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Improved Fuzzy Inference Network and Its Applications in Multi-targets Optimization of the High-Rise Structure Form Selection

机译:改进的模糊推理网络及其在多目标优化中的高层结构形式选择中的应用

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摘要

Firstly, two kinds of improved weighted fuzzy inference networks were established, namely the multi output multi input (MIMO) one and the multi input single output (MISO) one. The newly built networks share common merits with the weighted fuzzy evaluation method, the fuzzy inference method and the traditional fuzzy inference method, laying foundation for highly and effectively expressing, memorizing and utilizing the domain experts'' knowledge and strategies used in form selection. Then, two kinds of multi-target high-rise structure form selection optimization methods were established based on the improved fuzzy inference network and the fuzzy comprehensive evaluation model; and a comparison of characteristics was made between the two kinds of multi-targets optimization models: Both of them can directly and effectively solve the form selection optimization problem for the multi-target and multi layer structures. Moreover, the reasoning process of the first model can produce clearer and more concrete results, and the reasoning process of the second model is simpler. And it has been proven that the results of the models have the same conclusion. Finally, a project example was given, which proved that the methods can meet the needs and the optimization process better resembles people''s habits, experience and strategies in form selection.
机译:首先,建立了两种改进的加权模糊推理网络,即多输出多输入(MIMO)一个和多输入单输出(MISO)一个。新建的网络与加权模糊评价方法,模糊推理方法和传统的模糊推理方法共享常见的优点,奠定了高度有效表达,记忆和利用域专家的知识和策略的基础。然后,基于改进的模糊推理网络和模糊综合评价模型建立了两种多目标高层结构形式选择优化方法;在两种多目标优化模型之间进行了特征的比较:它们都可以直接且有效地解决多目标和多层结构的形式选择优化问题。此外,第一模型的推理过程可以产生更清晰,更具体的结果,第二种模型的推理过程更简单。已经证明,模型的结果具有相同的结论。最后,给出了一个项目示例,这证明了这些方法可以满足需求,优化过程更好地使人们的习惯,体验和策略在表单选择中。

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