A prediction and analysis model of complex system based on extension neural network - taking the prediction and analysis of terrorist events in the big data environment as an example

In predictive analysis of terrorist incidents there are often problems such as large data volumes, large data types, large redundancies, and difficulty dealing with multiple constraints, making it difficult to obtain effective prediction results for terrorist event prediction. Therefore, the methods of analysing and predicting terrorist events in big data environment are analysed, and a big data prediction analysis model for terrorist events based on improved extension neural network is presented. Firstly, a meta-element model for predicting and analysing terrorist events is established, the preliminary cluster analysis of the terrorist event prediction analysis based on the extension transformation is performed, and a terror event prediction extension principal component analysis model is established. Then, based on the prediction of the extension principal component analysis in the terrorist incident, an improved extension neural network structure is constructed, and the extension neurons based on different extensions are established. Furthermore, the predictive analysis model of the terrorist network extension neural network is formed, and the corresponding model and algorithm implementation steps are given. Finally, the algorithm and the model are illustrated and compared by specific case analysis, which shows the validity and feasibility of the model and algorithm.