论文标题
部分可观测时空混沌系统的无模型预测
A integrating critic-waspas group decision making method under interval-valued q-rung orthogonal fuzzy enviroment
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
This paper provides a new tool for multi-attribute multi-objective group decision-making with unknown weights and attributes' weights. An interval-valued generalized orthogonal fuzzy group decision-making method is proposed based on the Yager operator and CRITIC-WASPAS method with unknown weights. The method integrates Yager operator, CRITIC, WASPAS, and interval value generalized orthogonal fuzzy group. Its merits lie in allowing decision-makers greater freedom, avoiding bias due to decision-makers' weight, and yielding accurate evaluation. The research includes: expanding the interval value generalized distance measurement method for comparison and application of similarity measurement and decision-making methods; developing a new scoring function for comparing the size of interval value generalized orthogonal fuzzy numbers,and further existing researches. The proposed interval-valued Yager weighted average operator (IVq-ROFYWA) and Yager weighted geometric average operator (IVq-ROFYWG) are used for information aggregation. The CRITIC-WASPAS combines the advantages of CRITIC and WASPAS, which not only work in the single decision but also serve as the basis of the group decision. The in-depth study of the decision-maker's weight matrix overcomes the shortcomings of taking the decision as a whole, and weighs the decision-maker's information aggregation. Finally, the group decision algorithm is used for hypertension risk management. The results are consistent with decision-makers' opinions. Practice and case analysis have proved the effectiveness of the method proposed in this paper. At the same time, it is compared with other operators and decision-making methods, which proves the method effective and feasible.
