Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Hayet, Mouss"'
Publikováno v:
Revue des Énergies Renouvelables, Pp 47 – 57-47 – 57 (2024)
Due to the growing global demand for electricity energy, photovoltaic systems are becoming increasingly important as a continuous and environmentally friendly alternative. They ensure the continuity of electrical production in a healthy and sustainab
Externí odkaz:
https://doaj.org/article/f375fcc194b94fdab8062e839bc202a9
Publikováno v:
BizInfo, Vol 15, Iss 1, Pp 1-10 (2024)
Today, the algorithm selection paradigm has become one of the promising approaches in the field of optimization problems. Its main goal is to solve each case of an optimization problem with the most accurate algorithm using machine learning technique
Externí odkaz:
https://doaj.org/article/224f89cf11ec48dfaa6766e8c61b9d9d
Publikováno v:
International Journal of Production Management and Engineering, Vol 11, Iss 2, Pp 167-178 (2023)
In this paper, we present a novel hybrid meta-heuristic by enhancing the Basic Bees Algorithm through the integration of a local search method namely Simulated Annealing and Variable Neighbourhood Search like algorithm. The resulted hybrid bees algor
Externí odkaz:
https://doaj.org/article/4a6ec0e5b29548a2b833f2da530ec651
Analysis and Design of Modified Incremental Conductance-Based MPPT Algorithm for Photovoltaic System
Publikováno v:
Revue des Énergies Renouvelables, Vol 25, Iss 2, Pp 187 – 198-187 – 198 (2022)
This study discusses the design of the Maximum Power Point Tracking (MPPT) technique for photovoltaic (PV) systems employing a modified incremental conductance (IncCond) algorithm to extract maximum power from a PV module. A PV module, a DC-DC conver
Externí odkaz:
https://doaj.org/article/def9a61dae54465480f59ffd5df4c5cb
Publikováno v:
IEEE Access, Vol 9, Pp 152829-152840 (2021)
Nowadays, machine learning has emerged as a promising alternative for condition monitoring of industrial processes, making it indispensable for maintenance planning. Such a learning model is able to assess health states in real time provided that bot
Externí odkaz:
https://doaj.org/article/8a95c28b3d8741c397aacfeff34073e6
Publikováno v:
Aerospace, Vol 10, Iss 1, p 10 (2022)
Machine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing a
Externí odkaz:
https://doaj.org/article/c990e9d72d674a44916c43022d05549e
Publikováno v:
Entropy, Vol 24, Iss 7, p 1009 (2022)
The green conversion of proton exchange membrane fuel cells (PEMFCs) has received particular attention in both stationary and transportation applications. However, the poor durability of PEMFC represents a major problem that hampers its commercial ap
Externí odkaz:
https://doaj.org/article/95ea80808da34eeaa323f4e7e06e5421
Autor:
Tarek Berghout, Mohamed Benbouzid, Toufik Bentrcia, Xiandong Ma, Siniša Djurović, Leïla-Hayet Mouss
Publikováno v:
Energies, Vol 14, Iss 19, p 6316 (2021)
To ensure the continuity of electric power generation for photovoltaic systems, condition monitoring frameworks are subject to major enhancements. The continuous uniform delivery of electric power depends entirely on a well-designed condition mainten
Externí odkaz:
https://doaj.org/article/3218e447d5b443bb8b02614634f23f36
Publikováno v:
Energies, Vol 14, Iss 8, p 2163 (2021)
Since bearing deterioration patterns are difficult to collect from real, long lifetime scenarios, data-driven research has been directed towards recovering them by imposing accelerated life tests. Consequently, insufficiently recovered features due t
Externí odkaz:
https://doaj.org/article/94fa5a82386a48fb92d11ea2800d9437
Publikováno v:
IEEE Transactions on Energy Conversion. 37:1200-1210
Deep learning techniques have recently brought many improvements in the field of neural network training, especially for prognosis and health management. The success of such an intelligent health assessment model depends not only on the availability
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac44f128119cf9891302e58cd1c3d28d
https://doi.org/10.1109/tec.2021.3116423
https://doi.org/10.1109/tec.2021.3116423