A Harris Hawks optimization-based cellular automata model for urban growth simulation

Abstract

This paper proposes an innovative cellular automata model based on the Harris Hawk Optimization (HHO) algorithm. HHO is an intelligent optimization algorithm inspired by the cooperative hunting behavior of Harris’s hawks, demonstrating excellent optimization efficiency in spatial searches. Combining the HHO algorithm with the CA model, we establish the HHO-CA model for simulating urban growth in Guangzhou, China. The simulation achieves a total accuracy of 91.95%, an accuracy of urban cells of 82.43%, and a Kappa coefficient of 0.7441, all superior to the Null model. Furthermore, comparing the HHO-CA model with other representative CA models, the HHO-CA model outperforms in total accuracy, accuracy of urban cells, and Kappa coefficient, showcasing significant advantages in using the HHO algorithm to mine transition rules during the simulation of urban growth processes.