Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm

This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.