Hybrid intelligent algorithm and its application in geological hazard risk assessment

This paper introduces a novel intelligent biologically inspired computational method developed to facilitate the accurate assessment of geological hazard risk (GHR). The Hybrid Intelligent Algorithm (HIA) combines Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Back Propagation (BP) neural network. GA is adopted to initialize the network connection weights and thresholds of BP and PSO is used to update them in the iteration process. In simulations based on hazard monitoring data from Jilin Province in northeastern China, the HIA method provided increased accuracy compared to established methods using BP neural networks. As GHR assessment grows in acceptance among the international risk assessment community, improved hybrid methods such as HIA will promote more effective planning in emergency response, environmental management, land use, and development.