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- W4292717562 abstract "This chapter develops a new hybrid bioinspired technique. Two famous algorithms inspired by nature viz . the Cuckoo search (CS) and the firefly algorithm (FA) are combined using all their advantages. FA is used to explore the whole search field, while CS is utilized for local search in a global optimization environment. Not only does the bioinspired method work better than parent approaches, but it also overpowers some recent metaheuristic methods. The effectiveness of our approach is demonstrated through some benchmark test functions. This fact is also confirmed by statistical measures and nonparametric research. Also, the hybrid algorithm is used effectively to find the amended double-diode model parameters. The findings of the two models of solar cells show the efficacy of the technique suggested. The fitness plots with the number of iterations validated that the results are more convergent and reliable. The parameter estimation technique can in the future be considered as multidimensional modeling of the diode with the technique proposed. A multitarget approach can also be a good alternative to modeling parameters for various photovoltaic panels." @default.
- W4292717562 created "2022-08-23" @default.
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- W4292717562 date "2022-08-23" @default.
- W4292717562 modified "2023-10-01" @default.
- W4292717562 title "A New Hybrid Proposition Based on a Cuckoo Search Algorithm for Parameter Estimation of Solar Cells" @default.
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- W4292717562 doi "https://doi.org/10.1002/9781119816096.ch8" @default.
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