A novel fuzzy neural network architecture, the approximate analogical reasoning based fuzzy CMAC (FCMAC-AARS), is proposed. AARS is incorporated into the fuzzy CMAC structure as it is conceptually clearer and more computationally efficient than the CRI and TVR fuzzy inference schemes. A prediction and trading framework has been proposed which exploits the price percentage oscillator (PPO) for input preprocessing and trading decision making. Numerical experiments conducted on real-life stock data confirm the validity of the design and the performance of the FCMAC-AARS system.
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