To overcome premature problem of high-dimensional multimodal function in the optimization process by Standard Gravitational Search Algorithm (SGSA), a new Gravitational Search Algorithm based on Feedback mechanism (FGSA) was proposed. Considering the large loss in population diversity during the evolution process, the distance to the optimum position and the distance to its nearest neighbor were introduced into the proposed algorithm to balance the trade-off between exploration and exploitation ability. Mutation operation was also embedded into FGSA. The test results of four benchmark functions demonstrate that FGSA has much better stability and accuracy than SGSA in finding global optimum. Furthermore, when FGSA is applied to Support Vector Machine (SVM) classification, suitable feature subsets and SVM parameters can be effectively found out, and better classification results will be obtained.

A requirement modeling language called SPARDL was proposed for modeling and analyzing such periodic control systems consisting of periodic behaviors together with the mode transition mechanism. The Event-B interpretation was specified for the SPARDL model. The semantics of SPARDL were presented by Event-B and a refinement framework was introduced to develop the Event-B models based on the features of the SPARDL model. Finally, a case study was analyzed to show the effectiveness of our proposed approach to modeling and validation of the SPARDL model by Event-B.