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Development characteristics and intelligent identification method of natural fractures: A case study of the Upper Triassic Xujiahe Formation in the western Sichuan Depression, Sich...
Published 2025-06-01“…It was found that the random forest algorithm demonstrated strong robustness and anti-interference capabilities, with higher prediction accuracy and efficiency compared to the other three algorithms. …”
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Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal...
Published 2025-07-01“…This study sought to evaluate the region's surface water quality and sources of contamination using machine learning (ML) methods such as Logistic Regression (LOR), Random Forest (RF), Artificial Neural Network (ANN), Support Vector Machine (SVM), Decision Tree (DT), and K-Nearest Neighbor (KNN). …”
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Integrating Landsat, Sentinel-2 and Sentinel-1 time series for mapping intermediate crops
Published 2025-12-01Get full text
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Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning
Published 2025-05-01Get full text
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Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery
Published 2024-10-01“…This study selected the main oasis area of Turpan City in Xinjiang, China, as the research area. …”
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Landslide susceptibility evaluation and determination of critical influencing factors in eastern Sichuan mountainous area, China
Published 2024-12-01“…The results shown that Random Forest Model proves to be the most accurate (95.1 %) in assessing the spatial distribution of shallow landslides susceptibility, followed by the Artificial Neural Network model (78.6 %), the Support Vector Machine model (69.8 %), the Generalized additive model (68.1 %) and the Logistic Regression model (67.6 %).The area with high susceptible landslide possibility was 25.3 km2 occupying 14.8 % of the study region, it is mainly distributed in the west of Tianchi Lake, southeast of Huaying City and west of the study area, along with Xiangyu Railway. …”
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A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa)
Published 2024-12-01“…To address this gap, the application of machine learning (ML) algorithms has emerged as an effective strategy. In this study, we applied 12 algorithms, namely, k-nearest neighbor (KNN), kernel k-nearest neighbors (KKNN), support vector machine (SVM), random forest (RF), stochastic gradient boosting (GBM), cubist, bagged multivariate adaptive regression splines (Bagged MARS), eXtreme gradient boosting (XGBoost), boosted generalized linear model (GLMBoost), boosted generalized additive model (GAMBoost), bayesian regularized neural networks (BRNN), and recursive partitioning and regression trees (CART) to build ML models for 225 mixture toxicity of azole fungicides towards Auxenochlorella pyrenoidosa. …”
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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review
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The protocol for a multicentre prospective randomized noninferiority trial of surgical reduction versus non-surgical casting for displaced distal radius fractures in children: Chil...
Published 2025-05-01“…Up to one year after randomization, the main outcomes plus data on complications, resource use, and school absence will be collected. …”
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Performance of invariants of gravity gradient tensor in matching navigation: A case study in South China Sea
Published 2025-05-01“…However, using gravity gradient invariants in existing research is seldom a concern. The gravity gradient tensor has three invariants, named as I1, I2 and I3. …”
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