When individuals in social groups communicate with one another and are under the influence of neighbors' opinions, they typically revise their own opinions to adapt to such peer opinions. The individual threshold of bounded confidence will thus be affected by both a change in individual confidence and by neighbor influence. Individuals thus update their own opinions with new bounded confidence, while their updated opinions also influence their neighbors' opinions. Based on this reasoned factual assumption, we propose an opinion dynamics model with time-varying bounded confidence. A directed network is formed by the rule of the individual bounded confidence threshold. The threshold of individual bounded confidence involves both confidence variation and the in/out degree of the individual node. When the confidence variation is greater, an individual's confidence in persisting in his own opinion in interactions is weaker, and the individual is more likely to adopt neighbors' opinions. In networks, the in/out degree is determined by individual neighbors. Our main research involves the process of opinion evolution and the basic laws of opinion cluster formation. Group opinions converge exponentially to consensus with stable neighbors. An individual opinion evolution is determined by the average neighbor opinion effect strength. We also explore the conditions involved in forming a stable neighbor relationship and the influence of the confidence variation in the convergence of the threshold of bounded confidence. The results show that the influence on opinion evolution is greater with increased confidence variation.