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基于极端积算子的LL型模糊数的最小一乘回归 被引量:1
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作者 王宁 陆秋君 《运筹与管理》 CSSCI CSCD 北大核心 2016年第1期145-153,共9页
针对模糊输入和模糊输出数据系统中的回归分析问题,考虑到系统中依赖关系不确定性特点以及模型稳健性和求解准确性等需求,建立一个模糊最小一乘优化模型。首先利用能诱导出LL型模糊数乘法保形运算的唯一T-模,即极端积算子,结合扩张原理... 针对模糊输入和模糊输出数据系统中的回归分析问题,考虑到系统中依赖关系不确定性特点以及模型稳健性和求解准确性等需求,建立一个模糊最小一乘优化模型。首先利用能诱导出LL型模糊数乘法保形运算的唯一T-模,即极端积算子,结合扩张原理,给出LL型模糊数间加法和乘法的运算规则。其次,基于LL型模糊数间的完备距离,得到模糊线性回归模型的参数估计,由此给出考虑清晰参数或清晰输入的两个简约模型及相应参数估计。通过计算Kim&Bishu测度、贴近测度和输出展形差异测度,比较与其他7种回归方法的优劣,并由模型的敏感性分析,充分说明本文算法的有效性和稳健性。 展开更多
关键词 极端积算子 LL型模糊数 扩张原理 最小一乘法 模糊线性回归
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基于极端积算子的具有直觉模糊输入–直觉模糊输出的回归模型研究
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作者 陈良凤 陆秋君 《运筹与模糊学》 2022年第2期141-156,共16页
本文首先基于极端积算子,结合扩张原理,给出LL-型直觉模糊数间除法运算的结果。通过举例来说明基于极端积算子的除法不能保证直觉模糊数的形状不变性。其次基于直觉模糊数的截集提出了直觉模糊数之间距离测量并进行性质分析,利用距离将... 本文首先基于极端积算子,结合扩张原理,给出LL-型直觉模糊数间除法运算的结果。通过举例来说明基于极端积算子的除法不能保证直觉模糊数的形状不变性。其次基于直觉模糊数的截集提出了直觉模糊数之间距离测量并进行性质分析,利用距离将直觉模糊回归模型等价于整合回归分析,极端积算子的LL-型直觉模糊数间的运算,以及最小一乘估计的最小优化问题,考虑当直觉模糊数退化成模糊数时的模型。最后将模型应用到对称的三角直觉模糊数据和对称的模糊数据,利用三个拟合优度准则,与其他方法进行对比验证了该方法的适用性。 展开更多
关键词 极端积算子 LL-型直觉模糊数 直觉模糊回归 水平截集距离
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T_(D)生成的三角模
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作者 孙文璟 李琪 李钢 《齐鲁工业大学学报》 CAS 2021年第2期62-68,共7页
三角模在一些领域中有广泛的应用,如概率度量空间、多值逻辑、广义测度和积分、决策等,因此构造不同的三角模显得尤为重要。本文主要研究了TD利用一元函数进行变换生成一类新的三角模,并给出对偶三角余模的相关结论。
关键词 三角模 极端积 变换 一元函数
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Modeling and optimal vibration control of conical shell with piezoelectric actuators 被引量:1
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作者 王威远 《High Technology Letters》 EI CAS 2008年第4期418-422,共5页
In this paper numerical simulations of active vibration control for conical shell structure with dis-tributed piezoelectric actuators is presented.The dynamic equations of conical shell structure are derivedusing the ... In this paper numerical simulations of active vibration control for conical shell structure with dis-tributed piezoelectric actuators is presented.The dynamic equations of conical shell structure are derivedusing the finite element model (FEM) based on Mindlin's plate theory.The results of modal calculationswith FEM model are accurate enough for engineering applications in comparison with experiment results.The Electromechanical influence of distributed piezoelectric actuators is treated as a boundary conditionfor estimating the control force.The independent modal space control (IMSC) method is adopted and theoptimal linear quadratic state feedback control is implemented so that the best control performance withthe least control cost can be achieved.Optimal control effects are compared with controlled responses withother non-optimal control parameters.Numerical simulation results are given to demonstrate the effective-ness of the control scheme. 展开更多
关键词 conical shell piezoelectric material smart structure vibration control active control
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Bridge damage identification based on convolutional autoencoders and extreme gradient boosting trees
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作者 Duan Yuanfeng Duan Zhengteng +1 位作者 Zhang Hongmei Cheng JJRoger 《Journal of Southeast University(English Edition)》 EI CAS 2024年第3期221-229,共9页
To enhance the accuracy and efficiency of bridge damage identification,a novel data-driven damage identification method was proposed.First,convolutional autoencoder(CAE)was used to extract key features from the accele... To enhance the accuracy and efficiency of bridge damage identification,a novel data-driven damage identification method was proposed.First,convolutional autoencoder(CAE)was used to extract key features from the acceleration signal of the bridge structure through data reconstruction.The extreme gradient boosting tree(XGBoost)was then used to perform analysis on the feature data to achieve damage detection with high accuracy and high performance.The proposed method was applied in a numerical simulation study on a three-span continuous girder and further validated experimentally on a scaled model of a cable-stayed bridge.The numerical simulation results show that the identification errors remain within 2.9%for six single-damage cases and within 3.1%for four double-damage cases.The experimental validation results demonstrate that when the tension in a single cable of the cable-stayed bridge decreases by 20%,the method accurately identifies damage at different cable locations using only sensors installed on the main girder,achieving identification accuracies above 95.8%in all cases.The proposed method shows high identification accuracy and generalization ability across various damage scenarios. 展开更多
关键词 structural health monitoring damage identification convolutional autoencoder(CAE) extreme gradient boosting tree(XGBoost) machine learning
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