Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 25, 2025

Ozone pollution affects food production, human health, and the lives of individuals. Due to rapid industrialization urbanization, Liaocheng has experienced increasing ozone concentration over several years. Therefore, become a major environmental problem in City. Long short-term memory (LSTM) artificial neural network (ANN) models are established predict concentrations City from 2014 2023. The results show general improvement accuracy LSTM model compared ANN model. Compared ANN, an increase determination coefficient (R2), value 0.6779 0.6939, decrease root mean square error (RMSE) 27.9895 μg/m3 27.2140 absolute (MAE) 21.6919 20.8825 μg/m3. prediction is superior terms R, RMSE, MAE. In summary, promising technique for predicting concentrations. Moreover, by leveraging historical data enables accurate predictions future on global scale. This will open up new avenues controlling mitigating pollution.

Язык: Английский

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A spatiotemporal CNN-LSTM deep learning model for predicting soil temperature in diverse large-scale regional climates

The Science of The Total Environment, Год журнала: 2025, Номер 968, С. 178901 - 178901

Опубликована: Фев. 22, 2025

Язык: Английский

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Prediction of Crystalline Structure Evolution During Solidification of Aluminum at Different Cooling Rates Using a Hybrid Neural Network Model

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104578 - 104578

Опубликована: Март 1, 2025

Язык: Английский

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Short-Term Water Level Prediction for Long-Distance Water Diversion Projects Using Data-Driven Methods with Multi-Scale Attention Mechanism

Water Resources Management, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Язык: Английский

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Study on the Factors Influencing CO2 Hydrate Sequestration in CH4 Hydrate-Bearing Reservoirs

Energy, Год журнала: 2025, Номер unknown, С. 135777 - 135777

Опубликована: Март 1, 2025

Язык: Английский

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A Hybrid Wavelet-Based Deep Learning Model for Accurate Prediction of Daily Surface PM2.5 Concentrations in Guangzhou City

Toxics, Год журнала: 2025, Номер 13(4), С. 254 - 254

Опубликована: Март 28, 2025

Surface air pollution affects ecosystems and people’s health. However, traditional models have low prediction accuracy. Therefore, a hybrid model for accurately predicting daily surface PM2.5 concentrations was integrated with wavelet (W), convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), gated recurrent unit (BiGRU). The data meteorological factors pollutants in Guangzhou City from 2014 to 2020 were utilized as inputs the models. W-CNN-BiGRU-BiLSTM demonstrated strong performance during phase, achieving an R (correlation coefficient) of 0.9952, root mean square error (RMSE) 1.4935 μg/m3, absolute (MAE) 1.2091 percentage (MAPE) 7.3782%. Correspondingly, accurate is beneficial control urban planning.

Язык: Английский

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A machine learning computational approach for the mathematical anthrax disease system in animals

PLoS ONE, Год журнала: 2025, Номер 20(4), С. e0320327 - e0320327

Опубликована: Апрель 1, 2025

Objectives The current research investigations present the numerical solutions of anthrax disease system in animals by designing a machine learning stochastic procedure. mathematical is classified into susceptible, infected, recovered and vaccinated. Method A Runge-Kutta solver applied to collect dataset, which decreases mean square error dividing training as 78%, testing 12% verification 10%. proposed computing technique performed through logistic sigmoid activation function, single hidden layer construction, twenty-seven numbers neurons, optimization Bayesian regularization for animals. Finding designed procedure’s correctness authenticated results overlapping reducible absolute error, are calculated around 10 -05 -08 each case model. best performances -10 -12 Moreover, statistical terms regression coefficient, histogram, state transition values enhance reliability approach. Novelty scheme not before get

Язык: Английский

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CucuNetCNNs: Application of novel ensemble deep neural networks for classification of cucumber leaf disease

Ain Shams Engineering Journal, Год журнала: 2025, Номер 16(5), С. 103380 - 103380

Опубликована: Апрель 1, 2025

Язык: Английский

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BSANet: A Bilateral Segregation and Aggregation Network for real-time cloud segmentation

Remote Sensing Applications Society and Environment, Год журнала: 2025, Номер unknown, С. 101536 - 101536

Опубликована: Апрель 1, 2025

Язык: Английский

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Walrus Optimization Algorithm for Panchromatic and Multispectral Image Fusion

Remote Sensing Applications Society and Environment, Год журнала: 2025, Номер unknown, С. 101562 - 101562

Опубликована: Апрель 1, 2025

Язык: Английский

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