Risk Assessment And Analysis Of The Gravity Net Cage Based On Machine Learning

In decade years,with the development of offshore aquaculture equipment technologies inChina,the scale of marine fishery facility represented by the gravity net cage and farming areas are expanding quickly and constantly.Because the coastal regions of our country are located in the areas with high frequencies of typhoon,storm surge and other marine disaster weather,offshore fishery facilities are facing threats mainly from serve marine environments such as typhoon and strong currents,which seriously hinder the healthy development of marine fishery facilities in China.The overall level of marine fishery facility in China is relatively low,most fishery facilities are given priority to imitating foreign fishery facilities and are severely damaged by the marine disaster every year.Hazard factors of fishery facility including wind,wave,current and structure vulnerability of facilities,the damage response of facilities,and the unclear failure mechanism are taken into considered,which leads the pre-disaster prediction and measures are not targeted every year.Carrying out the risk assessment and analysis of the gravity net cage can provide useful suggestions before disaster weather coming.By collecting the historical data of the damaged net cage,the failure of the gravity net cage mainly includes the cracked floating collars,deformed net and broken mooring lines.In our study,the gravity net cages with the circumference of 40 m,60 m and 80 m distributed in the sea near the Nanji Island in Wenzhou are considered as the study objects.According to the local hydrological parameters,corresponding wave conditions for calculation are designed.Wave height ranges from 4 m to 10 m,wave period ranges from 5.4 s to 12.5 s,as well as velocities are 0 m/s and 0.4 m/s,respectively.The numerical hydrodynamic response of the gravity net cage is calculated under the designed wave conditions in the depths with 20 m,22 m and 23 m.The quantitative relationship between the hazard factors and the failure of the gravity net cage is established by artificial neural network(ANN)and grey correlation method is used to identify the main hazard factor.According to the historical data of the damaged gravity net cage,the hydrodynamic threshold and the corresponding descriptions of the damaged gravity net cage are made.In this study,Typhoon Maria disaster is considered as an example.The feasibility and correctness of the early warning model for the gravity net cage are verified bypre-disaster survey,pre-disaster forecast and post-disaster survey.The wave height threshold of the gravity net cage located in the sea areas near the Nanji Island is determined with different failure levels and the spatial distribution pictures of the failure level of the gravity net cage with different recurrence periods are mapped,combined with the hydrodynamic threshold for the damaged gravity net cage.