Semantic Scholar Open Access 2021 224 sitasi

Application of machine learning in intelligent fish aquaculture: A review

Shili Zhao Song Zhang Jincun Liu He Wang Jia Zhu +2 lainnya

Abstrak

Abstract Among the background of developments in automation and intelligence, machine learning technology has been extensively applied in aquaculture in recent years, providing a new opportunity for the realization of digital fishery farming. In the present paper, the machine learning algorithms and techniques adopted in intelligent fish aquaculture in the past five years are expounded, and the application of machine learning in aquaculture is explored in detail, including the information evaluation of fish biomass, the identification and classification of fish, behavioral analysis and prediction of water quality parameters. Further, the application of machine learning algorithms in aquaculture is outlined, and the results are analyzed. Finally, several current problems in aquaculture are highlighted, and the development trend is considered.

Topik & Kata Kunci

Biology

Penulis (7)

Shili Zhao

Song Zhang

Jincun Liu

He Wang

Jia Zhu

Daoliang Li

Ran Zhao

Format Sitasi

APA MLA BibTeX

Zhao, S., Zhang, S., Liu, J., Wang, H., Zhu, J., Li, D. et al. (2021). Application of machine learning in intelligent fish aquaculture: A review. https://doi.org/10.1016/J.AQUACULTURE.2021.736724

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Total Sitasi: 224×
Sumber Database: Semantic Scholar
DOI: 10.1016/J.AQUACULTURE.2021.736724
Akses: Open Access ✓