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981
Assessing Environmental Policy Impact through the Ecological Footprint: The Case of Türkiye
Published 2025-07-01“…This study investigates the long-term effectiveness of environmental policies in Türkiye by examining the stochastic properties of the ecological footprint (EF) and its six subcomponents, carbon footprint, cropland footprint, grazing land footprint, forest products footprint, fishing grounds footprint, and built-up land footprint over the period 1961–2022. …”
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982
Movie Box Office Prediction Based on IFOA-GRNN
Published 2022-01-01“…By comparing this model with FOA-GRNN, KNN, GRNN, Random Forest, Naive Bayes, Ensembles for Boosting, Discriminant Analysis Classifier, and SVM, it is found that the prediction effect of the IFOA-GRNN model is significantly better than the above eight models. …”
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983
Stock Closing Price Prediction with Machine Learning Algorithms: PETKM Stock Example In BIST
Published 2023-04-01“…According to the calculated error metrics, LSTM and RFR algorithms gave better results than CNN with an MSE value less than 0.02. …”
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984
DISPUTES IN THE APPLICATION OF EMPLOYMENT COPYRIGHT LAW RELATING TO THE PRINCIPLE OF STRICT LIABILITY IN ENVIRONMENTAL CLUSTERS
Published 2024-01-01“…In this instance, it is evident in the environmental cluster of Article 22 Number 33 of the Job Creation Law, where the phrase "without the need to prove elements of error" is omitted, leading to ambiguity in its meaning. …”
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985
Assessing evapotranspiration dynamics across central Europe in the context of land–atmosphere drivers
Published 2025-07-01“…The land cover at the selected ICOS stations ranged from deciduous broad-leaf forests, evergreen needle-leaf forests, and mixed forests to agriculture. …”
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986
Using the ASTER GDEM v.2 global digital elevation model to identify areas of possible activation of karst processes in the Arkhangelsk region (Russia)
Published 2021-06-01“…This approach is especially relevant for northern forested territories subjected to continuously increasing anthropogenic activity. …”
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987
Data driven decisions in education using a comprehensive machine learning framework for student performance prediction
Published 2025-07-01“…Model evaluation was conducted using Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE), demonstrating the robustness of the proposed approach. …”
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988
Individual tree segmentation of airborne and UAV LiDAR point clouds based on the watershed and optimized connection center evolution clustering
Published 2023-07-01“…The results show that the matching rate (Rmatch) of tree tops is up to 0.92, the coefficient of determination (R2) of tree height estimation is up to .94, and the minimum root mean square error (RMSE) is 0.6 m. Our method outperforms the other methods especially in the broadleaf forests plot on slopes, where the five evaluation metrics for tree top detection outperformed the other algorithms by at least 11% on average. …”
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989
Urban tree health diagnosis approach based on thermal image and deep learning model
Published 2025-01-01“…Traditional methods of manual inspection are labour-intensive and prone to errors. In this research paper, we propose a novel approach for diagnosing tree health based on thermal imaging and deep learning models. …”
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990
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991
Modeling Whole-Plant Carbon Stock in <i>Olea europaea</i> L. Plantations Using Logarithmic Nonlinear Seemingly Unrelated Regression
Published 2025-04-01“…Carbon stock (CS) is an important indicator of the structure and function of forest ecosystems, and plays an important role in mitigating climate change, maintaining ecological system balance, promoting carbon trading, and other socioeconomic and ecological values. …”
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992
Environmental, socioeconomic, and sociocultural drivers of monkeypox transmission in the Democratic Republic of the Congo: a One Health perspective
Published 2025-02-01“…The GM (1, n) model, based on the proportion of primary forest, index of economic well-being, and mean annual precipitation, predicted the epidemic trend (revealed relative error: 2.69). …”
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993
Development of low-cost handheld soil moisture sensor for farmers and citizen scientists
Published 2025-05-01“…For generalized calibration in mineral soils, we observed an overall Root Mean Square Error (RMSE) of 0.035 m3m−3 and a bias of <0.001 m3m−3 along with a strong correlation (R = 0.90). …”
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994
COVID-19 Tweets Classification during Lockdown Period Using Machine Learning Classifiers
Published 2022-01-01“…The CNN and AdaBoost, on the other hand, have been taught to detect the mean square error, root mean square error, and mean absolute error. …”
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995
An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment
Published 2025-08-01“…Although algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, they generally struggle in the more varied urban environment. …”
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996
A Tractor Work Position Prediction Method Based on CNN-BiLSTM Under GNSS Signal Denial
Published 2024-12-01“…In farmland environments where GNSS signals are obstructed, such as forested areas or in adverse weather conditions, traditional GNSS/INS integrated navigation systems suffer from positioning errors and instability. …”
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997
3D Pulse Image Detection and Pulse Pattern Recognition Based on Subtle Motion Magnification Technology
Published 2025-05-01“…Finally, machine learning algorithms such as decision trees and random forests are used to identify the five types of pulse conditions: deep pulse, intermittent pulse, flooding pulse, slippery pulse, and rapid pulse. …”
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998
Stacked hybrid model for load forecasting: integrating transformers, ANN, and fuzzy logic
Published 2025-06-01“…Furthermore, these techniques are prone to errors in the presence of noisy data and have scalability issues when used on big, high-dimensional datasets. …”
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999
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Digitally twin driven ship cooling pump fault monitoring system and application case
Published 2024-01-01“…By establishing highly realistic physical and mathematical models and integrating actual operational data, a comprehensive virtual environment was created to simulate the operational status of ship cooling pumps. Using the random forest algorithm for data training and testing, the results showed that the root mean square error for the training set was 0.0037873, and for the test set, it was 0.008929, indicating high accuracy in predicting the status of cooling pumps. …”
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