Application of machine learning methods to predict soil moisture based on meteorological and atmospheric data DOI Creative Commons
В С Тынченко,

Oksana Kukartseva,

Ksenia Degtyareva

et al.

BIO Web of Conferences, Journal Year: 2024, Volume and Issue: 130, P. 02003 - 02003

Published: Jan. 1, 2024

The purpose of this study was to develop and evaluate models for predicting soil moisture based on data from meteorological conditions particle concentrations in the air. Two machine learning methods were used work: random forest linear regression. results showed that model achieved 94% accuracy, while regression 92% accuracy. Air temperature, air humidity concentration particles turned out be important factors affecting moisture. Both offered good predictive capabilities, with an emphasis ability a adapt complex nonlinear dependencies, interpret results. developed can useful optimizing agricultural processes, managing land resources environmental monitoring.

Language: Английский

Data-Driven Strategies for Optimizing Albania’s Utilization of Renewable Energy Sources from Urban Waste: Current Status and Future Prospects DOI Creative Commons
Sonila Vito, Ilirjana Boci, Mohammad Gheibi

et al.

World, Journal Year: 2024, Volume and Issue: 5(2), P. 258 - 275

Published: April 26, 2024

Albania is now implementing a range of steps as part its journey towards European Union integration, based on agreements that have been achieved. Key to these initiatives the extensive adoption circular economy concepts through comprehensive waste management systems. This collaboration systematically measures align with fundamental principles hierarchy. wants lead in waste-to-energy conversion exploration by focusing trash minimization, reuse, recycling, and energy generation from residual waste. Although there has notable advancement, especially aligning laws EU requirements, are practical obstacles, execution projects. The challenges involve need for effective segregation, higher recycling rates, use advanced technologies. essay utilizes meticulously selected data Albania’s reputable organizations legal framework regulating assess current situation predict future possibilities, which may be advantageous government ministries agency platforms.

Language: Английский

Citations

0

DETERMINATION OF CONSTRUCTION STEP TO ARTIFICIAL STRIPS OF BACKFILLING FORE REDUCE THE EMISSION OF CLIMATICALLY ACTIVE GASES DOI Open Access
Vladimir Brigida, A.K. Dzhioeva

Ugol, Journal Year: 2024, Volume and Issue: 04, P. 74 - 78

Published: April 8, 2024

ПоДЗЕмнЫЕ раБотЫ • UNDERGROUND MININGГлобальная задача, стоящая перед отечественной горнодобывающей промышленностью, заключается в обеспечении «декарбонизации» добычи угля для достижения устойчивого развития горного производства.В связи с этим целью работы было совершенствование методологии определения шага возведения искусственных полос частичной закладки снижения эмиссии климатически активных газов за счет повышения устойчивости подрабатываемых дегазационных скважин.Итогом стала апробация методики оценки динамических пространственно-временных изменений концентрации метана при формировании максимального пролета кровли.Кроме того, определено значение предельного состояния пород кровли (150 м), определяющего частоту строительства сооружений области выработанного пространства лавы.

Language: Русский

Citations

0

Developing a chatbot-based information system for employee interaction DOI Creative Commons

Vasiliy Orlov,

В С Тынченко,

Ekaterina Volneykina

et al.

E3S Web of Conferences, Journal Year: 2024, Volume and Issue: 549, P. 08018 - 08018

Published: Jan. 1, 2024

Automated information systems, especially those that interact with employees through chatbots, are becoming increasingly popular in modern organizations. This paper examines the process of designing such a system using an object-oriented approach. Key aspects this discussed, including requirements analysis, architecture design, functionality development, and prototyping. Particular attention is paid to how approach can be applied create flexible, scalable, easily maintainable workforce management systems.

Language: Английский

Citations

0

Study on the effective drainage range of long horizontal borehole for goaf gas drainage DOI Creative Commons
Mingjie Guo, Wenbing Guo,

Ruifu Yuan

et al.

Energy Science & Engineering, Journal Year: 2024, Volume and Issue: 12(10), P. 4323 - 4334

Published: Aug. 27, 2024

Abstract Laying long horizontal borehole (LHB) in mining‐induced strata fractures for coal‐bed gas drainage the goaf is a pivotal method eliminating safety hazards, preventing atmospheric pollution, and realizing utilization. A crucial premise of this to determine effective range borehole, key parameter directly affecting boreholes spacing efficiency. In study, model seepage during LHB within circular equipotential boundary was presented, complex variable function theory mirror principle were adopted deriving potential flow under condition volume single center borehole. Besides, main indicator determinate given. Specifically, refers distance between turning point (the at which change rate velocity −0.002 around borehole) Subsequently, numerical simulation conducted obtain overlying strata, that is, 4 m < r 7 m. Furthermore, discussion carried out by analyzing distributions volumes. case study demonstrates double‐borehole layout with 10 can effectively control pressure‐relief goaf. Meanwhile, such achieve well‐balanced efficiency each minimal difference 0.31 3 min −1 , only about 7.9% average two boreholes. The above results verify determined reasonable. research provide references determining multi‐borehole coal mines, then LHBs arrangement, thereby improving extraction.

Language: Английский

Citations

0

Application of machine learning methods to predict soil moisture based on meteorological and atmospheric data DOI Creative Commons
В С Тынченко,

Oksana Kukartseva,

Ksenia Degtyareva

et al.

BIO Web of Conferences, Journal Year: 2024, Volume and Issue: 130, P. 02003 - 02003

Published: Jan. 1, 2024

The purpose of this study was to develop and evaluate models for predicting soil moisture based on data from meteorological conditions particle concentrations in the air. Two machine learning methods were used work: random forest linear regression. results showed that model achieved 94% accuracy, while regression 92% accuracy. Air temperature, air humidity concentration particles turned out be important factors affecting moisture. Both offered good predictive capabilities, with an emphasis ability a adapt complex nonlinear dependencies, interpret results. developed can useful optimizing agricultural processes, managing land resources environmental monitoring.

Language: Английский

Citations

0