Simulation of Hydrodynamic Pressure Bearing in Forestry Engineering Based On Multi Objective Function Optimization and Artificial Neural Network

In order to optimize the performance in the design process, simulation of hydrodynamicpressure bearing in forestry engineering is researched in this paper. The multi objective functionoptimization and artificial neural network is used in this paper to improve the accuracy andefficiency of simulation. This present study might be of special interests to designers who needa synchronized improvement of their sliding bearing performance as well as the reduction of thelubricant flow for their precision machines or high-speed devices and engines. However, themethod described within this paper successfully bridges the gap between the experimental andthe pragmatic and makes the optimization of journal bearings not only highly doable, but costefficient as well, combining technological aspects and artificial intelligence tools for functionminimization.