Application of a new computer program for tectonic discrimination of Cambrian to Holocene clastic sedimentsSpringer Science and Business Media LLC - Tập 9 - Trang 151-165 - 2015
Surendra P. Verma, Lorena Díaz-González, John S. Armstrong-Altrin
TecSand is a new Java software that is used for deciphering the tectonic setting of clastic sediments and sedimentary rocks through two new multidimensional discrimination diagrams. For each sample, TecSand calculates four complex discriminant functions: DF1m1 and DF2m1 for the high-silica diagram and DF1m2 and DF2m2 for the low-silica diagram, each representing linear combinations of log-ratios o...... hiện toàn bộ
Improving satellite image classification accuracy using GAN-based data augmentation and vision transformersSpringer Science and Business Media LLC - - Trang 1-18 - 2023
Ayyub Alzahem, Wadii Boulila, Anis Koubaa, Zahid Khan, Ibrahim Alturki
Deep learning (DL) algorithms have shown great potential in classifying satellite imagery but require large amounts of labeled data to make accurate predictions. However, generating large amounts of labeled data is time-consuming, costly, and can be problematic in the case of limited or imbalanced datasets. Data augmentation techniques have been proposed to improve the accuracy and robustness of D...... hiện toàn bộ
A framework for reading and unifying heliophysics time series dataSpringer Science and Business Media LLC - Tập 3 - Trang 75-86 - 2010
Jon Vandegriff, Lawrence Brown
We describe a framework designed to simplify the acquisition and integration of data from multiple, diversely formatted, geographically distributed science data sets. Our domain is Heliophysics where measurements of magnetic fields, plasmas, and charged particles are often made in-situ, with the data made available in relatively low volume data sets consisting of time series tables. Data format di...... hiện toàn bộ
Lithology identification of logging data based on improved neighborhood rough set and AdaBoostSpringer Science and Business Media LLC - Tập 15 - Trang 1201-1213 - 2022
Xialin Zhang, Qing Sun, Kunyang He, Zhenjiang Wang, Jin Wang
Traditional lithology identification left the problems of low accuracy, recognition efficiency and generalization ability. Facing the logging data with outliers, unbalance and high complexity, we propose a lithology identification method based on an improved neighborhood rough set and AdaBoost. On the basis of the classical neighborhood rough set, the selection of the neighborhood radius and the r...... hiện toàn bộ
Understanding the role of training sample size in the uncertainty of high-resolution LULC mapping using random forestSpringer Science and Business Media LLC - Tập 16 - Trang 3667-3677 - 2023
Kwanele Phinzi, Njoya Silas Ngetar, Quoc Bao Pham, Gashaw Gismu Chakilu, Szilárd Szabó
High-resolution sensors onboard satellites are generally reputed for rapidly producing land-use/land-cover (LULC) maps with improved spatial detail. However, such maps are subject to uncertainties due to several factors, including the training sample size. We investigated the effects of different training sample sizes (from 1000 to 12,000 pixels) on LULC classification accuracy using the random fo...... hiện toàn bộ
AI-driven reinforced optimal cloud resource allocation (ROCRA) for high-speed satellite imagery data processingSpringer Science and Business Media LLC - - 2024
Uma Maheswara Rao Inkollu, J. K. R. Sastry
The emergence of cloud computing has brought attention to the broad issue of resource allocation across domains. A thorough and adaptable solution to this complex issue is AI-driven Reinforced Optimal Cloud Resource Allocation, or ROCRA. By expertly fusing artificial intelligence with reinforcement learning, ROCRA develops an adaptive cloud resource allocation plan that works for a wide range of a...... hiện toàn bộ
Applicability evaluation and improvement of different snow evaporation calculation methods in the Great Xing’an mountainsSpringer Science and Business Media LLC - Tập 14 - Trang 1809-1820 - 2021
Youwei Lin, Tijiu Cai, Cunyong Ju, Xueqing Cui
This study highlights the importance of environmental factors and resultant snow evaporation rate change in the hydrologic balance of the seasonal snow-cover forest, and suggests that modeling studies must account for seasonally dissimilar characters of the environmental factors in order to accurately predict snow evaporation. Meanwhile, the relationship between the snow evaporation rate and envir...... hiện toàn bộ
Geospatial modeling using hybrid machine learning approach for flood susceptibilitySpringer Science and Business Media LLC - Tập 15 - Trang 2619-2636 - 2022
Bibhu Prasad Mishra, Dillip Kumar Ghose, Deba Prakash Satapathy
Advanced methods for flood susceptibility mapping are required to minimize hazards in the watershed. Here, Partial Least Square-Structural Equation Model (PLS-SEM) was introduced to analyze the impact of flood influencing factors. PLS-SEM integrated with four Machine Learning (ML) methods as Multi-Layer Perceptron Neural Network (MLPNN), K Nearest Neighbor (KNN), Support Vector Machine (SVM) and R...... hiện toàn bộ