# Deep Learning Forecasting for Supporting Terminal Operators in Port Business Development
## 1 Introduction  
In recent years, containerisation and ports have played important roles in international trade [1, 2] for supporting freight traffics efficiently in worldwide competition [3, 4]. Today, nearly all overseas shipments of products such as furniture, toys, footwear, clothing, auto parts, electronic components, and computers are usually made through containers on cargo ships. Furthermore, the amount of food goods shipped in refrigerated containers is also constantly growing [1], and this process has greatly stimulated the business development of terminal operators [5]. Therefore, shipping companies are using larger and larger ships that allow the transport of about 24,000 TEUs, minimizing unit transport costs and developing maritime economics of scale [6] to efficiently manage logistics activities both in port handling and in container storage on vessels through adoption of the so-called model of naval gignants [7]. In this context, the importance of optimal management and planning of ports' development is unquestionable [8]. In particular, construction costs represent sunk costs for a port, and to ensure that these investments in the development of ports will be profitable, the number and layout of the terminals [9, 10] in the port must be appropriately commensurate with the volume of container transport in the port itself [11]. It is therefore evident that, to avoid waste, port managers must be able to accurately predict the container transport volumes [12, 13], as this is essential for planning and organizing port activity [14] and is also relevant for government departments dealing with transport at both the micro and macro levels [15]. The demand forecast for container traffic is a crucial success factor in the business development of port logistics which allows efficient management of resources by both container terminal operators (i.e., concessionaires) and port authorities. Moreover, the strategic management of these maritime logistic activities depends on port governance models [16] as well as on the level of vertical integration of container transport processes between terminal operators and shipping companies [17; 18]. In this perspective, port authorities must forecast--through some concession clauses and the setting of target performance--the achievement of economic and operational outcomes by terminal operators [19], measurable in terms of traffic demand, logistics effectiveness, and efficiency managed by the \"landside\". Therefore, container terminal operators manage and plan critical logistic activities in accordance with port authority marketing strategies [20; 21] to support port competitiveness in the worldwide scenario [4; 22]. Technological advances--such as digitalisation and the Internet of Things--offer clear opportunities to streamline and synchronise operations, increase efficiency, and improve productivity toward the building of the so-called smart port [23; 24]. However, automation and port call optimisation involve digital investments, both for initial deployment and for keeping abreast of recent advances, and these investments are linked to traffic volume monitoring to support the port's competitive advantage [25]. Coherent with the aforesaid statements, this study comes at an opportune time when substantial variation can be observed in containerised shipment volumes, owing to factors such as trade tensions, protectionism, regionalisation of supply chains, the availability of mega container ships, and last but not least, the global pandemic [26]. In a scenario filled with uncertainty, port managers have to carefully rethink their development plans. Regulators and port authorities are also facing the challenges of a changing environment, especially insofar as they grant container terminal concessions. Finally, there is a fine-grained model capable of forecasting several categories of container traffic fits separately but simultaneously with the efforts to reduce carbon emissions due to shipping and the increased attention ports are giving to landslide operations and logistics.