Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Rami Al-Hajj"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 2, Pp 2970-2990 (2024)
Training neural networks by using conventional supervised backpropagation algorithms is a challenging task. This is due to significant limitations, such as the risk for local minimum stagnation in the loss landscape of neural networks. That may preve
Externí odkaz:
https://doaj.org/article/056d6257fa0d48eb8db31d57a58793b7
Publikováno v:
Fractal and Fractional, Vol 7, Iss 5, p 371 (2023)
In this paper, we study direct and inverse problems for a nonlinear time fractional diffusion equation. We prove that the direct problem has a unique weak solution and the solution depends continuously on the coefficient. Then we show that the invers
Externí odkaz:
https://doaj.org/article/048103d44f5b4c309b0e65a161750b40
Publikováno v:
IEEE Access, Vol 8, Pp 148378-148403 (2020)
Several optimization problems from various types of applications have been efficiently resolved using available meta-heuristic algorithms such as Particle Swarm Optimization and Genetic Algorithm. Recently, many meta-heuristic optimization techniques
Externí odkaz:
https://doaj.org/article/2ca9967a2af34ed4a09d6c3a7b04e350
Publikováno v:
Sustainability; Volume 15; Issue 11; Pages: 9131
Currently, numerous machine learning (ML) techniques are being applied in the field of renewable energy (RE). These techniques may not perform well if they do not have enough training data. Additionally, the main assumption in most of the ML algorith
Autor:
Rami Al-Hajj, Ali Assi
Publikováno v:
AIMS Energy, Vol 5, Iss 5, Pp 798-813 (2017)
Solar irradiance is one of the most important parameters that need to be estimated and modeled before engaging in any solar energy project. This article describes a non-linear regression model based on genetic programming technique for estimating sol
Externí odkaz:
https://doaj.org/article/9d9a60e3051f4cf8a0021fc0d9e969f3
Publikováno v:
2022 11th International Conference on Renewable Energy Research and Application (ICRERA).
Publikováno v:
IEEE Access, Vol 8, Pp 148378-148403 (2020)
Several optimization problems from various types of applications have been efficiently resolved using available meta-heuristic algorithms such as Particle Swarm Optimization and Genetic Algorithm. Recently, many meta-heuristic optimization techniques
Publikováno v:
2021 10th International Conference on Renewable Energy Research and Application (ICRERA).
The ability of predicting solar radiation strength is particularly important for the best administration of power grids involving photovoltaic solar energy. The production-consumption balance of energy is one of the most important characteristics tha
Publikováno v:
Journal of Solar Energy Engineering. 143
The ability to predict solar radiation one-day-ahead is critical for the best management of renewable energy tied-grids. Several machine learning ensemble techniques have been proposed to enhance the short-term prediction of solar radiation strength.
Publikováno v:
2019 8th International Conference on Renewable Energy Research and Applications (ICRERA).
The integration of Solar Energy in smart grids and many utilities is continuously increasing due to its environmental and economical benefits. However, the uncertainty of available solar energy provides challenges regarding stability in power generat