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So in order to overcome these numbers of drawbacks, the use of higher order neural networks (HONNs) becomes the solution by adding input units along with a stronger functioning of other neural units in the network and transforms easily these input units to hidden layers. In this paper, a new metaheuristic method, Firefly (FFA), is applied to calculate the optimal weights of the Functional Link Artificial Neural Network (FLANN) by using the flashing behavior of fireflies in order to classify ISA-Radar target. The average classification result of FLANN-FFA which reached 96% shows the efficiency of the process compared to other tested methods. <\/jats:p>","DOI":"10.1142\/s0219467822500449","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T06:19:50Z","timestamp":1635229190000},"source":"Crossref","is-referenced-by-count":0,"title":["Firefly Algorithm Optimized Functional Link Artificial Neural Network for ISA-Radar Image Recognition"],"prefix":"10.1142","volume":"22","author":[{"given":"Asma","family":"Elyounsi","sequence":"first","affiliation":[{"name":"National Engineering School of Gab\u00e8s, University of Gab\u00e8s, Tunisia"},{"name":"Sciences and Technologies of the Image and Telecommunications (SETIT), ISBS BP 1175, 3038, University of Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hatem","family":"Tlijani","sequence":"additional","affiliation":[{"name":"EniGafsa, University of Gafsa, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed Salim","family":"Bouhlel","sequence":"additional","affiliation":[{"name":"Sciences and Technologies of the Image and Telecommunications (SETIT), ISBS BP 1175, 3038, University of Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2021,10,25]]},"reference":[{"key":"S0219467822500449BIB001","first-page":"466","volume-title":"7th IEEE Int. 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