## 4 Discussion
The second method is to judge the vessel state by analyzing characteristic data, such as vessel speed and heading, to form a vector. [PERSON] et al. [34] used the speed, heading, operation depth, and other vessel factors to discriminate the types of operating nets with the help of a neural network. They found that some factors, such as speed and heading, significantly impacted the discrimination results, which were more sensitive to the distinction of different nets, because they could better reflect fishing behaviors. _A. chinensis_ stow nets are quite different from other stow nets and trawl in their structure and operation, which is an exclusive net for shrimp fishing. In this study, artificial neural networks were used to identify the position state of the vessels based on speed and positioning time or heading and positioning time, and the more similar these elements of fishing behavior of fishers, the higher the identification accuracy of vessel states based on them. The results showed that the artificial neural network based on speed and positioning time could identify the position states of the vessels, verifying the high degree of similarity in fishers' operation habits [23; 24]. In contrast, the accuracy of identifying the states based on heading and positioning time was significantly lower (Tables 2 and 3) because there were significant differences in the speed characteristics of the vessels when fishing for shrimp (Table 4). Moreover, through the verification of the actual operation of the vessel at sea, it was found that the lower the speed of the fishing vessel, the greater the influence of the tidal current on its heading data, which means that there was no significant difference in the heading characteristics of different vessel states. Therefore, the heading of the vessel could not be used as a reference element for the neural network model to identify the vessel's state. Fishing behaviors were related to the biological characteristics of _A. chinensis_, fishing characteristics of nets, management of fishing policy, and the state of the marine environment. In spring, _A. chinensis_ migrates to shallow coastal waters for food and fattening as the water temperature of the coastal water rises. The shrimp gonads mature in May, whereafter they spawn and breed in low-salt coastal waters. Hereafter, some of the parent shrimp die naturally, while the juveniles are distributed in the coastal waters for feeding and growth [35; 36]. During the fishing moratorium in China, a special fishing period for _A. chinensis_ was set from 15 June to 15 July to protect and utilize shrimp resources scientifically. In terms of speed characteristics, there were obvious differences in the vessel speeds in different states (Figure 4). The vessel speed was the highest when departing from the port or exploring to maximize fishing time and production during the TACs project. In addition, the speeds of vessels in the same state were also slightly different and were mainly determined by the marine environmental conditions, such as current speed and wind speed and the quantity of catch in the fishing nets. In terms of positioning time characteristics, the set of VMS points with a casting state appeared at 4:00 a.m. and ended at 5:00 p.m. daily. (Figure 5). Waiting for a catch occurred between the casting and hauling states. Therefore, the waiting state was mainly distributed in the daytime, which was related to the fishing characteristics of the nets and the vertical movement of the shrimp during the day and night. Under the scientific setting of the buoyancy of floats and the gravity of sinkers and nets, combined with the impact of the ocean current, the mouths of the nets were mainly suspended above the sea bottom. At midnight, _A. chinensis_ gradually migrated to the bottom of the sea [37]. Therefore, the occurrence times of casting and hauling were closely related to the fishing time of _A. chinensis_ (i.e., the state of waiting for the catch) in the daytime.