Xu, H.; Fu, M., and Jia, C., 2018. Classification method of marine tourism resource of least square support vector machines based on particle swarm algorithm. In: Liu, Z.L. and Mi, C. (eds.), Advances in Sustainable Port and Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 632–636. Coconut Creek (Florida), ISSN 0749-0208.

In the current marine tourism resources classification research, the potential relationship between various types of marine tourism resources characteristics can not be fully used. The dimensional Curse and low accuracy can not be solved in the process of marine tourism resources classification. Thus, this article proposes a method for automatically selecting parameters of support vector machine based on particle swarm optimization and applies it on marine tourism resources classification. This method maps the input space of marine tourism resources to a high-dimensional feature space through non-linear transformation and finds the optimal linear classification surface of marine tourism resources classification in this new space. This method takes the classification accuracy as the fitness function of optimization problem and uses the particle swarm optimization algorithm to optimize parameters of support vector machine.