Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Ebrahim Akbari"'
Autor:
Majid Pouraminian, Amir Ebrahim Akbari Baghal, Keyvan Andalibi, Farshid Khosravi, Vahid Arab Maleki
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract In the current investigation, the effect of recycled steel fibers recovered from waste tires on the pull-out response of ribbed steel bars from carbon nanotube (CNT)-modified ultrahigh performance fiber reinforced concrete (UHPFRC) was consi
Externí odkaz:
https://doaj.org/article/b54d4cd383c742688541bdf4b6dd84b3
Publikováno v:
Intelligent Systems with Applications, Vol 23, Iss , Pp 200398- (2024)
Optimal reactive power dispatch (ORPD) problems are important tools for the sake of security and economics of power systems. The ORPD problems are nonlinear optimization problems to minimize the real power losses and voltage profile enhancement by op
Externí odkaz:
https://doaj.org/article/f61ae0d731d146c8bb591dc35c4ada60
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-28 (2024)
Abstract This study introduces an enhanced self-adaptive wild goose algorithm (SAWGA) for solving economical-environmental-technical optimal power flow (OPF) problems in traditional and modern energy systems. Leveraging adaptive search strategies and
Externí odkaz:
https://doaj.org/article/9bab3baa54d04419b74e1100b6b9d333
Autor:
Keyvan Golalipour, Saber Arabi Nowdeh, Ebrahim Akbari, Seyed Saeed Hamidi, Danyal Ghasemi, Almoataz Y. Abdelaziz, Hossam Kotb, Amr Yousef
Publikováno v:
Alexandria Engineering Journal, Vol 83, Iss , Pp 257-285 (2023)
This paper proposes a novel efficient inspired algorithm based on snow avalanches in nature which is named the Snow Avalanches Algorithm (SAA), for solving the benchmark and engineering optimization problems and determining the global solution. The p
Externí odkaz:
https://doaj.org/article/1323970a161a43e0ad6a78fa4e4d4512
Autor:
Abolfazl Rahimnejad, Ebrahim Akbari, Seyedali Mirjalili, Stephen Andrew Gadsden, Pavel Trojovský, Eva Trojovská
Publikováno v:
PeerJ Computer Science, Vol 9, p e1557 (2023)
The whale optimization algorithm (WOA) is a widely used metaheuristic optimization approach with applications in various scientific and industrial domains. However, WOA has a limitation of relying solely on the best solution to guide the population i
Externí odkaz:
https://doaj.org/article/5e21976dfc244d3889b4f03ef7093d30
Akademický článek
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Autor:
Mojtaba Ghasemi, Abolfazl Rahimnejad, Ebrahim Akbari, Ravipudi Venkata Rao, Pavel Trojovský, Eva Trojovská, Stephen Andrew Gadsden
Publikováno v:
PeerJ Computer Science, Vol 9, p e1431 (2023)
Many important engineering optimization problems require a strong and simple optimization algorithm to achieve the best solutions. In 2020, Rao introduced three non-parametric algorithms, known as Rao algorithms, which have garnered significant atten
Externí odkaz:
https://doaj.org/article/7f08cd2cb97f4a77a623a998781b7aa3
Publikováno v:
مخاطرات محیط طبیعی, Vol 10, Iss 29, Pp 53-68 (2021)
Environmental hazards in structures, scales and different perspectives have different functions. It has been argued that the amount of damages and losses incurred from each occurrence or the consequence of it has a direct relation with the vulnerabil
Externí odkaz:
https://doaj.org/article/592de3b7ef9b4fd98d63ec2c5b72f96d
Publikováno v:
IET Renewable Power Generation, Vol 15, Iss 1, Pp 58-72 (2021)
Abstract Today, with growing expansion of renewable energy resources, electricity production is accompanied by uncertainties. The usage and optimal management of energy storage is one of the effective ways to compensate for these uncertainties. Compr
Externí odkaz:
https://doaj.org/article/04c527c0c7ae4b0b93dd4771e1fab0a4
Publikováno v:
Electronics Letters, Vol 57, Iss 13, Pp 499-501 (2021)
Abstract Grey wolf optimization (GWO) algorithm is a new emerging algorithm that is based on the social hierarchy of grey wolves as well as their hunting and cooperation strategies. Introduced in 2014, this algorithm has been used by a large number o
Externí odkaz:
https://doaj.org/article/feadca1c120544c887d2811bc126812a