It is known that there are two main types of resolution of the problem of identification of dynamic models. The first one is when there is a sufficient number of data about the modeled system and there is possibility of applying a certain statistical hypothesis. And the other is when there is no serious basis for applying any statistical hypothesis. In the latter case, the identification problem becomes a problem of adjustment between the parameters of the model and the observed data. Here are two methods of this adjustment. One of them is based on a particular property of the prey-predator system, namely: the average values of the number of prey and predators over a period are the same for all solutions. And the other method reduces the problem of identification to the resolution of a linear algebraic equation system with number of equations greater than the number of variables. The proposed methods were applied to analyze the incidence of soybean caterpillars (Anticarsia gemmatalis ) and their natural enemies that coexist in a prey-predator system. The results of the identification showed a good approximation of the model parameters to the observed data.
