Journal of Materials Science, Journal Year: 2024, Volume and Issue: 59(44), P. 20824 - 20839
Published: Nov. 1, 2024
Language: Английский
Journal of Materials Science, Journal Year: 2024, Volume and Issue: 59(44), P. 20824 - 20839
Published: Nov. 1, 2024
Language: Английский
Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 487, P. 136966 - 136966
Published: Jan. 7, 2025
Language: Английский
Citations
0Biomass and Bioenergy, Journal Year: 2025, Volume and Issue: 195, P. 107724 - 107724
Published: Feb. 18, 2025
Language: Английский
Citations
0Energy Reports, Journal Year: 2025, Volume and Issue: 13, P. 4163 - 4181
Published: April 6, 2025
Language: Английский
Citations
0Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 112, P. 551 - 568
Published: Nov. 13, 2024
Language: Английский
Citations
1Applied Sciences, Journal Year: 2024, Volume and Issue: 14(13), P. 5694 - 5694
Published: June 29, 2024
Smart highways represent a novel highway concept in the era of big data, emphasizing synergy among people, vehicles, road facilities, and environment. However, operation management smart have become more intricate, surpassing adaptability traditional evaluation methods. This study integrates distinctive characteristics facilities operational objectives to enhance modernize existing system. Drawing from research on construction projects, system encompassing facility structure, electromechanical services is formulated based hierarchical analysis method. The quantitative each indicator achieved by combining specifications expert questionnaire solicitation. group decision-making method initially employed optimize subjective weights, followed calculation combined weights using both entropy weight critic objective evaluation. Finally, comprehensive model established validated through engineering projects. results demonstrate that effectively highlights advantages disadvantages highways, thereby fostering advancement iteration.
Language: Английский
Citations
0Academic Journal of Science and Technology, Journal Year: 2024, Volume and Issue: 12(1), P. 261 - 264
Published: Aug. 20, 2024
This paper mainly studies the correlation between "momentum" index and match outcome in tennis matches, establishes a model to predict competition fluctuations. First, weights associated with were determined by CRITIC weight method, Spearman coefficient "performance coefficient" was 0.479, which indicated that there significant these two. Then, this analyzed other indicators coefficient", found successful first serve, unforced error, running distance, hitting number had an important influence on fluctuation of game. In order fluctuations, CNN LSTM combined form prediction model, good results 2023 Wimbledon data (RMSE <1). addition, used prove fluctuations player wins are not random, using at least one game explore factors change situation, laying foundation for developing predictive models. The allocation conducted explored relationship result analysis, established CNN-LSTM deep learning prediction, achieved high accuracy.
Language: Английский
Citations
0Journal of Materials Science, Journal Year: 2024, Volume and Issue: 59(44), P. 20824 - 20839
Published: Nov. 1, 2024
Language: Английский
Citations
0