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The neural network scheme has been proved for the boiler design, and it provides a framework for the non-linear system models. In this paper, a hybrid of artificial neural network and firefly algorithm is proposed. The proposed modeling technique is simulated in MATLAB, and the experimentation is carried out extensively. The performance of the proposed modeling technique is demonstrated using type I and II error functions, followed by performing higher statistical measures such as error deviation and correlation analysis. Comparative analysis is made to substantiate the superiority of the proposed modeling technique.<\/jats:p>","DOI":"10.1515\/jisys-2016-0113","type":"journal-article","created":{"date-parts":[[2017,5,11]],"date-time":"2017-05-11T08:45:40Z","timestamp":1494492340000},"page":"393-412","source":"Crossref","is-referenced-by-count":7,"title":["Modeling and Optimizing Boiler Design using Neural Network and Firefly Algorithm"],"prefix":"10.1515","volume":"27","author":[{"given":"Sangram Bhagwanrao","family":"Savargave","sequence":"first","affiliation":[{"name":"Pacific Academy of Higher Education and Research University , Udaipur , India"}]},{"given":"Madhukar Jagannath","family":"Lengare","sequence":"additional","affiliation":[{"name":"Konkan Gyanpeeth College of Engineering , Karjat (MH) , Maharashtra 410201 , India"}]}],"member":"374","published-online":{"date-parts":[[2017,5,11]]},"reference":[{"key":"2025120523310297163_j_jisys-2016-0113_ref_001_w2aab3b7b7b1b6b1ab1b6b1Aa","doi-asserted-by":"crossref","unstructured":"M. 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