# Predictive Analysis for Optimizing Port Operations
## 1 Introduction  
In the intricate landscape of global maritime logistics, an often overlooked yet substantial segment of a vessel's journey unfolds within the confines of port facilities. While traditional narratives tend to focus on vessels (ships) navigating the open waters [1, 2, 3], a substantial portion of their journey involves complex maneuvers, cargo handling, and operational intricacies within ports [4]. Surprisingly, although there is a dualistic nature of a vessel's journey, at sea and within port, the latter is relatively under explored in the existing literature. The temporal dynamics, efficiency challenges, and optimization opportunities inherent in the port-centric leg of a vessel's journey warrant closer scrutiny [5]. This gap in scholarly exploration calls for an in-depth examination, shedding light on the pivotal role that port activities play in the broader context of maritime transportation, supply chain efficiency, and global trade networks [6]. The optimization of port operations holds critical importance in the context of globalization, where nations strive to maintain their competitiveness and economic resilience in an interconnected world. Efficient port operations are essential not only for facilitating trade and commerce but also for accommodating the growing flow of goods and passengers associated with global tourism and cultural exchanges. The integration of marine traffic information through an Application Programming Interface (API) [7, 8, 9] has emerged as a key technological advancement, offering real-time insights into vessel movements and enabling proactive decision-making to enhance port efficiency on a global scale. While the specific focus of this project is on Brazil's ports, the broader implications extend to a global context. The main objective of this study is to analyze and optimizeport operations through predictive analysis of data obtained from Brazilian ports, applying recognized approaches to derive actionable insights. This research addresses a critical gap in the literature for integrating comprehensive data analysis with operational optimization strategies, an area that remains underexplored in maritime logistics [10,11]. The novelty of this study lies in its application of advanced statistical techniques to assess port efficiency, as well as its emphasis on feature analysis to improve port operations. By studying the case of Brazil, with its rich maritime history and strategic positioning in global trade, valuable insights can be gained that are applicable to port operations and maritime logistics across diverse regions and economies. The findings would be particularly relevant to port authorities, policymakers, and supply chain analysts seeking data-driven approaches to enhance port efficiency and global trade integration. The main contribution of the paper is as follows:  
* Defining the problem for predictive analysis for port operations which is lacking in the current literature. * Exhaustive comparison of methods with multiple metrics for prediction and classification of Total Time (Stay Time) and Delay Time at the port to obtain a holistic view. * Discovery of key factors that affect port operations using feature importance. * SHAP (Shapley Additive Explanations) analysis to understand the contribution of these key factors on the output. * The combined analysis and inference is used to improve decision-making for effective port operations. By providing tools to accurately predict and classify vessel behavior, this research contributes greatly to improving our understanding of various methods, which can be used to make more efficient and effective predictive analytics-based decision-making in port management. The paper is structured as follows: Section 2 provides a comprehensive review of the literature relevant to the study. Section 3 discusses Brazil's port case study and outlines the proposed methods used for port predictive analysis.