Knowledge reasoning-oriented ship behavior formalized expression method and system

Abstract

The invention discloses a ship behavior formalized expression method and system oriented to knowledge reasoning, and the method comprises the steps: analyzing a ship entity and basic characteristics of behaviors of the ship entity, abstractly expressing a ship as a ship object, carrying out the specific description of the ship, and carrying out the modeling of the ship object; carrying out abstract expression on attribute elements, relation elements and time-space elements of the ship by using a resource description framework method and a set theory method; dynamic changes of the ship attribute elements and the relation elements in the space-time elements are abstractly expressed into ship behaviors, the ship behaviors are classified into ship attribute behaviors and ship relation behaviors according to element change types, and the ship behaviors are subjected to character and formulation expression by using a function mapping and set description method; the method is applied to a computer to identify and understand ship behaviors, and based on this, ship behavior knowledge is reasoned. According to the method, ship behaviors can be reasoned, and theoretical and method bases are provided for structured modeling and semantic understanding of the ship behaviors.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence knowledge expression, in particular to a formalized expression method and system for knowledge reasoning-oriented ship behavior. Background technique [0002] Ships are the main body of water traffic. The formal description and expression of ship behavior characteristics is the basis for modeling ship behavior characteristics, intelligent cognition and reasoning, and is also an important basic research for realizing ship intelligent control and water traffic situation intelligent perception. To study the characteristics of ship behavior, it is necessary to effectively organize the information elements of the water traffic scene, analyze and clearly and completely express the relationship between the various elements of ship behavior, and discover the rules of ship behavior; to realize the formal expression of ship behavior needs to be based on the characteristics of ships in the spa...

AI Technical Summary

Problems solved by technology

[0003] At present, many experts and scholars have conducted a lot of research on ship behavior. In terms of ship behavior characteristics, they mainly analyze the macro behavior and micro behavior of ships. The macro behavior mainly uses classical algorithms to cluster ship trajectories, and uses AIS data Class analysis of ship behavior characteristics to obtain typical ship motion trajectory, combined with Kalman filter, long-short-term memory neural network (LSTM) and other methods to predict ship navigation trajectory and real-time data status of the ship, and find the movement law of the ship in a certain voyage, It has certain guiding significance for the navigation of ships in this voyage, but the macro analysis cannot detect and analyze the abnormal behavior of a certain ship, nor can it express the current behavior status of the ship in real time

Microscopic analysis is to describe the behavior of individual ships. Scholars have successively proposed methods such as k-means clustering algorithm and Bayesian network, consistency detection, and cyclic neural network to identify abnormal behavior of ships, but these methods ignore the inherent nature of ship behavior patterns. evolution, making it difficult to accurately identify and predict ship behavior

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