The Electromagnetic Environment Parameters Prediction Based On P Systems

Recently, with the rapid development of economy and technology, the electromagnetic environment is more and more complexity. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action.According to the analysis of existing research results, it is still in the early phase for electromagnetic environment prediction and visualization research. Presently, the main work is in the electromagnetic environment of battlefield, and has not yet been a panoramic view of electromagnetic environment for prediction and visualization system solutions based on the monitoring data. In order to overcome the shortcomings of existing technology, improve the level of intelligent radio monitoring and grasp the tendency of the radio electromagnetic situation. This article will research on related problems and put forward the complete algorithm and solution. The mainly work of this paper are as follows:(1) This paper puts forward a prediction model based on P systems for chaos time series, the model optimizes simultaneously the parameters of phase space reconstruction (r,m) and least squares support vector machine (LSSVM) (?,?) by using membrane computing optimization algorithm. Then, the model presented in this paper is used to forecast parameters in electromagnetic environment.(2) This paper puts forward a fuzzy Markov model based on FCM, in which, FCM algorithm is used to divide states of time series, the membership function is employed to calculate membership vector for each object about every fuzzy state. Then, using membership vector of predicted point as the weights, calculating predictive value by clustering center. Finally, the prediction model proposed in this paper is applied to predict indicate parameters in electromagnetic environment.(3) Compared P-LSSVM with FCM Fuzzy-Markov, it is found that P-LSSVM is much better than FCM Fuzzy-Markov for the prediction of chaos time series by experiment.