3 results about "Evacuation plan" patented technology

The system according to this embodiment aims to grasp detailed disaster risks for each region and to formulate effective disaster prevention plans. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a proposal unit, a prediction unit, and an instruction unit. The collection unit collects data such as topographic data, weather information, past disaster history, and infrastructure status. The analysis unit comprehensively analyzes the data collected by the collection unit and creates a detailed disaster risk map for each region. The proposal unit proposes the optimal evacuation plan and infrastructure development priorities based on the analysis results obtained by the analysis unit. The prediction unit predicts disasters in real time based on the latest data. The instruction unit generates the optimal evacuation order according to the situation of each resident.

We provide the system. [Solution] Means for acquiring atmospheric data and topographic information, Means for acquiring atmospheric information and topographic data, Means for pre-processing the aforementioned atmospheric information and topographic data, A means for analyzing the aforementioned atmospheric information and topographic data using machine learning methods to predict the probability of disaster occurrence, A means for generating an evacuation plan based on prediction results, Means for presenting the aforementioned evacuation plan via an output device, A means of providing personalized evacuation instructions based on the user's location information, A system that includes this.

The application discloses a multi-agent nuclear accident dynamic emergency evacuation method and a storage medium, and belongs to the technical field of nuclear accident emergency evacuation. In view of the problem that existing evacuation algorithms do not combine real city fine-grained traffic conditions in the nuclear proliferation scene, the application proposes a grid slicing and dynamic road condition mapping mechanism based on a map API. By obtaining the boundary coordinates of the target area to generate grid slicing, a rectangular query algorithm with frequency control is used to obtain branch-level real-time traffic data and time-series processing; the traffic data is superimposed with a nuclear radiation Gaussian plume space-time diffusion model to construct a radiation and traffic dual risk joint state matrix; based on the matrix, the MAPPO multi-agent reinforcement learning algorithm is used to train the agent through a multi-dimensional reward function to obtain an optimal collaborative evacuation plan that avoids congestion and high radiation areas. The application fills the technical gap in the real fine-grained road network access and multi-agent collaborative scheduling of nuclear emergency evacuation.