Abstract
In this paper, machine learning is implemented in a simulated air-conditioning system based on evolutionary computing methods involving the use of classifier systems and genetic algorithms. The overall objective is to achieve a controller capable of selflearning from its own experience to arrive at the desired performance against a specified evaluation scheme. The simulated results show that the self-learning intelligent control strategy is successful and can be considered for further development for application to on-line computer control of air-conditioning systems. It is envisaged that efficient control of air-conditioning systems employing this methodology will help achieve substantial energy saving.
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