Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was...Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.展开更多
This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system （FES） is used in this study to control th...This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system （FES） is used in this study to control the swamp tracked vehicle＇s intelligent air cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-cushion system with total power consumption （PC）, cushion clearance height （CCH） and cushion pressure （CP）. Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure sensor, micro controller and battery pH sensor will be incorporated with the FES to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle＇s intelligent air-cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97.展开更多
基金National Natural Science Foundation of China(5 97740 0 5 )
文摘Fault recognition and coal seam thickness forecast are important problems in mineral resource prediction. Knowledge of multiple disciplines, which include mining engineering, mine geology, seismic prospecting etc, was used synthetically. Artificial neural network was combined with genetic algorithm to found integrated AI method of genetic algorithm artificial neural network(GA ANN). Fault recognition and coal seam thickness forecast were carried to completion by case studies. And the research results are satisfactory.
文摘This paper describes the unique structure of an intelligent air-cushion system of a hybrid electrical air-cushion track vehicle working on swamp terrain. Fuzzy expert system （FES） is used in this study to control the swamp tracked vehicle＇s intelligent air cushion system while it operates in the swamp peat. The system will be effective to control the intelligent air-cushion system with total power consumption （PC）, cushion clearance height （CCH） and cushion pressure （CP）. Ultrasonic displacement sensor, pull-in solenoid electromagnetic switch, pressure sensor, micro controller and battery pH sensor will be incorporated with the FES to investigate experimentally the PC, CCH and CP. In this study, we provide illustration how FES might play an important role in the prediction of power consumption of the vehicle＇s intelligent air-cushion system. The mean relative error of actual and predicted values from the FES model on total power consumption is found as 10.63 %, which is found to be alomst equal to the acceptable limits of 10%. The goodness of fit of the prediction values from the FES model on PC is found as 0.97.
