신재생에너지 활용에 따른 아파트에너지 절감방안 연구

• 영문명: A Study on Reducing the public electricity of the Renewable Energy Apartments
• 발행기관: 한국주거환경학회
• 저자명: 김선주(Kim, Sun-Ju) 김행종(Kim, Haeng-Jong)
• 간행물 정보: 『주거환경(한국주거환경학회논문집)』住居環境 제12권 제4호 (통권 제26호), 109~117쪽, 전체 9쪽
• 주제분류: 사회과학 > 지역개발
• 파일형태: PDF
• 발행일자: 2014.12.31

영문 초록

This study was per ㎡ apartments in renewable energy electricity saving measures were analyzed public. First, based on the results of multiple regression analysis of renewable energy per ㎡ apartments and analysis of public electricity-saving measures are as follows. The greater the number of households, the fewer the number of lifts, the more condominium, apartment hallway type more likely, a small number of years elapsed apartment (new apartment), the more electricity per unit area decreases the public was analyzed. Next, the hidden layer of the neural network analysis result, ㎡ party public electricity affects orientation is unknown. However, the accuracy of the model is high compared to the regression analysis,so take advantage of them when you can have a high predictive power. Neural network analysis of the relative influence of the independent variables are the size of Type of ownership>Corridor type>the uppermost stratum>the number of households>he number of Dong> the number of lifts>Heating Type>number of years>Administration Type.

목차

Ⅰ. 서 론

Ⅱ. 이론적 논의

Ⅲ. 실증분석

Ⅳ. 결론

키워드

신재생에너지 공용전기료 신경망모형 은닉층 Renewable Energy public electricity neural network analysis hidden layer