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In order to improve the control performance of airborne EO tracking systems, we develop a proposed variable universe control algorithm based on fuzzy reasoning. The algorithm combines a new fuzzy control algorithm with classic PID control algorithm and greatly improves the dynamic performance of the airborne EO tracking systems. The simulation results indicate that the adaptive fuzzy controller can ensure the precision of the system with better adaptability and robustness.

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In the remanufacturing industry, customer demands and product returns always display irregular intermittent patterns. It is very difficult to accurately forecast such customer demands and product returns. This paper conducts a comparative assessment of the forecasts derived by various methods, and evaluates the robustness of forecasting methodology through the demand data from a remanufacturing company. The results show the econometric methods are more accurate than the classic methods in terms of the mean squared error (MSE).