The purpose of Civics teaching is to enhance the ideological awareness of talents and better meet the needs of society for the cultivation of talents’ thoughts. Based on this, the article takes Marxist theory as a guide, introduces Boolean network algebraization and multi-objective optimization ideas, and converts the optimization of Civics teaching content into a multi-objective optimization problem. Then the BiGRU-CRF model is utilized to identify the entities of Civics teaching content, and the entity relations are extracted by convolutional neural network, and then the Civics teaching content knowledge graph is established. Based on the knowledge map of Civics teaching content, a multi-objective fuzzy dynamic optimization network model of Civics teaching content is constructed by combining the Boolean network model and the fuzzy dynamic model. The SSA algorithm is optimized by MFO algorithm, and MC-SSA algorithm is established to solve the multi-objective fuzzy dynamic optimization network model. Simulation results show that the MC-SSA algorithm has high solving accuracy and the highest degree of proximity between its Pareto solution set and the real Pareto solution set, which can effectively solve the optimal results of the MFDBN model and provide guidance for the optimization of the Civics teaching content.
