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100 # 2076
Evaluation of the level of technical infrastructure development
104 # 2249
Neural analysis of the ultrasonographic images in the intramuscular fat level content identification process – preliminary research
104 # 2248
The impact of the number of variables on the operation quality of neuron model for identifying mechanical damage of corn seeds
105 # 2258
Assessment of the selection of neural network used to show the occurrence and to determine quasiplateau range in volt-ampere-metric soil oxygenation measurements
105 # 2281
Modelling of functional statuses in the language of Bayesian networks
105 # 2275
Possibility of using radio networks in the MESH topology for wireless communications between farm machinery units
105 # 2264
Using artificial neural networks to assess apples ripeness degree
105 # 2273
Using neural networks (fbm) for modelling of the process involving mixing of two-component granular systems
107 # 2292
About the need to establish a Scientific Network in agroengineering environment
107 # 2333
Using the LAN/WAN network to control sprinkling machines in farms
109 # 2396
Implementation of diagnostic concluding for field spraying machine atomiser in real time
109 # 2402
Selection of heat pumps supported by artificial neural networks for single-family houses for complete and incomplete data sets
109 # 2379
Using neural networks to count insecticidal nematoda
113 # 2373
Innovative method for identifying selected qualitative characteristics of seeds using image analysis and artificial neural networks (ANN)
114 # 2507
Probabilistic models of spatial phenomena in agriculture
114 # 2519
Voltage fluctuations in rural electric power networks
115 # 2531
The Method used to predict time series using artificial neural networks
117 # 2598
Neural analysis of acoustic signal spectrum during determination of seed physical properties
117 # 2574
Neural classification of images showing dried vegetables
118 # 2610
An Artificial Neural Networks-based method for assessing technical and constructional modernity of farm tractors. Part I: Method guidelines
118 # 2632
Conversion of digital images into the form of teaching sets for the purposes of neural modelling
118 # 2611
Employing an author’s method for determining values of parameters for modern technical systems in ploughs and field spraying machines
118 # 2644
Using the ZigBee protocol for signal transmission in a dispersed measuring system
120 # 2695
Using artificial neural networks to describe flour permittivity
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
121 # 2747
Prediction of temperature changes for compost bed depending on aeration degree, carried out using artificial neural networks
122 # 2779
Modelling of complex bioagrotechnological systems – Modelling of reliability of complex bioagrotechnical systems
125 # 2888
Exploratory analysis and modeling of extrusion-cooking process of precooked wholewheat pasta products
125 # 2870
Modelling of food-processing with the use of artificial neural networks
126 # 2915
Basic rules of agricultural production process modelling
126 # 2904
Research methodology and preparation of learning datasets for neural networks identifying compost quality
129 # 2960
Modelling a protective action synthesis for the agricultural producution process
131 # 3064
Decision process modelling in the integrated agricultural production system
132 # 3097
Using neural networks in the process of mixing heterogeneous granular materials
136 # 3169
A concept of the questionnaire measurement of work safety culture
137 # 3207
Application of Kohonen map and a scatter diagram for identification of honey groups according to their electric features
149 # 3546
Investigation of the impact of water content and activity on electric properties of honey with the use of neuron networks
152 # 3613
Automatic indexing of information resources concerning agriculture in Polish
155 # 3664
Computer image analysis and artificial neuron networks in the qualitative assessment of agricultural products
155 # 3665
The use of neural image analysis in the identification of information encoded in a graphical form
19 # 996
Application of artificial neural networks to modelling of grain losses rising in a combine harvester
21 # 470
Application of neural networks in agriculture
35 # 911
A comparison of the results of modeling the mixing process of homogenous granular components using a stochastic model and the back propagation method in neural networks
35 # 882
An attempt to restrict computer crimes reiated to the Information flow in a produetion logistic system of a food company
35 # 881
Radial neural networks as a tool for estimation of heterogenity of the air flow through a stone store
41 # 560
Analysis of a settlement network as a basis to develop transformation plans for rural regions
45 Tom II # 1148
Application of fuzzy clustering to comparative analysis of a failure frequency of rural distribution networks
45 Tom II # 1152
Calculating of load in the rural low voltage power networks
61 # 1172
The HACCP system in dairy farms
61 # 1160
Using the neural network to estimate the air relative humidity on the basis of its temperature value
62 # 700
Analysis and classification of dried vegetables’ images with utilization of artificial neural networks
62 # 699
Assessment of effectiveness of the neural prediction based on selected methods exemplified by distribution of agricultural products
62 # 707
Genetic algorithms as a optimization tool applied in neural networks
62 # 711
Neural networks in modeling agricultural engineering processes with limited date file
62 # 706
Optimization of decision processes using chosen methods of artificial intelligence
62 # 705
The analysis of assumptions for modeling sugar beet crop with utilization of artificial neural networks
66 # 1278
Decision support system for machinery maintenance
67 # 931
Algorithm for identification of biological materials images
68 # 1371
Adequacy of the mathematical model and the models based on artificial neural networks to evaluating the kinetic strength of feed pellets
68 # 1367
An attempt to application of artificial neural network to evaluating technological advancement of agricultural machines
68 # 1366
Analysis of diagnostic parameter of the combine harvester gear assembly with the use of artificial neural network
68 # 1377
Application of the neural networks to diagnostics of fuel injection system in diesel engines
68 # 1360
Comparison of algorithms to education of unidirectional neural network, with time-lag, used to predicting values of atmospherical air temperature
68 # 1361
Comparison of the GRNN models developed by using neural network moduli of the MATLAB and STATISTICA packets
68 # 1393
Interactive educational system introducing into issue of artificial neural networks
68 # 1405
Prediction of solar radiation sums for solar energy conversion systems
68 # 1392
Prediction of sugar beet yields with the use of neural network techniques
68 # 1391
The wireless internet links as a method to activation of village areas - theory and practice
68 # 1395
Using the neural networks for prediction of biotechnological process parameters
70 # 1211
Image recognition with artificial neuron networks
70 # 1191
Spring Barley seeds density determination using artificial neuron networks
74 # 1255
Estimating the distribution of a granual molecule mixed using the Funnel-flow system
74 # 1239
Forecasting a hothouse cucumber price with the use of neuron networks
74 # 1263
Neural method of maximizing the values of the results of the simultaneous production of enzymes by yeast Kluyveromyces marxianus K-4
74 # 1262
Neural prediction of the results of the process of simultaneous biosynthesis of inulinase and invertase by Aspergillus niger under conditions of selected abiotic stresses
74 # 1272
The neurals model of daily prediction of solar radiation
81 # 207
Qualitaty models analysis neural networks on the example of the pellet quality
86 # 297
ethod of Forecasting technical parameter values of state--of-the-art farm machines. Part No I. Forecasting technique for farm tractor parameters
87 # 383
Application of Bayesian networks in modeling of agricultural production process
87 # 379
Dynamic bayesian networks as knowledge representation system
87 # 347
Modelling of operation process for engineering facilities using dynamic Bayesian networks
87 # 399
The analysis of production output in a family farm, carried out using a neural network
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 # 413
Interactive education system supporting the use of artificial neural networks in agriculture
88 # 460
Modeling the threshing process when using artificial neural networks
89 # 1471
Modelowanie zintegrowanych systemów ogrzewania na obszarach wiejskich
90 # 1794
Artificial neural networks for modelling ammonia emission from field applied slurry manure
90 # 1771
Determining the value of basic technical parameters for modern harvester combines with the use of ANN
90 # 1786
Emploment of neuron network for definition of effectiveness of work foresty shreder
90 # 1790
Neural Network as a tool enabling prediction of water demand in agricultu
90 # 1793
Prognose of the content of the sugar in roots of sugar-beet with utilization of the techniques regression and neural
90 # 1792
The analysis of possibilities of predictions of soil dislocations during ploughing using standard statistical methods as well as artificial neural networks
90 # 1791
The modern technology of the wireless networks WiMAX - IEEE 802.16 in the development of agricultural areas in the local and regional dimension
94 # 1887
Ocena energetyczno-ekonomiczna ogrzewania dendromasą
99 # 2031
Neural model allowing to locate defects in injection pumps
99 # 2030
Using of artificial neural networks to assess credit ratings of farmers – clients of a leasing company
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