Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm
By Diego Oliva, M. G. A. Aziz, Aboul Ella Otifey Hassanien. 2017
566 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/32f021b06593cc52c7c4ff991118b7ac33715436
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Electrical and Electronic Engineering
- Richard Binns
- Derick Mathew
- C. Rani
- Yue Wang
- Krishna K. Busawon
- Vincenzo Stornelli
- Mirco Muttillo
- M. Rajesh Kumar
In Renewable Energy, Sustainability and the Environment
- Richard Binns
- Derick Mathew
- C. Rani
- Yue Wang
- Krishna K. Busawon
- Vincenzo Stornelli
- Mirco Muttillo
- M. Rajesh Kumar
Citations in the corpus
- A New Simplified Five-Parameter Estimation Method for Single-Diode Model of Photovoltaic Panels (2019, methodology): “Other methods used time-varying acceleration coefficients particle swarm optimization (TVACPSO) [24], the hybrid adaptive Nelder–Mead simplex algorithm based on the eagle strategy [25], algorithms and adapting control parameters [27], genetic algorithms to estimate parameters [28], a chaotic whale o”
- Wind-Driven Optimization Technique for Estimation of Solar Photovoltaic Parameters (2018, methodology): “The comparison of results estimated by WDO and other techniques such as bee pollinator flower pollination algorithm (BPFPA) [26], self-adaptive teaching learning based optimization [27], cat swarm optimization [28], chaotic whale optimization algorithm (CWOA) [29], and FPA [15] has been shown in Tab”