Parametric coefficient genetic algorithm for domestic water consumption / Nurul Nadia Hani

Residential water consumption is influenced by various factors. Household routine parameters involving water-using appliances and fixtures such as number of times the occupants of a household took bath and shower, doing laundry, watering plants and other routines ultimately regulate the amount of residential's monthly water consumption. Accurately and effectively estimating and classifying the amount of residential water consumption is a tremendously challenging task as these parameters differ from one another with one household routine may be more influential and vice versa. Previous method which employs per capita water consumption (PCC) basically finding average of water consumption in different state of Malaysia which-is largely inaccurate. This research therefore proposes the employment of Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. This is accomplished by encoding the chromosome data in GA to incorporate the CMWC values to minimize the residential water consumption estimation error rates and subsequently enabling increased accuracy towards estimating and classifying the amount of residential water consumption. Using household's characteristic data and average monthly water consumption from 80 households in Seremban, it is discovered that CMWC values for bath and shower, flush toilets, personal hygiene, laundry by washing machine and food preparation are more influential towards the water consumption compared to laundry by handwashing, water plants, wash car and miscellaneous routines.