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Meaden, G. J., & Aguilar-Manjarrez, J., eds. (2013). Advances in geographic
information systems and remote sensing for fisheries and aquaculture.
Summary version. FAO Fisheries and Aquaculture Technical Paper (No. 552).
Longdill, P. C., Healy, T. R., & Black, K. P. (2008). An integrated GIS approach for
sustainable aquaculture management area site selection. Ocean and Coastal
Management, 51, 612-624. https://doi.org/10.1016/j.ocecoaman.2008.06.010
Pedregosa, F. (2011) Scikit‑learn: machine learning in python. The Journal of
Machine Learning Research, 12, 2825–2830.
https://dl.acm.org/doi/10.5555/1953048.2078195
Ramos-Carreño, S., Valencia-Yáñez, R., & Correa-Sandoval, F. (2014). White spot
syndrome virus (WSSV) infection in shrimp (Litopenaeus vannamei) exposed
to low and high salinity. Arch Virol, 159, 2213–2222.
https://doi.org/10.1007/s00705-014-2052-0
Rajendran, K. V., Shivam, S., Praveena, P. E., Rajan, J. J., Kumar, T. S., Avunje, S.,
Jagadeesan, V., Babu, S. P., Pande, A., Krishnan, A. N., & Alavandi, S. V.
(2016). Emergence of Enterocytozoon hepatopenaei (EHP) in farmed Penaeus
(Litopenaeus) vannamei in India. Aquaculture. https://doi.org/10.1016/
j.aquaculture.2015.12.034
Rajitha, K., Mukherjee, C. K., & Vinu Chandran, R. (2003). Applications of remote
sensing and GIS for sustainable management of shrimp culture in India.
Aquacultural Engineering, 36(2007), 1–17. https://doi.org/10.1016/j.aquaeng.
2006.05.003
Rao, P. (2017). Computer aided shrimp disease diagnosis in aquaculture. IJRASET.
https://doi.org/10.22214 /ijraset.2017.2079
Satheesh, K. S., Anand Bharathi, R., & Alavandi, S. V. (2019). Viability of white
spot syndrome virus (WSSV) in shrimp pond sediments with reference to
physicochemical properties. Aquaculture International, 27, 1369-1382.
https://doi.org/10.1007/s10499-019-00394-2
Shahriar, M. S., & McCulluch, J. (2014). A dynamic data‑driven decision sup‑ port
for aquaculture farm closure. Procedia Computer Science, 29, 1236-1245.
https://doi.org/10.1016/j.procs.2014.05.111
Shinn, A. P., Pratoomyot, J., Griffiths, D., Trong, T. Q., Vu, N. T., Jiravanichpaisal,
P., & Briggs, M. (2018). Asian shrimp production and the economic costs of
disease. Asian Fisheries Science, 31(S), 29-58. https://doi.org/10.33997/j.afs.
2018.31.S1.003
Soykan, C. U., Eguchi, T., Kohin, S., & Dewar, H. (2014). Prediction of fish‑ ing
effort distributions using boosted regression trees. Ecological Applications,
24(1), 71-83. https://doi.org/10.1890/12‑0826.1
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