# Performance Evaluation Model of Landport and Seaport Collaboration Using the Support Vector Machine
## 1 Introduction
[PERSON] and [PERSON] proposed a site selection framework of dry ports based on multiple standard analyses, and the whole framework was divided into four steps including the preliminary study of candidate sites, stakeholder classification, method application, and case study [7]. [PERSON] et al., proposed a site selection problem of hub ports by considering service time limitations and transport congestion. They considered cargo transportation time, loading and unloading time, and delay time on the hub network, and established a dispatching model with consideration of single and multiple hubs [8]. [PERSON] et al. proposed exploring the variable factors affecting the sustainable development of site selection of dry ports as well as how to evaluate such sustainable development. Further, they established a model by employing the multiple decision analysis method and Bayesian network to find out the key variables [9]. [PERSON] regarded the site selection optimization of dry ports as a multi-objective decision-making process, and combined the two optimization models of Fuzzy-AHP and ELECTRE [10]. [PERSON] et al., developed a mathematical model that minimizes the sum of transport and fixed costs associated with opening and closing dry ports. They conducted sensitivity analysis on model parameters [11]. [PERSON] et al. put forward a three-stage model on the basis of the existing one, which is respectively used to weigh decision criteria, determine potential locations and evaluate these alternatives [12]. The research on the network design of dry ports mainly focuses on the network traffic optimization model. [PERSON] et al. propose a multi-period shipping network including the location of dry ports on the basis of considering the problem of empty containers, cargo routes and cargo volume [13]. [PERSON] proposes a two-stage dry port network design model, which integrates strategic and operational decision considering the stochastic nature of demand [14]. [PERSON] and [PERSON], considering the wharf space resources, used the mathematical programming model of the two-stage weighted dynamic graph to transport container flows by using multimodal transport through establishing dry ports [15]. [PERSON] et al. believed that there was some room for the optimization of dry ports in the multimodal transport system, and proposed a mixed integer programming model to solve the route optimization and scheduling problems of vehicle transportation in the combined transport system of dry ports [16]. [PERSON] and [PERSON] considered the location of hub ports in the network and the distribution of these hubs by demand nodes, proposed a multi-modaltransport hub network based on a hierarchical structure, and solved the problem by using the heuristic algorithm based on the sub-gradient method [17]. In addition, there are also some studies on the cooperation between dry ports and seaports. [PERSON] and [PERSON] pointed out that cooperation between ports can improve the market share of cooperative ports [18]. [PERSON] used game theory to study the cooperation effect and cooperation relationship of Pakistani ports against the background of competition [19]. At present, the research on dry ports mainly focuses on the site selection of dry ports, the network design of dry ports, and the cooperation with seaports. The research of dry ports is very mature at present. The performance evaluation of the cooperation between ports will help both parties find out the problems in time and strengthen their own construction. At present, the performance evaluation methods of ports mainly include the neural network, analytic hierarchy process, grey theory, clustering, and other analysis methods. However, these methods can only unilaterally reflect the recent level of cooperation between seaports and dry ports. There are many factors that affect the cooperation between dry ports and seaports, and these factors have different degrees of influence.