Soil quality analysis using statistical methods

BIO Web of Conferences, Год журнала: 2024, Номер 130, С. 02010 - 02010

Опубликована: Янв. 1, 2024

This paper presents an analysis of soil quality using statistical methods. The study includes correlation to identify key relationships between various and environmental parameters, regression quantify the influence these factors. findings demonstrate how factors such as geographical climatic conditions affect parameters. highlight effectiveness integrating methods for more accurate reliable related data. These results can be useful developing land management strategies improving agricultural practices.

Язык: Английский

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The impact of power system characteristics on the energy consumption of a steel plant

E3S Web of Conferences, Год журнала: 2024, Номер 583, С. 05012 - 05012

Опубликована: Янв. 1, 2024

This paper presents a comprehensive analysis of the relationships between energy consumption and various factors affecting operation power system steel plant. Given growing demand for electricity necessity to transition sustainable sources, studying these is becoming increasingly relevant. The main methods used in research include correlation factor analysis, which help identify key dependencies patterns behavior systems. study covers parameters such as reactive power, load type, temporal factors, including day week day's status. results reveal strong relationship lagging well significant connections with other variables, type characteristics. These highlight importance considering resource management. Factor identifies several influencing consumption, opening new opportunities process optimization findings emphasize need data approach effectively manage enhance resilience supply work practical significance companies specialists management, can be develop strategies optimizing improving planning, ensuring reliability. Overall, this contributes understanding dynamics lays foundation future field development.

Язык: Английский

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Statistical analysis of seasonal variations in pollutant concentrations in urban atmosphere

E3S Web of Conferences, Год журнала: 2024, Номер 592, С. 06010 - 06010

Опубликована: Янв. 1, 2024

In the context of global climate change and urbanization, issue air quality is becoming increasingly relevant. Air pollution poses a threat to human health ecosystems, highlighting need for monitoring concentrations pollutants. This study examines seasonal variations in harmful substances urban atmosphere using statistical methods. The aim research analyze time series data on carbon monoxide (CO), nitrogen oxide (NO), dioxide (NO2), sulfur (SO2), ozone (O3), ammonia (NH3), particulate matter (PM2.5 PM10). Correlation factor analysis are employed assess relationships between pollutants identify underlying factors. collected over several years emphasizes changes, showing that pollutant subject significant fluctuations driven by both natural anthropogenic results can be used develop strategies improving predicting impacts population. deepens understanding dynamics atmospheric its dependence, which important shaping environmental policy management decisions.

Язык: Английский

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Modeling techniques for enhancing barrel-type part casting processes

E3S Web of Conferences, Год журнала: 2024, Номер 592, С. 05022 - 05022

Опубликована: Янв. 1, 2024

This article discusses the principles of modeling casting process for parts - “Barrel”. A detailed overview drawing is provided, as well designed 3D model according to this drawing. The values allowances machining part are analyzed. characteristic obtained alloy presented, on basis which calculation technological yield suitable one made. At end article, result output a given.

Язык: Английский

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Forecasting seismic activity using machine learning algorithms

E3S Web of Conferences, Год журнала: 2024, Номер 592, С. 05002 - 05002

Опубликована: Янв. 1, 2024

In this paper, the possibility of using random forest method to predict earthquake locations based on historical data was studied. The aim work develop a model capable accurately predicting geographical coordinates earthquakes in India and adjacent regions. showed high accuracy predictions, which is confirmed by low values mean quadratic error (MSE) coefficients determination (R 2 ). Analysis results that successfully captures patterns able regions with seismic activity. At same time, areas deviations were identified, highlights need for further research improve increase its accuracy. This study demonstrates promise machine learning methods seismological forecasting tasks can serve as basis creating more accurate early warning systems.

Язык: Английский

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Comprehensive approach to modeling electricity consumption and identifying patterns using data mining methods

E3S Web of Conferences, Год журнала: 2024, Номер 592, С. 03006 - 03006

Опубликована: Янв. 1, 2024

In this study, a detailed analysis of dataset related to electricity consumption under various conditions was conducted. The includes comprehensive information such as indoor temperature at the time data recording, humidity levels, room size, number people present, use heating, ventilation, and air conditioning (HVAC) systems, lighting, day week, presence holidays. This extensive coverage factors provides an opportunity for deep understanding relationships between different variables. Several significant patterns were identified during analysis. One key finding detection connection readings consumption, confirming importance in energy usage. A correlation also found HVAC system use, indicating substantial impact these on overall consumption. Other lighting holidays, renewable sources, week proved factor These results further validated using Self-Organizing Maps (SOMs), which demonstrates reliability patterns. However, when attempting model data, less satisfactory. models showed only marginal improvement combining methods, suggesting need work. To achieve more accurate reliable results, it is recommended supplement with additional or apply sophisticated analytical methods. steps will help improve quality effectively utilize forecasting optimizing

Язык: Английский

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Modeling the impact of pollinator biodiversity on the resilience of agricultural ecosystems

BIO Web of Conferences, Год журнала: 2024, Номер 141, С. 01028 - 01028

Опубликована: Янв. 1, 2024

This study focuses on examining the factors that influence yield of wild blueberries (Vaccinium spp.), taking into account ecological and agronomic aspects. In context climate change declining pollinator populations, food security has become a pressing issue. Successful pollination determines quantity quality harvests, including berries. The research utilized data habitat characteristics blueberries, density (honeybees, bumblebees, bees) climatic conditions (temperature, precipitation). Statistical methods, such as correlation factor analysis, were applied to identify relationships between influencing factors. results showed high blueberry yields are associated with presence pollinators conditions. Positive correlations observed seed yield, well negative clone size fruit set. These findings underscore importance diversity optimal highlights need preserve biodiversity optimize practices in face change. can be used develop recommendations for improving cultivation methods increasing yields.

Язык: Английский

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Application of neural networks to predict the quality of iron ore concentrate based on flotation data

E3S Web of Conferences, Год журнала: 2024, Номер 583, С. 01014 - 01014

Опубликована: Янв. 1, 2024

This paper presents a study aimed at developing and testing neural network model for predicting the percentage of silica in iron ore concentrate obtained during flotation. The problem precise control content is critical mining industry, since quality final product and, accordingly, its market value depend on it. During study, data was collected from flotation plant, their preliminary processing carried out, including standardization elimination missing values. developed included two hidden layers trained real data. evaluation showed high results, which confirmed by metrics mean square error (MSE), absolute (MAE) coefficient determination (R 2 ). Additionally, an analysis visualizations residuals predicted values accuracy stability model. results demonstrate that proposed can be effectively used production conditions to improve process industry.

Язык: Английский

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Integration of IT solutions for resource management in environmentally sustainable agriculture

BIO Web of Conferences, Год журнала: 2024, Номер 145, С. 06008 - 06008

Опубликована: Янв. 1, 2024

This article presents the development of a resource management system for environmentally sustainable agriculture. The main purpose is to optimize use water, fertilizers and energy in agriculture, which significantly reduces negative impact on environment increases production efficiency. includes modules soil monitoring, data collection resources climatic conditions, as well analytical components processing analysing information received. An important element user interface, allows farmers agronomists receive recommendations allocation based up-to-date forecasts. work highlights current challenges such systems, including complexity technology integration need affordable solutions various types farms. also discusses prospects further research aimed at improving accuracy forecasts, expanding monitoring functions adapting small proposed makes significant contribution oriented providing tool contributing achievement environmental protection goals.

Язык: Английский

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Decision support in reforestation through the analysis of soil and mycorrhiza data

BIO Web of Conferences, Год журнала: 2024, Номер 145, С. 06006 - 06006

Опубликована: Янв. 1, 2024

This study presents an analysis of key biological and ecological factors affecting the growth survival tree seedlings. The dataset used includes information on soil types, levels mycorrhizal activity, biochemical compound content, light availability, other environmental parameters. Special attention is given to relationships between symbioses (AMF, EMF), plant physiological characteristics, conditions. Correlation cluster methods were applied data, allowing for identification groups with similar characteristics assessment impact various their survival. results emphasize importance microbial interactions indicators, such as phenol lignin in adaptation trees stressful data can be decision-making reforestation, including optimizing planting conditions selecting most resilient species. also highlights managing microbiome enhance effectiveness forest ecosystem restoration.

Язык: Английский

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