Data supporting figures and tables in Reimagining Electrical Diagrams in Construction: Automated Symbol Detection and Wiring Design and Generation with Deep Learning by IKENNA EKEKE (20996041)

“…</li><li>Evaluating automated wiring algorithms using modified A* search for layout optimisation.…”

The robustness test results of the model. by Xini Fang (20861990)

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Data Sheet 1_Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China.docx by Hanyu Zhang (1425250)

“…</p>Methods<p>UAV-LiDAR point clouds of Populus alba, Populus simonii, Pinus sylvestris, and Pinus tabuliformis from 12 sample plots, 2,622 tree in total, were obtained in North China, training and testing sets were constructed through data pre-processing, individual tree segmentation, feature extraction, Non-uniform Grid and Farther Point Sampling (NGFPS), and then four tree species were classified efficiently by two machine learning algorithms and two deep learning algorithms.…”

Effects of processing rate and algorithms performance on estimates of biodiversity. by Valentine Fleuré (12822137)

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Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx by Xuehui Fan (10762662)

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Optimize process data and final results by Dawei Wang (471687)

Statistics of GI data processing using different algorithms at various input CTTDs. by Ki Hyun Nam (5813819)

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Statistics of HEWL data processing using different algorithms at various input CTTDs. by Ki Hyun Nam (5813819)

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Algorithm for determining the number and selecting primary sampling units and households. by Oriol Mitjà (208397)

Decision tree construction process in Microsoft decision tree algorithm. by Liangzheng Wu (20501304)

Machine learning algorithms hyperparameter values. by Mahbub E. Sobhani (22278967)

Data processing. by Jay Chandra (19703931)