A prediction model of urban counterterrorism based on stochastic strategy

Abstract

With ever increasing complexity and intelligence of the modern cities, protecting key public facilities and important targets from any damage is a major challenge for the security sector. In all types of anti-terrorism prediction models, the prediction of attack behaviour is indispensable. Therefore, the attack behaviour model plays an important role in the anti-terrorism security system. This paper builds the attacker’s behaviour model, and carries out the prediction about the possible attack behaviour by the attacker model based on random strategy. According to the attack strategies, analysis and construction of the attack tree and attack graph are carried out based on the state-based stochastic model. The paper describes the security system in detail taking use of the state-based stochastic model method, so as to clarify the state distribution and the transfer relationship between the states of various security resources after threatened by attacks. At the same time, this paper applies the state-based stochastic model to establish the attacker model through the impact of attack on the security system.

Movement Evaluation Algorithm-Based Form Tracking Technology and Optimal Control of Limbs for Dancers

“…In motion reorientation, early researchers used traditional numerical methods. Qi X first proposed this problem as a spatial-temporal optimization problem for the entire motion, centered on solving it using hand-designed constraints and inverse kinematics [17]. Wu and Huo proposed a hierarchical curve-fitting technique combined with inverse kinematics to solve this problem [18].…”