This paper presents a residential water demand forecasting model using a back propagation neural network (BPNN) in the context of residential buildings in Korea. The water demand of a building demonstrates a highly complex and non-linear phenomenon reflecting such features as geographic and climatic and special types of buildings. We describe the impact of several potential determinant factors ...

Energy consumption in the residential sector is a complex socio-technical problem that can be explained using acombination of physical, demographic and behavioural characteristics of a house and its occupants. In this paper, byusing the energy consumption data for the residential sector of Shiraz in Iran, the effect of built area (BA) andoccupant number (Occ) on annual energy consumption (Ec) w...