Algorithm for planning shelters in oil and gas energy resource-based cities based on artificial intelligence resilient city model - Liang, Jing; Ge, Ming (Frontiers in Energy Research, 2023)
Oil and gas energy resource-based cities are crucial for energy production and economic development, but they also face various disasters and safety risks. To ensure the safety and well-being of urban residents in disaster events, the planning of urban shelters is crucial. This article used artificial bee colony algorithm to optimize the location and capacity planning of shelters, considering multiple factors including disaster risk, population distribution and transportation convenience. Secondly, by reasonably allocating facilities and resources, the emergency response ability and living security level of shelters were improved and the spatial layout and safety design of shelters were optimized to improve their disaster resistance and residents' safety. By comprehensively evaluating the disaster resistance ability, residents' response speed and other relevant indicators of urban shelters, the planning algorithm of shelters were continuously optimized to better satisfy the demands of oil and gas energy resource-based cities. The average overall disaster resistance of urban shelters based on artificial intelligence reached 0.64. When the distance from the shelter was four kilometers, the average response speed of residents reached 10.22 minutes and other indicators also improved. The planning algorithm for oil and gas energy resource-based urban shelters based on the artificial intelligence resilient city model provided an innovative method for urban planners and disaster managers. Further research and practice can help promote the application of this algorithm in practical cities and improve the resilience and disaster-resistance of cities, as well as the safety and security level of residents.