TreeMap 2016 Forest Type Algorithm (Image Service) حسب U.S. Forest Service (17476914)

"…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …"

Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

"…<div><p>A fault diagnosis method for oil immersed transformers based on principal component analysis and SSA LightGBM is proposed to address the problem of low diagnostic accuracy caused by the complexity of current oil immersed transformer faults. Firstly, data on dissolved gases in oil is collected, and a 17 dimensional fault feature matrix is constructed using the uncoded ratio method. …"

Algorithm: MAML with CL-selector. حسب Zhejun Sun (9873500)

Algorithm: Pre-fine-tuning. حسب Zhejun Sun (9873500)

Algorithm: CL-selector initialization. حسب Zhejun Sun (9873500)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). حسب Johannes Weyer (13392175)

Data Sheet 2_Early stroke detection through machine learning in the prehospital setting.pdf حسب María Ríos Delgado (22004942)

Data Sheet 1_Early stroke detection through machine learning in the prehospital setting.pdf حسب María Ríos Delgado (22004942)

Ablation comparison experimental data. حسب Tengfei Ma (597633)

Comparison of the performance of the different models in the BRFSS _ 2015 data set. حسب Lang Deng (5681033)

Statistical analysis of characteristics of the Z-AlizadehSani data set. حسب Lang Deng (5681033)

Performance comparison of different models of the BRFSS_2015 data set. حسب Lang Deng (5681033)

Breakdown of how the data was aggregated to get the different temporal aggregation levels. حسب Andrew J. Fairbairn (22231970)

parameter settings. حسب Yanyan Dong (1304145)

الموضوعات:

parameter settings. حسب Yanyan Dong (1304145)

الموضوعات:

Parameter settings. حسب Qingbo Tu (22641033)

"…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. This method uses GA to intelligently screen key features and optimize model parameters. …"

Indicator settings. حسب Qingbo Tu (22641033)

"…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. This method uses GA to intelligently screen key features and optimize model parameters. …"

Model parameter settings. حسب Dinghong Mu (14204200)

"…The model, optimized with multi-level attention mechanisms, excels in accuracy and generalization, particularly in handling data with pseudo-artifacts. Computational analysis indicates that the proposed optimization algorithm has minimal impact on CNN’s training and testing times. …"

Classification performance of each category of the test set in MLP during the improved processes. حسب Lu Xiao (314030)

الموضوعات:

Weighted-F1 of the optimal combination model with different scale text sets. حسب Lu Xiao (314030)

الموضوعات: