Buchumschlag

Prediction of hydraulic resistance coefficient using an ensemble neural network algorithm

This study presents the development and testing of a computational algorithm based on ensemble learning of artificial neural networks for predicting the empirical hydraulic resistance coefficient known as the Chézy roughness coefficient in open channels. The input data for the model include hydrolog...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Datum:	2025
Hauptverfasser:	Khodnevych, Yaroslav, Korbutiak, Vasyl
Format:	Artikel
Sprache:	Ukrainisch
Veröffentlicht:	Kyiv National University of Construction and Architecture 2025
Schlagworte:	ensemble learning artificial neural networks bagging method prediction the Chézy roughness coefficient Python
Online Zugang:	https://es-journal.in.ua/article/view/351693
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!
Назва журналу:	Environmental safety and natural resources

Institution

Environmental safety and natural resources

Ähnliche Einträge

Data arrangements to train an artificial neural network within solving the tasks for calculating the Chézy roughness coefficient under uncertainty of parameters determining the hydraulic resistance to flow in river channels
von: Khodnevych, Yaroslav V., et al.
Veröffentlicht: (2022)

Do we need a more sophisticated multilayer artificial neural network to compute roughness coefficient?
von: Khodnevych, Yaroslav V., et al.
Veröffentlicht: (2023)

Еstimating the Chézy roughness coefficient as a characteristic of hydraulic resistance to flow in river channels: a general overview, existing challenges, and ways of their overcoming
von: Stefanyshyn, Dmytro V., et al.
Veröffentlicht: (2021)

Development and research of a modified convolutional neural network for malaria cell pattern recognition
von: Федорченко, Є. М., et al.
Veröffentlicht: (2023)

The problem of prediction of the transmission coefficient using neural networks with a limited quantity of data
von: Krysenko, Pavlo
Veröffentlicht: (2025)

APPLICATION OF AN ARTIFICIAL NEURAL NETWORK FOR PREDICTING THE THERMAL STATE OF AN AIR-SOIL HEAT EXCHANGER
von: Basok , B., et al.
Veröffentlicht: (2025)

Development and research of a genetic method for medical diagnosis of diabetes mellitus
von: Федорченко, Є. М., et al.
Veröffentlicht: (2021)

Method for political propaganda detection in internet content using neural network natural language processing tools
von: Krak, Iu.V., et al.
Veröffentlicht: (2024)

Adaptive maximum power point tracking using neural networks for a photovoltaic systems according grid
von: Sahraoui, H., et al.
Veröffentlicht: (2021)

PHOTOVOLTAIC GENERATION FORECASTING MODELS: CONCEPTUAL ENSEMBLE ARCHITECTURES
von: Matushkin, Dmytro
Veröffentlicht: (2024)

Complex systems in geophysics: methods of research and prediction of their behavior
von: Mykulyak, Serhiy
Veröffentlicht: (2025)

Application of neural networks in OLAP-systems
von: Nabibayeva, G.Ch.
Veröffentlicht: (2024)

New application of artificial neural network-based direct power control for permanent magnet synchronous generator
von: Akkouchi, K., et al.
Veröffentlicht: (2021)

A modern approach to calculating the abilities and capabilities of military units to perform tasks using artificial intelligence
von: Бойченко, А. В., et al.
Veröffentlicht: (2025)

Convolutional neural network model and software for classification of typical pests
von: Bezliudnyi, Y.S., et al.
Veröffentlicht: (2022)

Photovoltaic system faults diagnosis using discrete wavelet transform based artificial neural networks
von: Bengharbi, A. A., et al.
Veröffentlicht: (2022)

Yield prediction at field level
von: Kryvoshein, Oleksandr, et al.
Veröffentlicht: (2024)

A prediction of the frequency of non-periodic signals based on convolutional neural networks
von: Subbotin, S. A., et al.
Veröffentlicht: (2018)

Recurrent neural network model for music generation
von: Komarskiy, O.C., et al.
Veröffentlicht: (2022)

Neural networks’ learning process acceleration
von: Katerynych, L., et al.
Veröffentlicht: (2020)

A generalized methodology of sign language recognition on video streams based on neural networks and transformers
von: Кузнєцова, Н. В., et al.
Veröffentlicht: (2023)

Recurrent neural networks for the problem of improving numerical meteorological forecasts
von: Doroshenko, А.Yu., et al.
Veröffentlicht: (2023)

A Convolutional Neural Network Model and Software Tool for Classifying the Presence of a Medical Mask on a Human Face
von: Hryhorenko, Y.S., et al.
Veröffentlicht: (2023)

Practical content of the elements of petrophysical model of terrigenous sandstones — oil and gas reservoirs in neural networks, deep learning and regression methods
von: Vyzhva, Serhiy, et al.
Veröffentlicht: (2025)

Development of the intelligent control system of an unmanned car
von: Dakhno, N.B., et al.
Veröffentlicht: (2024)

Software package for adaptive training of robot controllers based on neural networks
von: Vitiuk, A.Y., et al.
Veröffentlicht: (2023)

Neural and Bayesian networks in the problem of credit risk analysis
von: Kuznietsova, N. V., et al.
Veröffentlicht: (2015)

Implementation of neural network based 2D seismic images super resolution approach
von: Noskov, Oleksii, et al.
Veröffentlicht: (2025)

Problems and perspectives of application of Artificial Neural Nets in power engineering. Part 2. Management
von: Voronovskiy, et al.
Veröffentlicht: (2007)

NEURAL NETWORK MODELING IN PROBLEMS OF PREDICTION MODES OF ELECTRICAL GRIDS
von: Moroz, A. N., et al.
Veröffentlicht: (2016)

Automatic development of deep neural networks for improving numerical meteorological forecast
von: Doroshenko, А.Yu., et al.
Veröffentlicht: (2024)

PREDICTION OF ENERGY EFFICIENCY OF SCREW COMPRESSORS IN AMMONIA REFRIGERATION SYSTEMS WITH FREQUENCY CONTROL USING A NEURAL NETWORK
von: Nitsak, Yaroslav, et al.
Veröffentlicht: (2026)

Overview and comparison of neural network models for diagnostics and quality control in the production of printed circuit boards
von: Верлань , А.А., et al.
Veröffentlicht: (2025)

Application of neuro evolution tools in automation of technical control systems
von: Doroshenko, А.Yu., et al.
Veröffentlicht: (2021)

An intelligent chatbot for evaluating the emotional colouring of a message and responding accordingly
von: Kobchenko, V. R., et al.
Veröffentlicht: (2024)

Fault diagnosis in a five-level multilevel inverter using an artificial neural network approach
von: Parimalasundar, E., et al.
Veröffentlicht: (2023)

Fault diagnosis of power converters in a grid connected photovoltaic system using artificial neural networks
von: Mimouni, A., et al.
Veröffentlicht: (2023)

Developing a semantic image model using machine learning based on convolutional neural networks
von: Andon, P.I., et al.
Veröffentlicht: (2020)

Characteristics for choice of models in the ansables classification
von: Barmak, O.V., et al.
Veröffentlicht: (2018)

Application of deep learning and computer vision frameworks for solving video context prediction problem
von: Voloshyn, D.
Veröffentlicht: (2018)