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Forecasting Water Quality Index in Groundwater Using Artificial Neural Network

Energies (Basel), 2021-09, Vol.14 (18), p.5875

2021

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Machine Learning Methods to Forecast the Concentration of PM10 in Lublin, Poland

Energies (Basel), 2022-09, Vol.15 (17), p.6428

2022

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Evaluation of High-Frequency Measurement Errors from Turned Surface Topography Data Using Machine Learning Methods

Materials, 2024-04, Vol.17 (7), p.1456

2024

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Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks

Advances in science & technology, research journal, 2024-01, Vol.18 (1), p.231-243

2024

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Improved Prediction of the Higher Heating Value of Biomass Using an Artificial Neural Network Model Based on the Selection of Input Parameters

Energies (Basel), 2023-05, Vol.16 (10), p.4162

2023

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Review of Magnesium Wheel Types and Methods of Their Manufacture

Materials, 2024-01, Vol.17 (3), p.584

2024

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Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys

Materials, 2022-04, Vol.15 (9), p.3184

2022

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The use of fuzzy logic in the decision-making process regarding the use of outsourcing in companies

Journal of Modern Science, 2023-12, Vol.54 (5), p.66-82

2023

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The Effect of Abrasive Waterjet Machining Parameters on the Condition of Al-Si Alloy

Materials, 2020-07, Vol.13 (14), p.3122

2020

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Using Fuzzy Logic to Make Decisions Based on Data From CRM Systems

Advances in science & technology, research journal, 2023-10, Vol.17 (5), p.269-279

2023

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Trochoidal Milling and Neural Networks Simulation of Magnesium Alloys

Materials, 2019-06, Vol.12 (13), p.2070

2019

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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

Materials, 2023-04, Vol.16 (9), p.3384

2023

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Identification of an Arbitrary Shape Obstacle of Scattering Problem Using Near Field Data

Advances in science & technology, research journal, 2024-11, Vol.18 (7), p.396-405

2024

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Implementing AI Collaborative Robots in Manufacturing – Modeling Enterprise Challenges in Industry 5.0 with Fuzzy Logic

Advances in science & technology, research journal, 2024-11, Vol.18 (7), p.229-238

2024

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Management Decision Making in a Retail Establishment Using Machine Learning Methods

Advances in science & technology, research journal, 2024-11, Vol.18 (7), p.460-474

2024

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Optimizing the Neural Network Loss Function in Electrical Tomography to Increase Energy Efficiency in Industrial Reactors

Energies (Basel), 2024-01, Vol.17 (3), p.681

2024

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Research, Modelling and Prediction of the Influence of Technological Parameters on the Selected 3D Roughness Parameters, as Well as Temperature, Shape and Geometry of Chips in Milling AZ91D Alloy

Materials, 2022-06, Vol.15 (12), p.4277

2022

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Risk awareness in making consumer online decisions during Covid-19 pandemichttps://www.editorialsystem.com/editor/jms/js/article/176172

Journal of Modern Science, 2023-12, Vol.54 (5), p.43-65

2023

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Effect of the AWJM Method on the Machined Surface Layer of AZ91D Magnesium Alloy and Simulation of Roughness Parameters Using Neural Networks

Materials, 2018-10, Vol.11 (11), p.2111

2018

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Comparative Analysis of Machine Learning Methods for Predicting Energy Recovery from Waste

Applied sciences, 2024-04, Vol.14 (7), p.2997

2024

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Predicting Food Consumption to Reduce the Risk of Food Insecurity in Kazakhstan

Economies, 2024-01, Vol.12 (1), p.11

2024

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2D Geometric Surface Structure ANN Modeling after Milling of the AZ91D Magnesium Alloy

Advances in science & technology, research journal, 2022-04, Vol.16 (2), p.131-140

2022

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Using Business Process Model and Notation 2.0 to Deploy Cobots in a Manufacturing System – Case Study

Advances in science & technology, research journal, 2024-11, Vol.18 (7), p.150-162

2024

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Modelling the properties of aerated concrete on the basis of raw materials and ash-and-slag wastes using machine learning paradigm

Frontiers in materials, 2024-10, Vol.11

2024

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Effect of technological parameters on vibration acceleration in milling and vibration prediction with artificial neural networks

MATEC Web of Conferences, 2019, Vol.252, p.3015

2019

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Forecasting Water Quality Index in Groundwater Using Artificial Neural Network

Machine Learning Methods to Forecast the Concentration of PM10 in Lublin, Poland

Evaluation of High-Frequency Measurement Errors from Turned Surface Topography Data Using Machine Learning Methods

Prediction of Buckling Behaviour of Composite Plate Element Using Artificial Neural Networks

Improved Prediction of the Higher Heating Value of Biomass Using an Artificial Neural Network Model Based on the Selection of Input Parameters

Review of Magnesium Wheel Types and Methods of Their Manufacture

Influence of the Tool Cutting Edge Helix Angle on the Surface Roughness after Finish Milling of Magnesium Alloys

The use of fuzzy logic in the decision-making process regarding the use of outsourcing in companies

The Effect of Abrasive Waterjet Machining Parameters on the Condition of Al-Si Alloy

Using Fuzzy Logic to Make Decisions Based on Data From CRM Systems

Trochoidal Milling and Neural Networks Simulation of Magnesium Alloys

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

Identification of an Arbitrary Shape Obstacle of Scattering Problem Using Near Field Data

Implementing AI Collaborative Robots in Manufacturing – Modeling Enterprise Challenges in Industry 5.0 with Fuzzy Logic

Management Decision Making in a Retail Establishment Using Machine Learning Methods

Optimizing the Neural Network Loss Function in Electrical Tomography to Increase Energy Efficiency in Industrial Reactors

Research, Modelling and Prediction of the Influence of Technological Parameters on the Selected 3D Roughness Parameters, as Well as Temperature, Shape and Geometry of Chips in Milling AZ91D Alloy

Risk awareness in making consumer online decisions during Covid-19 pandemichttps://www.editorialsystem.com/editor/jms/js/article/176172

Effect of the AWJM Method on the Machined Surface Layer of AZ91D Magnesium Alloy and Simulation of Roughness Parameters Using Neural Networks

Comparative Analysis of Machine Learning Methods for Predicting Energy Recovery from Waste

Predicting Food Consumption to Reduce the Risk of Food Insecurity in Kazakhstan

2D Geometric Surface Structure ANN Modeling after Milling of the AZ91D Magnesium Alloy

Using Business Process Model and Notation 2.0 to Deploy Cobots in a Manufacturing System – Case Study

Modelling the properties of aerated concrete on the basis of raw materials and ash-and-slag wastes using machine learning paradigm

Effect of technological parameters on vibration acceleration in milling and vibration prediction with artificial neural networks

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