1997
DOI: 10.1016/s0888-613x(96)00118-1
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Knowledge-based fuzzy model for performance prediction of a rock-cutting trencher

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Cited by 53 publications
(15 citation statements)
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“…ANNs have been used to solve a wide variety of application in Geomechanics and Rock Engineering [8]. In the last few years, fuzzy inference systems (FISs) began to be used in the areas of rock mechanics and engineering geology [9][10][11][12]. According to Setnes et al [13], an interesting and perhaps the most attractive characteristics of fuzzy models compared with other conventional methods commonly used in geosciences.…”
Section: Introductionmentioning
confidence: 99%
“…ANNs have been used to solve a wide variety of application in Geomechanics and Rock Engineering [8]. In the last few years, fuzzy inference systems (FISs) began to be used in the areas of rock mechanics and engineering geology [9][10][11][12]. According to Setnes et al [13], an interesting and perhaps the most attractive characteristics of fuzzy models compared with other conventional methods commonly used in geosciences.…”
Section: Introductionmentioning
confidence: 99%
“…To move the cut soil in the case of cup tooth, gravitational force (F g ) should be calculated, while to get the total force (F T ), gravitational force should be added to resistive force (F s ) as, (6) and calculations provide F T = 196.842 N (for one cutting tooth).…”
Section: Fig 2 Working Principlementioning
confidence: 99%
“…The performance of a trencher [5,6] is expressed by its production (excavation) rate and by the bit consumption (due to wear and breakage). The production rate, i.e., the volume of material excavated per hour, affects the time necessary to excavate a trench.…”
Section: Introductionmentioning
confidence: 99%
“…The values of VAF closer to 100 % indicate low variability and consequently better prediction capabilities. The lower the RMSE, the better the model performs [62,63]. In ideal condition, the value of RMSE should be zero and value of CE should be unity.…”
Section: Model Performancementioning
confidence: 99%