adsabs/AstroCLIMB huggingface dataset:
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: The distributions of the differences between the latitudes of the source regions of the CMEs and the position-angle equivalent latitudes of the CMEs, occurring during the rising, maximum, and declining phases of Cycle 24 (horizontally for each row), are plotted for the CMEs originating from ARs, APs, and PEs (vertically for each column, corresponding to each phase of the solar cycle). A Gaussian is also fitted to each of the nine cases and the mean (μ), the absolute mean (μ  a ), and the standard deviation (σ) for each of the fitted Gaussians are also shown in each plot.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: The distribution of the difference between the latitudes of the source regions of the CMEs and the position-angle equivalent latitudes of the CMEs is plotted for all CMEs in panel (a) and for CMEs originating from ARs, APs, and PEs in panels (b), (c), and (d), respectively. A Gaussian is also fitted to all four cases and the mean (μ), the absolute mean (μ  a ), and the standard deviation (σ) for each of the fitted Gaussians are also shown in each plot.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: The distribution of the difference between the latitudes of the source regions of the CMEs and the position-angle equivalent latitudes of the CMEs, occurring during the minimum phase of Cycle 23, is plotted for all CMEs in panel (a) and for the ones originating from ARs, APs, and PEs in panels (b), (c), and (d), respectively. A Gaussian is also fitted to all four cases and the mean (μ), the absolute mean (μ  a ), and the standard deviation (σ) for each of the fitted Gaussians are also shown in each plot.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the variation of the speed distributions of all CMEs in panel (a), and those originating from the three different source regions (ARs, APs, and PEs) in panels (b), (c), and (d), respectively, during the minimum phase of cycle 23. A power law is also fitted to the data (dashed line) and the power-law index (α) is mentioned in each case.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the variation of the speed distributions of the CMEs originating from the three different source regions (ARs, APs, and PEs) and occurring during the declining phases of cycles 23 and 24. A power law is also fitted to the data (dashed line) and the power-law index (α) is mentioned in each case.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the variation of the speed distributions of the CMEs originating from the three different source regions (ARs, APs, and PEs) and occurring during the rising phases of cycles 23 and 24. A power law is also fitted to the data (dashed line) and the power-law index (α) is mentioned in each case.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the variation of the speed distributions of the CMEs originating from the three different source regions (ARs, APs, and PEs) and occurring during the maximum phases of cycles 23 and 24. A power law is also fitted to the data (dashed line) and the power-law index (α) is mentioned in each case.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Evolution of molecular hydrogen abundance ﹩{x}_{{{\rm{H}}}_{2}}﹩ and gas temperature T for the one-zone H2 formation test. The analytic solutions given by Equations (16) and (20) are shown as the red dotted curves. The black solid and blue dashed curves show the numerical results from the CVODE and forward Euler solvers, respectively. Both solvers yield results that agree with the analytic solutions.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: L1 error of the numerical solution as a function of the relative tolerance parameter in the CVODE solver for the one-zone H2 formation test. The gas temperature T is in kelvin. The L1 error increases when the relative tolerance is less stringent.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Abundance profile of the atomic hydrogen x H in the H2 formation with advection test. After 5 Myr, the numerical result is compared with the analytic solution. Here the number of grid cells is N = 128, and we use the RK2 integrator with PLM reconstruction.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Weak scaling of the computational cost for the turbulent multiphase ISM with time-dependent chemistry test performed using the NERSC Perlmutter cluster. The x- and y-axes denote the number of cores used and the time for finishing 100 iterations with a fixed block size of 483 for each core, respectively. Each dashed line represents a different potential hardware bottleneck for parallel efficiency, which are the core complex (labeled as CCX, 8 cores for zen3), the central processing unit (CPU) package (labeled as CPU, 64 cores in our test), and the compute node (labeled as Node, 128 cores in our test). The black horizontal line is the time for a single CPU core to finish 100 iterations, which is also the reference of ideal parallel efficiency.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Results from the turbulent multiphase ISM simulation test. The panels show a 2D slice of the gas density (left) and temperature (middle) overlaid with the plane-of-the-sky magnetic field streamline (shown as blue curves in the left panel), and the electron abundance (right). The white arrow in the middle panel represents the mean magnetic field direction.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Moving two-sided PDR test. The abundances of chemical species at t = 1 Myr are shown as lines with different colors indicated by the legends. The x-axis is the relative position of the PDR in the cold medium. The solid lines show the static reference solution with v  x  = 0. The square symbols, which overlap with the reference solution, show the results from the moving PDR with v  x  = 5 km s−1.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Convergence of chemical abundances for the H2 formation with advection test. The L1 error of H and H2 abundances are shown as red and blue lines, respectively. The results using the second-order scheme (RK2+PLM) are shown as dashed lines, while results from the third-order scheme (RK3+PPM) are in solid lines. As the resolution increases, the numerical error from advection decreases until, above a threshold resolution, the error from the chemistry ODE solver dominates, and the error flattens.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Static one-sided PDR test. The abundances of chemical species and gas temperature are shown as lines with different colors indicated by the legends. The solid lines show the result from our chemistry code with the GOW17 network. The square symbols, which overlap with the solid lines, show the results from the open-source PDR code by Gong et al. (2017).
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: A snapshot from TIGRESS simulation of the solar neighborhood ISM, with molecular content from chemistry postprocessing. The left panel shows the total column density from the original TIGRESS output. The middle and right panels show the H2 and CO column densities from chemistry postprocessing.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Results of the modified shock tube test from our Athena++ code (black solid curves), the KROME code Grassi et al. (2014; red circles), and the original Sod shock tube without chemistry and cooling (gray dashed curves). From top to bottom, the panels show the gas density, temperature, velocity, and the mass fraction of H2.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Pressure–density phase diagram of the multiphase ISM simulation snapshot shown in Figure 11. The color scale shows the number of pixels in each bin. The dashed curve denotes the thermal equilibrium state.
Paper: Implementation of Chemistry in the Athena++ Code
Authors: Munan Gong, 慕南 龚, Ka Wai Ho, James M. Stone, Eve C. Ostriker, Paola Caselli, Tommaso Grassi, Chang-Goo Kim, Jeong-Gyu Kim, Goni Halevi
Figure caption: Distribution of the H I, H2, and CO column density vs. the visual extinction A  V  in the TIGRESS simulation snapshot shown in Figure 8. The color scale shows the number of pixels in each bin.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: The left panels plot the offset differences between the SCR and SCR′ methods against the spatially dependent errors of E(B − V)SFD in the grizy bands. The other panels compare the differences between the SCR and SCR′ magnitude offsets for each set of two bands. Only boxes with more than five stars are plotted. The color in each panel indicates the number density of the stars. The red lines represent the linear fitting results, while the blue lines represent the theoretical results. The blue and red lines’ slopes are indicated in blue and red, respectively, and the correlation coefficients are marked in black. Here, Δm represents ﹩{\rm{\Delta }}{m}_{\mathrm{SCR}}-{\rm{\Delta }}{m}_{\mathrm{SCR}^{\prime} }﹩, m = {g, r, i, z, y}.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: Comparisons of individual stars for each set of two methods based on the common stars of the three method samples in the g, r, i, z, and y bands. For each panel, the standard deviation is marked in the top left corner, and the black dashed line denotes y = x. The color in each panel indicates the number density of stars. Top: ﹩{\rm{\Delta }}{m}_{\mathrm{SCR}^{\prime} }﹩ vs. Δm SCR. Middle: Δm XPSP vs. Δm SCR. Bottom: ﹩{\rm{\Delta }}{m}_{\mathrm{SCR}^{\prime} }﹩ vs. Δm XPSP.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: The same as Figure 10, but for comparisons with the restriction of the star numbers in boxes being more than 20 for the SCR method, more than 30 for the SCR′ method, and more than 50 for the XPSP method, after ﹩14^{\prime} \times 14^{\prime} ﹩ binning.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: Spatial variations of the differences between the SCR and SCR′ magnitude offsets for the common stars of the SCR sample and the SCR′ sample in the g, r, i, z, and y bands in the Galactic coordinate system. All-sky distributions of the spatially dependent correction from Sun et al. (2022) are shown in bottom right panel. Color bars are overplotted to the bottom, respectively.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: Spatial distribution of the XPSP magnitude offsets for stars of ∣b∣ < 20°. From top to bottom are the g, r, i, z, and y bands, respectively. The color bar is overplotted to the right. The black dotted lines indicate decl. of −30°.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: Spatial distribution of the differences between the observed SDSS magnitudes with the synthetic magnitudes of stripe 4682 in the i band. The color bar is overplotted to the right.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: The same as Figure 7, but for the SCR′ (left panel) and XPSP (right panel) methods.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: The same as Figure 7, but for the SCR (left panel) and XPSP (right panel) methods.
Paper: Improvement of Pan-STARRS Photometric Calibration with LAMOST and Gaia
Authors: Kai Xiao, Haibo Yuan, Bowen Huang, Ruoyi Zhang, Lin Yang, Shuai Xu
Figure caption: The same as Figure 3, but after combining.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the yearly occurrences of (a) slow and fast CMEs, and (b) the contributions of different source regions to the CMEs. The histograms are color-coded according to the categories they are representing. The y-axis on the left-hand side denotes the number of events that the histograms are representing. We also show the relative contribution of each category in each year (with respect to the total number of events in that particular year) on the y-axis plotted on the right-hand side, corresponding to the data points connected by dotted lines. The different phases of the solar cycle are highlighted in the background in different gray-scale shades.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: Yearly contributions of the source regions to (a) slow CMEs and (b) fast CMEs. The histograms are color-coded according to the category they are representing. The y-axis on the left-hand side denotes the number of events that the histograms are representing. We also show the relative contribution of each category in each year (with respect to the total number of events in that particular year) on the y-axis plotted on the right-hand side, corresponding to the data points connected by dotted lines The different phases of the solar cycle are highlighted in the background in different gray-scale shades.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: In this figure, we plot the (d) the distribution of the average speed of all CMEs and the distributions of the average speeds of CMEs coming from ARs, APs, and PEs in (b), (c), and (d) respectively. A power law is fitted to the data based on the MLE technique (dashed line). The power-law index (α) and the mean speed are also provided in each panel.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows the speed distributions of the CMEs, fitted with power laws (dashed lines), for different phases of the solar cycles 23 and 24. The fitted power-law index (α) is mentioned in each case.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: This figure shows examples of the three source region categories that have been considered in this work. (a) An AR is shown, which is exhibiting bright emission in AIA 171 Å. (b) A PE is shown, which is located at the quiet-Sun region, in AIA 304 Å. (c) An AP is shown in AIA 304 Å, where we can see that the footpoint of the prominence is connected to an AR.
Paper: A Coronal Mass Ejection Source Region Catalog and Their Associated Properties
Authors: Satabdwa Majumdar, Ritesh Patel, Vaibhav Pant, Dipankar Banerjee, Aarushi Rawat, Abhas Pradhan, Paritosh Singh
Figure caption: Fractional occurrences of (a) slow, fast, and intermediate CMEs and (b) the fractional contributions of the different source regions to the CMEs during the studied period.
Paper: A Systematic Observational Study on Galactic Interstellar Ratio 18O/17O. II. C18O and C17O J = 2–1 Data Analysis
Authors: Y. P. Zou, 益鹏 邹, J. S. Zhang, 江水 张, C. Henkel, D. Romano, W. Liu, 玮 刘, Y. H. Zheng, 映慧 郑, Y. T. Yan, 耀庭 闫, J. L. Chen, 家梁 陈, Y. X. Wang, 友鑫 汪, J. Y. Zhao, 洁瑜 赵
Figure caption:  18O/17O isotope ratios plotted as a function of galactocentric distance, R GC (Figure 6(a), left panel). In Figure 6(b) (right panel), we plot the weighted average values (weight 1/σ 2; see Paper I) of the ratio in bins of 1 kpc in R GC. The red circles and black triangles are the results from our IRAM 30 m and SMT 10 m measurements, respectively. The curves represent predictions of the most recent Galactic chemical evolution model; the dotted curve represents the model adopting the new yields by Limongi & Chieffi (2018) for nonrotating stars (MWG-10), the dash-dotted and solid curves show rotating stars without or with novae, respectively (MWG-12; see details in Romano et al. 2019).
Paper: A Systematic Observational Study on Galactic Interstellar Ratio 18O/17O. II. C18O and C17O J = 2–1 Data Analysis
Authors: Y. P. Zou, 益鹏 邹, J. S. Zhang, 江水 张, C. Henkel, D. Romano, W. Liu, 玮 刘, Y. H. Zheng, 映慧 郑, Y. T. Yan, 耀庭 闫, J. L. Chen, 家梁 陈, Y. X. Wang, 友鑫 汪, J. Y. Zhao, 洁瑜 赵
Figure caption: The comparison of estimated source sizes from C18O and C17O J = 2–1 lines (left panel) and the isotope ratio measured by IRAM 30 m and SMT 10 m (right panel) for the 41 sources detected by both telescopes toward identical positions. The dashed green lines indicate ﹩{\theta }_{s}^{18}﹩ = ﹩{\theta }_{s}^{17}﹩ and RatioIRAM = RatioSMT, while the dark and light shaded green areas indicate the ±10% and ±20% error ranges, respectively.
Paper: A Systematic Observational Study on Galactic Interstellar Ratio 18O/17O. II. C18O and C17O J = 2–1 Data Analysis
Authors: Y. P. Zou, 益鹏 邹, J. S. Zhang, 江水 张, C. Henkel, D. Romano, W. Liu, 玮 刘, Y. H. Zheng, 映慧 郑, Y. T. Yan, 耀庭 闫, J. L. Chen, 家梁 陈, Y. X. Wang, 友鑫 汪, J. Y. Zhao, 洁瑜 赵
Figure caption: The spectra of C18O (upper panels) and C17O (lower panels) with green fit lines of the 41 sources detected by both the SMT 10 m (left columns) and the IRAM 30 m (right columns) telescopes. .1 of 3 image
Paper: A Systematic Observational Study on Galactic Interstellar Ratio 18O/17O. II. C18O and C17O J = 2–1 Data Analysis
Authors: Y. P. Zou, 益鹏 邹, J. S. Zhang, 江水 张, C. Henkel, D. Romano, W. Liu, 玮 刘, Y. H. Zheng, 映慧 郑, Y. T. Yan, 耀庭 闫, J. L. Chen, 家梁 陈, Y. X. Wang, 友鑫 汪, J. Y. Zhao, 洁瑜 赵
Figure caption: Abundance ratios of the entire sample plotted against heliocentric distance. The red circles and black triangles represent our IRAM 30 m and SMT 10 m measurements, respectively.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: Schematic diagram of the shuffle process. Each column represents one kind of feature variable. i 1, i 2, ⋯, i  n  denotes the original order of the data in one column. After a shuffle, the order of data becomes j 1, j 2, ⋯, j  n .
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: Variation of the MAE for each feature during 100 shuffles.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: Feature importance ranking obtained by the information gain method.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: Feature importance ranking obtained by the permutation method.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: The predicted transit time by XGBoost model vs. the actual transit time for CMEs in the test set. The black dashed line denotes the perfect matching between the predicted and actual transit time.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: The average and maximum R 2 of trainings trained.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: Frequency distribution of 18 features of the CME and solar wind.
Paper: Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method
Authors: Y. Yang, J. J. Liu, X. S. Feng, P. F. Chen, B. Zhang
Figure caption: The average and minimum MAE of trainings trained.