A New Computer Performance Evaluation Model of Extended Cloud Based on Optimal Cloud Entropy
Jian Liu, Jianfang Lian, Panfei Yang, Ping Chen · 2024
In this paper, we propose a new computer performance evaluation model based on the extension cloud model. This approach eliminates the misjudgment of performance levels caused by the uncertainty of the evaluation process. The optimal cloud entropy adaptive method is introduced into the model to further adjust the clarity and fuzziness of the grade boundary. For nonlinear decision-making models in optimal cloud entropy computation methods, we propose the Improved Archimedean Optimization Algorithm (IAOA). IAOA uses random Gaussian variation strategy to guide the population to search the optimal solution region and enhance the global search ability. Finally, the experimental results demonstrate that this method effectively evaluates computer performance, and the evaluation results align with the actual situation.