Abstract: This study presents a novel Adaptive boosting theory-Counterpropagetion neural network(ACPN) for solving forecasting problems. The boosting concept is integrated into the CPN learning algorithm for learning effectively. Compared with traditional CPN, the minimum training error and learning time in ACPN network fell about 96% and 44%. Furthermore, the curve of trainning error in ACPN presents downtrend basically and has less fluctuation.