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Prediction of the surface roughness of wood for machining
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作者 Damjan Stanojevic Marija Mandic +1 位作者 gradimir danon Srdjan Svrzic 《Journal of Forestry Research》 SCIE CAS CSCD 2017年第6期1271-1273,共3页
The surface quality of solid wood is very important for its effective response in manufacturing processes. The effects of feed rate, cutting depth and rake angle on surface roughness and power consumption were investi... The surface quality of solid wood is very important for its effective response in manufacturing processes. The effects of feed rate, cutting depth and rake angle on surface roughness and power consumption were investigated and modeled. Neuro-fuzzy methodology was applied and shown that it could be useful, reliable and an effective tool for modeling the surface roughness of wood.Thus, the results of the present research can be successfully applied in the wood industry to reduce time, energy and high experimental costs. 展开更多
关键词 NEURO-FUZZY Forecasting Surface roughness WOOD PREDICTION
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