Geological Disaster Rescue Routes Based On Factor Space Optimization Study

With the continuous innovation of science and technology and the frequent occurrence of geological disasters,geological disaster rescue path optimization technology has become the focus of more and more experts and scholars,and at the same time it is the factor space in the field of analysis and processing of information and data science is in the stage of interactive integration development.The optimization of geological disaster rescue path based on factor space theory is a research with depth and significance,and this paper focuses on the feature data selection and path finding problem of rescue path optimization,and the main results are obtained as follows:First,this paper introduces the optimal rescue path constraint indicators and global rescue path search type,with each constraint indicator as an entry point for preliminary analysis,the selection of a suitable global rescue path search type has a positive effect on the rescue path planning results.Then,for the first time,the feature extraction method based on factor space theory is applied to the field of rescue path optimization for the problem of how to enhance the expression of feature data.Through the factor space feature data selection method,effective feature data is successfully extracted to identify the hidden important terrain and provide a comprehensive and specific terrain analysis for the optimal path.In addition,for solving large-scale combinatorial optimization problems,this paper proposes an ant colony optimization model based on factor proximity,which is mainly based on the factor space theoretical framework and the distance method of superior and inferior solutions,and adds the urban distance with the best proximity measure to the optimization mechanism of multiple swarm ant colony algorithms.The model results are obtained through the pheromone update mechanism and multiple iterations.Finally,the multiple swarm ant colony algorithm is introduced for the optimization problem of geological disaster rescue path.By comparing the factor ant colony optimization algorithm with the multiple swarm ant colony algorithm,it is demonstrated that the factor ant colony optimization algorithm achieves the optimal iteration with fewer iterations and shorter path distances under the condition of large-scale combinatorial optimization problem,and achieves the optimal iteration better compared with the multiple swarm ant colony algorithm.