Robotics and Autonomous Systems, Journal Year: 2024, Volume and Issue: 183, P. 104839 - 104839
Published: Oct. 22, 2024
Language: Английский
Robotics and Autonomous Systems, Journal Year: 2024, Volume and Issue: 183, P. 104839 - 104839
Published: Oct. 22, 2024
Language: Английский
Alexandria Engineering Journal, Journal Year: 2025, Volume and Issue: 125, P. 463 - 479
Published: April 22, 2025
Language: Английский
Citations
0Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 257, P. 125054 - 125054
Published: Aug. 14, 2024
Language: Английский
Citations
3Ocean & Coastal Management, Journal Year: 2024, Volume and Issue: 257, P. 107342 - 107342
Published: Aug. 24, 2024
Language: Английский
Citations
3Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: unknown, P. 115830 - 115830
Published: Nov. 1, 2024
Language: Английский
Citations
3Turkish Journal of Forecasting, Journal Year: 2024, Volume and Issue: 8(2), P. 45 - 53
Published: May 31, 2024
The study analyzes coal consumption using the ECFGM(1, 1) model by utilizing time series data provided Statistical Review of World Energy for years 2016-2019. optimal α value, determined Brute Force Algorithm, is utilized to establish model’s parameters and formulate solution function. Subsequently, predictive accuracy assessed from 2020-2022, with resulting Mean Absolute Percentage Error (MAPE) reflecting overall performance.
Language: Английский
Citations
2Journal of King Saud University - Computer and Information Sciences, Journal Year: 2023, Volume and Issue: 35(9), P. 101780 - 101780
Published: Sept. 27, 2023
To solve the information overload problem of multimodal answers in community question answering (CQA), this paper proposes a representative answer extraction method. First, method similarity calculation between is constructed, and clustering used to cluster answers. Then, binary multi-objective optimization model with three objective functions including coverage, redundancy, consistency constructed extract subset The improved Beluga whale algorithm (MTRL-BWO), based on tent mapping, reinforcement learning, multiple swarm strategy, designed increase diversity population while avoiding local optima improve search capability solution accuracy algorithm. Experimental results show feasibility superior performance proposed
Language: Английский
Citations
3Robotics and Autonomous Systems, Journal Year: 2024, Volume and Issue: 183, P. 104839 - 104839
Published: Oct. 22, 2024
Language: Английский
Citations
0