Inżynieria Rolnicza
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Francik Sławomir
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10 # 1488
Selection of trend function to forecasting technical-operation indices of agricultural machines
107 # 2300
Indexes that characterise farm tractors suitability for operation in mountainous terrains
109 # 2385
Analysis of force destroying walnut cover
109 # 2393
Neural model of changes in water content in willow chips during convection drying
109 # 2394
Neural model of temperature changes during convection drying of energy willow chips
115 # 2531
The Method used to predict time series using artificial neural networks
115 # 2560
The modelling of complex production system – relation model of fruit farm
118 # 2610
An Artificial Neural Networks-based method for assessing technical and constructional modernity of farm tractors. Part I: Method guidelines
118 # 2611
Employing an author’s method for determining values of parameters for modern technical systems in ploughs and field spraying machines
121 # 2731
Method allowing to assess technical and constructional modernity of farm tractors with the use of Artificial Neural Networks. Part II: Neural models for farm tractor modernity assessment
121 # 2732
Method allowing to assess technical and constructional modernity of farm tractors with the use of Artificial Neural Networks. Part III: Method application examples
123 # 2804
SSN model for determination of the force destroying the walnut cover
125 # 2861
Analysis of the use of decision support systems by farmers
19 # 996
Application of artificial neural networks to modelling of grain losses rising in a combine harvester
19 # 995
Method of forecasting in agricultural engineering with the use of artificial neural networks
31 # 1677
Model of dry substance decreases in process of onion heat treatment
31 # 1662
Possibility of enlargement of technical prognoses exactitude obtained by use ofartificial neuronal net
52 # 784
Evaluation of machines modern features upon the example of tractors
66 # 1292
Tendencies of changes in parameters of farm tractors
68 # 1367
An attempt to application of artificial neural network to evaluating technological advancement of agricultural machines
70 # 1191
Spring Barley seeds density determination using artificial neuron networks
74 # 1239
Forecasting a hothouse cucumber price with the use of neuron networks
86 # 297
ethod of Forecasting technical parameter values of state--of-the-art farm machines. Part No I. Forecasting technique for farm tractor parameters
86 # 298
Method of Forecasting technical parameter values of state-of-the-art farm machines. Part II. Neural models for setting out farm tractor parameters
87 # 367
Utilization of ANN to determine wheat grain hardness
88 # 461
Analysis of celery hardness during drying process
88 # 427
Hardness model for wheat caryopsises using Artificial Neural Networks
88 # 462
Modeling drying shrinkage for selected root vegetables using neural networks
90 # 1771
Determining the value of basic technical parameters for modern harvester combines with the use of ANN
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