Tropical Cyclonears Developed Artificial Intelligence System to Protect Ports When Threats

When Tropik cyclonarlar threatens ports of global trade, timely and accurate preparation planning is vital. The researchers developed a new system by taking advantage of **makine learning technology to protect these critical infrastructures. The published study offers a two-stage artificial intelligence framework to predict what ports are at risk before storm and how long the operating interruptions are.

The system has the following basic features:

• Candidates ports at the first stage are selected according to the proximity to the expected output location
• In the second stage, more detailed analysis is assessed the potential for specific damage of each port
• The algorithm is used to overcome the uncertainty of historical data failure and output location
• The system aims to reliably sort the relative effects between ports

Most ports have limited history of observation on tropical cyclone, compelling predictability. In addition, the uncertainty of the exact exit path of storms complexes to implement emergency intervention plans. The two-stage system developed by researchers was designed to solve these problems. By using artificial intelligence methods combined with geographic proximity and meteorological data, the model can calculate every port-specific risk levels more in a way.

This technology allows port managers to set measures to take before storm. As a result, it helps to improve proactive strategies for the protection and minimization of critical infrastructure.