predicted results (Si) under generally accepted levels. In conclusion, the ANN model presented its applicability to the thermal control algorithm for setting up the most energy-efficient setback temperature.ⓒ 2017 KIEAE Journal

The purpose of this study is to investigate the prior art based on deep learning to objectively calculate the metabolic rate which is the subjective factor for the PMV optimum control and to make a plan for future research based on this study. Methods: For this purpose, the theoretical and technical review and applicability analysis were conducted through various documents and data both in domestic and foreign. Results: As a result of the prior art research, the machine learning model of artificial neural network and deep learning has been used in various fields such as speech recognition, scene recognition, and image restoration. As a representative case, OpenCV Background Subtraction is a technique to separate backgrounds from objects or people. PASCAL VOC and ILSVRC are surveyed as representative technologies that can recognize people, objects, and backgrounds. Based on the results of previous researches on deep learning based on metabolic rate for occupational metabolic rate, it was found out that basic technology applicable to occupational metabolic rate calculation technology to be developed in future researches. It is considered that the study on the development of the activity quantity calculation model with high accuracy will be done.

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The management of indoor air quality is regarded highly important to health of modern people because more than 85% of their daily time stay in the indoor. There are a number of pollutants that affect the indoor air quality. Among them, particulate matter is one of the serious threats to the health of occupants. A window type ventilation system refers to a system, in which windows and ventilation systems are integrated, without interfering with the function and performance of the window. The purpose of this study is to evaluate the performance of windows with Bernoulli principle through Computational fluid dynamics analysis. As a result of the study, it is expected that the ventilation rate will be maximized due to the formation of a jet stream in the window where the Bernoulli principle is applied.