In order to solve the problem of ambiguity and limitation of application scope in the establishment of safety prevention and control measures for high-temperature tunnel construction, a method of generating prevention and control measures for high-temperature tunnels based on C-CBR is proposed. Firstly, the index system of the cloud case base is constructed for the tunnel high ground temperature and heat damage problem and combined with the analytic hierarchy process(AHP)-entropy weighting method for the comprehensive weighting calculation. Secondly, the cloud historical case base is constructed based on the three basic characteristic indexes of the cloud model, namely expectation, entropy, and hyperentropy, and the principle of case-based reasoning, and the collaborative filtering algorithm is applied to preliminarily filter the historical cases which are in line with the requirements. And then, the cloud model algorithm which integrates the shape-distance is introduced to achieve the integration between target cases and historical case base. Then, the integrated shape-distance cloud model algorithm is introduced to achieve similarity matching between the target cases and the historical case base, to correct the similarity and update the historical case base to generate the optimal similarity prevention and control measures; finally, the optimal similarity prevention and control measures are fully compared with the actual prevention and control measures in the field. The results show that the corrected similarity between the optimal historical case and the target case generated based on C-CBR is 0.746 0, which is a good match, and the the target case similar prevention and control measures are basically in line with the actual prevention and control measures of the project, which makes the generation method more applicable to different tunnels with high ground temperatures under construction.