The comparison of neural network and case-based reasoning in cost estimating modeling of remanufacturing hydraulic cylinder

摘要

The current research sets the BP neural network and CBR as factors of engineering machinery hydraulic cylinder remanufacturing cost prediction. Take the differences between the new product manufacturing and remanufacturing and the process of hydraulic cylinder remanufacturing into consideration, we extract 10 feature factors and case attributes and establish BP prediction model and CBR model respectively. The comparison of two models indicates that the BP model and CBR model are both feasible ways to estimate the manufacturing cost of engineering machinery hydraulic cylinder and the BP model is more accurate. Study provides a feasible method for engineering machinery hydraulic cylinder remanufacturing production cost prediction, as well as effective measures for remanufacturing economic efficiency.