Spatial propagation of different drought types and their concurrent societal risks: A complex networks-based analysis

Journal of Hydrology, Год журнала: 2024, Номер 636, С. 131247 - 131247

Опубликована: Апрель 28, 2024

Язык: Английский

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Predicting long term regional drought pattern in Northeast India using advanced statistical technique and wavelet-machine learning approach

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 10(1), С. 1005 - 1026

Опубликована: Июль 5, 2023

Язык: Английский

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Meteorological Variables Forecasting System Using Machine Learning and Open-Source Software

Electronics, Год журнала: 2023, Номер 12(4), С. 1007 - 1007

Опубликована: Фев. 17, 2023

The techniques for forecasting meteorological variables are highly studied since prior knowledge of them allows the efficient management renewable energies, and also other applications science such as agriculture, health, engineering, energy, etc. In this research, design, implementation, comparison models have been performed using different Machine Learning part Python open-source software. implemented include multiple linear regression, polynomial random forest, decision tree, XGBoost, multilayer perceptron neural network (MLP). To identify best technique, mean square error (RMSE), absolute percentage (MAPE), (MAE), coefficient determination (R2) used evaluation metrics. most depend on variable to be forecasting, however, it is noted that them, forest XGBoost present better performance. For temperature, performing technique was Random Forest with an R2 0.8631, MAE 0.4728 °C, MAPE 2.73%, RMSE 0.6621 °C; relative humidity, 0.8583, 2.1380RH, 2.50% 2.9003 RH; solar radiation, 0.7333, 65.8105 W/m2, 105.9141 W/m2; wind speed, 0.3660, 0.1097 m/s, 0.2136 m/s.

Язык: Английский

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A support vector machine based drought index for regional drought analysis

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Апрель 29, 2024

Abstract The increased global warming has the likelihood of recurrent drought hazards. Potential links between frequency extreme weather events and have been suggested by earlier research. spatial variability meteorological factors over short distances can cause distortions in conclusions or limit scope analysis a particular region when values predominate. Therefore, it is challenging to make trustworthy judgments regarding spatiotemporal characteristics regional drought. This study aims improve quality accuracy characterization process continuous monitoring. new indicator presented this called Support Vector Machine based index (SVM-DI). It created adding different weights an SVM-based X-bar chart that displayed with precipitation aggregate data. SVM-DI application site located Pakistan's northern area. Using Pearson correlation coefficient for pairwise comparison, compares Regional Standard Precipitation Index (RSPI). Interestingly, compared RSPI, shows more pronounced its correlations other stations, significantly lower Coefficient Variation. These results confirm useful tool analysis. methodology offers unique way reduce impact outliers aggregating

Язык: Английский

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Recent advances in Transformer technology for agriculture: A comprehensive survey

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 138, С. 109412 - 109412

Опубликована: Окт. 11, 2024

Язык: Английский

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