Continuous space optimized artificial ant colony for real- time typhoon eye tracking

For real-time typhoon eye tracking, artificial ant colony (AAC) methodology has been proved valuable for the efficient & effective identification of snake contour model boundary, which was built to simulate the real unclear typhoon eye whirly shape. While satellite digital photograph technology make it possible to capture real-time meteorological information; by means of constructing solution space and heuristic information, the contour of non-clear typhoon eye can be tracked intelligently. However, the practical conditions and meteorological phenomena are very complicated, only using discrete energy parameters as the heuristic information to lead the intelligent directing of ants are not reliable enough. In this paper, continuous space multi-kernel functions are introduced to optimize the heuristic information. In order to supply more practical factors for the energy converging procedure, corresponding Gaussian parameters calculation method will be given. In comparison, the iteration numbers can be decreased concerning same complexity of the problem to be solved, which proves that proposed optimization could provide the improvement on the practicability and effectiveness of original solutions.