Discussion of “Estimation of Reference Evapotranspiration Using Neural Networks and Cuckoo Search Algorithm” by Shahaboddin Shamshirband, Mohsen Amirmojahedi, Milan Gocić, Shatirah Akib, Dalibor Petković, Jamshid Piri, and Slavisa Trajkovic

Fister, Iztok [Jr.], Fister, Iztok and Yang, Xin-She ORCID logoORCID: https://orcid.org/0000-0001-8231-5556 (2018) Discussion of “Estimation of Reference Evapotranspiration Using Neural Networks and Cuckoo Search Algorithm” by Shahaboddin Shamshirband, Mohsen Amirmojahedi, Milan Gocić, Shatirah Akib, Dalibor Petković, Jamshid Piri, and Slavisa Trajkovic. Journal of Irrigation and Drainage Engineering, 144 (2) . 07017023. ISSN 0733-9437 [Article] (doi:10.1061/(asce)ir.1943-4774.0001270)

Abstract

Nature-inspired algorithms are modern tools to deal with nonlinear challenging optimization problems that are relevant in computer science, data mining, machine learning, medicine, engineering, and real-world applications. These methods are computer algorithms inspired by the behavior and characteristics of natural and biological systems in nature. In the last few decades, many different algorithms were developed, and it is estimated that there may be more than 100 different algorithms and variants. Thus, it is difficult to produce a complete list of all the relevant developments in this research area. For example, Fister et al. (2013) surveyed some of the contemporary metaheuristic algorithms and even classified them according to their sources of inspiration. [...]

Item Type: Article
Keywords (uncontrolled): Agricultural and Biological Sciences (miscellaneous), Civil and Structural Engineering, Water Science and Technology
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 28113
Useful Links:
Depositing User: Jisc Publications Router
Date Deposited: 07 Nov 2019 10:06
Last Modified: 27 Jan 2020 15:00
URI: https://eprints.mdx.ac.uk/id/eprint/28113

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