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Learning from the behavior of the resident is essential in order to adapt the lightning system and to provide intelligent lighting control based on behavior patterns. Different homes have different conditions and habits which have to be taken into account for the intelligent system to be useful. However, with passage of time even deeply ingrained habits are subject to change. Therefore, a truly intelligent system has to respond to the changing and diverse environment. An intelligent lighting control system that employs artificial neural networks for on-line learning and adaptation and is based on resident's behavioural patterns is presented in this paper. In order to manage problems related to constant increase of data and dynamic environments, a group of algorithms have been improved by implementing a similarity threshold based data replacement algorithm that has been experimentally tested and compared with alternative algorithms. [ABSTRACT FROM AUTHOR]