انتخاب بهترین روش یادگیری ماشین برای پیش بینی بارندگی

•   آرشیو : نسخه زمستان 1398
•   نوع مقاله : پژوهشی
•   کد پذیرش : 1350
•   موضوع : سایر شاخه های علوم رایانه
• نویسنده/گان : مریم باقری نسب بهابادی
•   کلید واژه : الگوریتم‌های هیبریدی، بهینه‌سازی، زمانبندی‌کارها، زمان اتمام اجرای کارها.
•   Abstract :
  A computational grid is a set of large-scale heterogeneous systems. Job scheduling is one of the most important issues in a distributed grid system. Genetic Algorithm As a basic evolutionary algorithm, it is a fair way to answer difficult problems that have failed with traditional conventional methods to achieve the desired results. This algorithm has been able to achieve acceptable results for the task scheduling problem in the grid system. In this research, the scheduling of tasks in the grid system is investigated by the proposed method. The second proposed method will create hybrid algorithms (H-GA-ICA), (H-GA-PSO), (H-GA-SA) and (H-GA-ACO) which is a way to combine algorithms. The main purpose of the proposed algorithms is to improve the local search process of the genetic algorithm (GA) by combining it with the evolutionary algorithms ICA, PSO, SA and ACO, preventing early convergence and stopping at local minimums and ensuring global optimization. Considering the time process of workflow and completion time of works as comparison criteria, finally the proposed algorithms (PSO-GA) and (H-GA-PSO) for the task scheduling problem in the distributed grid system were approved.
•   مراجع :
  1. Dordaie, N. and N.J. Navimipour, A hybrid particle swarm optimization and hill climbing algorithm for task scheduling in the cloud environments. ICT Express, 2018. 4(4): p. 199-202.
  2. Dai, Y., Y. Lou, and X. Lu. A Task Scheduling Algorithm Based on Genetic Algorithm and Ant Colony Optimization Algorithm with Multi-QoS Constraints in Cloud Computing. in 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics. 2015.
  3. Molaiy, S. and M. Effatparvar, Scheduling in Grid Systems using Ant Colony Algorithm. International Journal of Computer Network and Information Security, 2014. 6: p. 16-22.
  4. Zhang, L., et al., A Task Scheduling Algorithm Based on PSO for Grid Computing. International Journal of Computational Intelligence Research, 2008. 4: p. 37-43.
  5. Chen, T., et al., Task Scheduling in Grid Based on Particle Swarm Optimization. 2006. 238-245.
•  صفحات : 11-28
•   دانلود فایل ( 1.14 MB )