On the neurocomputing based intelligent simulation of tractor fuel efficiency parameters
作者： S.M. Shafaei , M. Loghavi , S. Kamgar
DOI: 10.1016/J.INPA.2018.02.003
关键词:
摘要: Abstract Tractor fuel efficiency parameters (TFEPs) (fuel consumption per working hour (FCWH), tilled area (FCTA) and specific volumetric (SVFC)) were intelligently simulated. A neurocomputing based simulation strategy (adaptive neuro-fuzzy inference system (ANFIS)) was used to simulate the TFEPs. comparison also made between results of best ANFIS environment those another strategy, artificial neural network (ANN). Field experiments conducted at plowing depths 10, 20 30 (cm) forward speeds 2, 4 6 (km/h) using a disk plow implement. Statistical descriptor applied evaluate environments indicated that both ANN able perfectly predict However, comprehensive with simple architecture 2-6-3 easier use than three individual environments. The revealed simultaneous increase speed from 2 6 (km/h) depth 10 30 (cm) led nonlinear increment FCWH 5.29 14.89 (L/h) decrement SVFC 2.95 0.67 (L/h kW). Meanwhile, along resulted in FCTA 28.13 12.24 (L/ha). Interaction on congruent, while it incongruent for FCTA. It is suggested employ developing future planning schemes tractor during tillage operations.
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