Abstract: This paper describes a computational model of searching behavior of lady beetle ( Coccinella septempunctata L.) by using Neural Network and Genetic Algorithms. It also describes several Neural Network structures to interpret how the Neural Network controls the behavior of lady beetle, as well as the evolution of the computational model. In the nature, Alphid’s pattern is clumped, and the lady beetle's food-foraging strategy is: when the predator does not touch the prey, the predator's behavior is searching in a large area; but if the predator finds a prey, it behavior switch to searching in the neighborhood area around the prey.In this paper, several Neural NetWork structures have been used to control the individuals' food-searching behavior. And a form of Genetic Algorithms have been used for the Neural Network's Learning.After simulation, the model's food-foraging strategy is similar to the nature. It is not very necessary for the lady beetle to have the ability of finding the Alphid in a short distance. In fact the Alphid almost can not escape after the lady beetle finds it. So the most important factor for improving the searching efficiency is the ability of memory. It coincides with the lady beetle's food-foraging behavior in the nature.

Key words: biochar, soil amendment, microbial ecology, combined bioremediation.