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Monika Kulisz
Monika Kulisz
Katedra Organizacji Przedsiębiorstwa, Politechnika Lubelska
Verified email at pollub.pl
Title
Cited by
Cited by
Year
Forecasting water quality index in groundwater using artificial neural network
M Kulisz, J Kujawska, B Przysucha, W Cel
Energies 14 (18), 5875, 2021
702021
Trochoidal milling and neural networks simulation of magnesium alloys
I Zagórski, M Kulisz, M Kłonica, J Matuszak
Materials 12 (13), 2070, 2019
442019
Prediction of municipal waste generation in Poland using neural network modeling
M Kulisz, J Kujawska
Sustainability 12 (23), 10088, 2020
402020
Effect of the AWJM method on the machined surface layer of AZ91D magnesium alloy and simulation of roughness parameters using neural networks
I Zagórski, M Kłonica, M Kulisz, K Łoza
Materials 11 (11), 2111, 2018
342018
Machine learning methods to forecast the concentration of PM10 in Lublin, Poland
J Kujawska, M Kulisz, P Oleszczuk, W Cel
Energies 15 (17), 6428, 2022
302022
Using an LSTM network to monitor industrial reactors using electrical capacitance and impedance tomography-a hybrid approach
G Kłosowski, T Rymarczyk, K Niderla, M Kulisz, Ł Skowron, M Soleimani
Eksploatacja i Niezawodność 25 (1), 2023
292023
Properties of the surface layer after trochoidal milling and brushing: experimental study and artificial neural network simulation
M Kulisz, I Zagórski, J Matuszak, M Kłonica
Applied Sciences 10 (1), 75, 2019
282019
Application of artificial neural network (ANN) for water quality index (WQI) prediction for the river Warta, Poland
M Kulisz, J Kujawska
Journal of Physics: conference series 2130 (1), 012028, 2021
252021
The effect of abrasive waterjet machining parameters on the condition of Al-Si alloy
M Kulisz, I Zagórski, J Korpysa
Materials 13 (14), 3122, 2020
242020
Artificial neural network modelling of vibration in the milling of AZ91D alloy
I Zagórski, M Kulisz, A Semeniuk, A Malec
Advances in Science and Technology. Research Journal 11 (3), 261-269, 2017
232017
Polish consumers’ response to social media eco-marketing techniques
A Bojanowska, M Kulisz
Sustainability 12 (21), 8925, 2020
182020
Analysis of Vibration, Deflection Angle and Surface Roughness in Water-Jet Cutting of AZ91D Magnesium Alloy and Simulation of Selected Surface Roughness Parameters Using ANN
K Biruk-Urban, I Zagórski, M Kulisz, M Leleń
Materials 16 (9), 3384, 2023
172023
Consumer‘s behaviour regarding cashless payments during the COVID-19 pandemic
M Kulisz, A Bojanowska, K Toborek
University of Piraeus. International Strategic Management Association, 2021
172021
Matrix profile implementation perspective in Industrial Internet of Things production maintenance application
J Pizoń, M Kulisz, J Lipski
Journal of Physics: Conference Series 1736 (1), 012036, 2021
132021
Analysis and prediction of the impact of technological parameters on cutting force components in rough milling of AZ31 magnesium alloy
M Kulisz, I Zagórski, A Weremczuk, R Rusinek, J Korpysa
Archives of Civil and Mechanical Engineering 22 (1), 1, 2021
122021
Comparative Analysis of Machine Learning Methods for Predicting Energy Recovery from Waste
M Kulisz, J Kujawska, M Cioch, W Cel, J Pizoń
Applied Sciences 14 (7), 2997, 2024
112024
Prediction of buckling behaviour of composite plate element using artificial neural networks
K Falkowicz, M Kulisz
Advances in Science and Technology. Research Journal 18 (1), 2024
112024
Artificial neural network modelling of cutting force components in milling
I Zagórski, M Kulisz, A Semeniuk
ITM Web of Conferences 15, 02001, 2017
112017
Optimizing the neural network loss function in electrical tomography to increase energy efficiency in industrial reactors
M Kulisz, G Kłosowski, T Rymarczyk, J Słoniec, K Gauda, W Cwynar
Energies 17 (3), 681, 2024
82024
Improved prediction of the higher heating value of biomass using an artificial neural network model based on the selection of input parameters
J Kujawska, M Kulisz, P Oleszczuk, W Cel
Energies 16 (10), 4162, 2023
82023
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