敏感区域预警数据
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通过对报位信息数据的实时分析，反映船只在敏感区域中的航行情况，基于对误入敏感区域或即将误入的船舶做出预警，对于预防和减少事故的发生、提高安全防范意识、加强事故调查等方面都具有重要意义，为海洋大数据服务平台等提供数据支持。1.数据收集与处理：收集和整理船只的实时报位信息。对数据进行清洗、校正和统一处理，确保数据的准确性和一致性。 2.特征提取与选择：通过对报位信息数据中标识符的比对，剔除不匹配的报位数据。 3.预警模型建立：利用收集的船只实时报位信息和预设的敏感区域信息，根据多监督学习模型建立预警模型。预警模型通过对船舶报位信息的进行线性回归的船舶轨迹预测建模。 4.预警规则设定：基于建立的预警模型，设定规则组合的预警规则，当预测轨迹必定经过敏感区域时触发预警。 5.预警输出和反馈：根据预警规则船只的实时报位信息和轨迹预测进行实时监测和分析，当触发预警条件时，通过模型预测提供船舶敏感区域的预测，及时生成预警信息反馈给用户，以便决策者能够及时采取相应的措施。
Real-time analysis of vessel position reporting data can reflect the navigation status of ships in sensitive waters, and issue early warnings for vessels that have improperly entered or are about to enter these areas. This is of great significance for preventing and reducing maritime accidents, enhancing safety awareness, and strengthening accident investigations, while providing data support for platforms such as marine big data service platforms. 1. Data Collection and Processing: Collect and organize real-time vessel position reporting data. Conduct data cleaning, correction and unified processing to ensure the accuracy and consistency of the dataset. 2. Feature Extraction and Selection: Compare the identifiers within the vessel position reporting data to eliminate mismatched reporting records. 3. Early Warning Model Development: Utilize the collected real-time vessel position reporting data and preset sensitive area information to build an early warning model using multi-supervised learning. The model conducts vessel trajectory prediction modeling through linear regression based on the vessel's position reporting information. 4. Early Warning Rule Configuration: Establish early warning rules in rule combinations based on the developed model. An early warning will be triggered when the predicted trajectory is confirmed to pass through a sensitive area. 5. Early Warning Output and Feedback: Perform real-time monitoring and analysis based on the vessel's real-time position reporting data and trajectory prediction results. When the early warning conditions are met, the model will provide predictions of the ship's exposure to sensitive areas, and generate early warning information in a timely manner to feed back to users, enabling decision-makers to take corresponding measures promptly.
