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Gradient Optimization Assisted Bubble Sampling Method for Structural Reliability Analysis 认领 引用
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作者 Zeng Meng LiwenjieShen +2 位作者 Changquan Li Jiaxiang Yi Gang Dong 《Acta Mechanica Solida Sinica》 SCIE EI CSCD 2026年第6期891-904,共14页
The sampling method is an important numerical technique for solving reliability problems in engineering systems.However,the evaluation of the failure probability using classical sampling methods is time-consuming for ... The sampling method is an important numerical technique for solving reliability problems in engineering systems.However,the evaluation of the failure probability using classical sampling methods is time-consuming for complex engineering structure.To address this issue,this paper proposes a gradient optimization assisted bubble sampling method(GOBSM)to reduce the computational costs,which enhances the coverage range of bubbles,thereby improving the computational efficiency without sacrificing the accuracy.Furthermore,the bubble gradient iterative algorithm is developed to efficiently construct bubbles.Eight complex numerical examples are tested for assessing the failure probability,and the results demonstrate the performance of GOBSM. 展开更多
关键词 Reliability analysis Bubble sampling method Bubble gradient iterative algorithm Failure probability
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Adaptive Time Synchronization in Time Sensitive-Wireless Sensor Networks Based on Stochastic Gradient Algorithms Framework 认领 引用 被引量：2
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作者 Ramadan Abdul-Rashid Mohd Amiruddin Abd Rahman +1 位作者 Kar Tim Chan Arun Kumar Sangaiah 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第3期2585-2616,共32页
This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different... This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms.The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments.The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency.A novel closed-form expression is also derived for a generalized asymptotic error variance steady state.Steady and convergence analyses are then presented for the synchronization,with frequency adaptations done using least mean square(LMS),the Newton search,the gradient descent(GraDes),the normalized LMS(N-LMS),and the Sign-Data LMS algorithms.Results obtained from real-time experiments showed a better performance of our protocols as compared to the Average Proportional-Integral Synchronization Protocol(AvgPISync)regarding the impact of quantization error on synchronization accuracy,precision,and convergence time.This generalized approach to time synchronization allows flexibility in selecting a suitable protocol for different wireless sensor network applications. 展开更多
关键词 Wireless sensor network time synchronization stochastic gradient algorithm multi-hop
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融合自注意力编码与XGBoost-GSA的窃电检测方法 认领 引用
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作者 王金健 许宁照 +2 位作者 李中豪 郏琨琪 张凯 《电工技术》 2026年第10期101-104,共4页
针对当前窃电检测方法实现难和准确率低的问题,提出一种融合自注意力编码与XGBoost-GSA的窃电检测方法。首先对数据进行周期性波动分析,并使用变异系数对日电量数据进行筛选,然后采用基于Transformer的自注意力自编码器对筛选后的日电... 针对当前窃电检测方法实现难和准确率低的问题,提出一种融合自注意力编码与XGBoost-GSA的窃电检测方法。首先对数据进行周期性波动分析,并使用变异系数对日电量数据进行筛选,然后采用基于Transformer的自注意力自编码器对筛选后的日电量数据进行特征提取,再采用引力搜索算法(Gravitational Search Algorithm,GSA)对XGBoost进行部分超参数优化,将提取的特征作为XGBoost的输入,实现对窃电行为的检测。实验中所提方法各项指标均为最佳。 展开更多
关键词 窃电检测 自注意力机制 自编码器 极限梯度提升 引力搜索算法
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Improved preconditioned conjugate gradient algorithm and application in 3D inversion of gravity-gradiometry data 认领 引用 被引量：10
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作者 Wang Tai-Han Huang Da-Nian +2 位作者 Ma Guo-Qing Meng Zhao-Hai Li Ye 《Applied Geophysics》 SCIE CSCD 2017年第2期301-313,324,共13页
With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processin... With the continuous development of full tensor gradiometer （FTG） measurement techniques, three-dimensional （3D） inversion of FTG data is becoming increasingly used in oil and gas exploration. In the fast processing and interpretation of large-scale high-precision data, the use of the graphics processing unit process unit （GPU） and preconditioning methods are very important in the data inversion. In this paper, an improved preconditioned conjugate gradient algorithm is proposed by combining the symmetric successive over-relaxation （SSOR） technique and the incomplete Choleksy decomposition conjugate gradient algorithm （ICCG）. Since preparing the preconditioner requires extra time, a parallel implement based on GPU is proposed. The improved method is then applied in the inversion of noise- contaminated synthetic data to prove its adaptability in the inversion of 3D FTG data. Results show that the parallel SSOR-ICCG algorithm based on NVIDIA Tesla C2050 GPU achieves a speedup of approximately 25 times that of a serial program using a 2.0 GHz Central Processing Unit （CPU）. Real airbome gravity-gradiometry data from Vinton salt dome （south- west Louisiana, USA） are also considered. Good results are obtained, which verifies the efficiency and feasibility of the proposed parallel method in fast inversion of 3D FTG data. 展开更多
关键词 Full Tensor Gravity Gradiometry （FTG） ICCG method conjugate gradient algorithm gravity-gradiometry data inversion CPU and GPU
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Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system 认领 引用 被引量：3
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作者 程生毅 刘文劲 +3 位作者 陈善球 董理治 杨平 许冰 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第8期391-397,共7页
Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltage... Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ～ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ～(O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. 展开更多
关键词 adaptive optics iterative wavefront control algorithm direct gradient wavefront control algorithm
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Gradient Descent Algorithm for Small UAV Parameter Estimation System 认领 引用 被引量：1
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作者 Guo Jiandong Liu Qingwen Wang Kang 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2017年第6期680-687,共8页
A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and... A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and magnetometer are introduced to construct an error equation with the gyros,thus the drifting characteristics of gyroscope can be compensated by solving the error equation utilized by the gradient descent algorithm.Performance of the presented algorithm is evaluated using a self-proposed micro-electro-mechanical system(MEMS)based attitude heading reference system which is mounted on a tri-axis turntable.The on-ground,turntable and flight experiments indicate that the estimation attitude has a good accuracy.Also,the presented system is compared with an open-source flight control system which runs extended Kalman filter(EKF),and the results show that the attitude control system using the gradient descent method can estimate the attitudes for UAV effectively. 展开更多
关键词 gradient descent algorithm attitude estimation quaternions small unmanned aerial vehicle(UAV)
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Genetic Algorithm for the Thermal Stresses Optimum Design ofFunctionally Gradient Material Plate 认领 引用 被引量：2
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作者 Xiaodan Zhang Zhengbin Tang Changchun Ge 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS 1999年第3期224-227,共4页
Based on the thermal stress distribution for functionally gradient material(FGM)plates,a Genetic Algorithm(GA)method for the thermal stresses optimum design of FGM plate with computer technologies is given.The minimum... Based on the thermal stress distribution for functionally gradient material(FGM)plates,a Genetic Algorithm(GA)method for the thermal stresses optimum design of FGM plate with computer technologies is given.The minimum thermal stresses combination distribution for FGM is obtained. 展开更多
关键词 functionally gradient material(FGM) thermal stress Genetic Algorithm(GA) crossover mutation
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Improved gradient iterative algorithms for solving Lyapunov matrix equations 认领 引用 被引量：1
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作者 顾传青 范伟薇 《Journal of Shanghai University(English Edition)》 2008年第5期395-399,共5页
In this paper, an improved gradient iterative （GI） algorithm for solving the Lyapunov matrix equations is studied. Convergence of the improved method for any initial value is proved with some conditions. Compared wi... In this paper, an improved gradient iterative （GI） algorithm for solving the Lyapunov matrix equations is studied. Convergence of the improved method for any initial value is proved with some conditions. Compared with the GI algorithm, the improved algorithm reduces computational cost and storage. Finally, the algorithm is tested with GI several numerical examples. 展开更多
关键词 gradient iterative （GI） algorithm improved gradient iteration （GI） algorithm Lyapunov matrix equations convergence factor
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The Irregular Weighted Wavelet Frame Conjugate Gradient Algorithm 认领 引用
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作者 Jiang Li Yi Aichun +1 位作者 Zhang Changfan Zhu Shanhua 《China Communications》 SCIE 2007年第4期48-54,共7页
The dropping off of data during information transmission and the storage device’s damage etc.often leads the sampled data to be non-uniform.The paper, based on the stability theory of irregular wavelet frame and the ... The dropping off of data during information transmission and the storage device’s damage etc.often leads the sampled data to be non-uniform.The paper, based on the stability theory of irregular wavelet frame and the irregular weighted wavelet frame operator,proposed an irregular weighted wavelet fame conjugate gradient iterative algorithm for the reconstruction of non-uniformly sampling signal. Compared the experiment results with the iterative algorithm of the Ref.[5],the new algorithm has remarkable advantages in approximation error,running time and so on. 展开更多
关键词 Non-uniform sampling frame algorithm irregular wavelet frame conjugate gradient algorithm
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HYBRID MULTI-OBJECTIVE GRADIENT ALGORITHM FOR INVERSE PLANNING OF IMRT 认领 引用
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作者 李国丽 盛大宁 +3 位作者 王俊椋 景佳 王超 闫冰 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2010年第1期97-101,共5页
The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to an... The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment （IMRT）. The objective functions of planning target volume （PTV） and normal tissue （NT） are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications. 展开更多
关键词 gradient methods inverse planning multi-objective optimization hybrid gradient algorithm
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Improving the interpretation of undrained shear strength from piezocone penetration tests by integrating soil physical properties using a hybrid meta-heuristic algorithm 认领 引用 被引量：1
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作者 Meng Wu Zening Zhao Guojun Cai 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第5期3180-3197,共18页
Conventional empirical equations for estimating undrained shear strength(su)from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required f... Conventional empirical equations for estimating undrained shear strength(su)from piezocone penetration test(CPTu)data,without incorporating soil physical properties,often lack the accuracy and robustness required for geotechnical site investigations.This study introduces a hybrid virus colony search(VCS)algorithm that integrates the standard VCS algorithm with a mutation-based search mechanism to develop high-performance XGBoost learning models to address this limitation.A dataset of 372 seismic CPTu and corresponding soil physical properties data from 26 geotechnical projects in JiangsuProvince,China,was collected for model development.Comparative evaluations demonstrate that the proposed hybrid VCS-XGBoost model exhibits superior performance compared to standard meta-heuristic algorithm-based XGBoost models.The results highlight that the consideration of soil physical properties significantly improves the predictive accuracy of su,emphasizing the importance of considering additional soil information beyond CPTu data for accurate suestimation. 展开更多
关键词 Undrained shear strength Piezocone penetration test Extreme gradient boosting Meta-heuristic algorithm
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Performance of invariants of gravity gradient tensor in matching navigation: A case study in South China Sea 认领 引用 被引量：1
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作者 Xiaoyun Wan Ming Li +1 位作者 Panpan Chen Faisal Hussain 《Geodesy and Geodynamics》 EI CSCD 2025年第3期341-349,共9页
Choosing appropriate background field data is crucial for gravity field matching navigation.Current research mainly uses gravity anomaly data or gravity gradient data as background fields.However,using gravity gradien... Choosing appropriate background field data is crucial for gravity field matching navigation.Current research mainly uses gravity anomaly data or gravity gradient data as background fields.However,using gravity gradient invariants in existing research is seldom a concern.The gravity gradient tensor has three invariants,named as I1,I2and I3.I1 is a Laplace operator outside the Earth and a Poison operator inside the Earth.The focus of this study is to discuss the performance of the other two invariants of gravity gradients in matching navigation based on the Iterative Closest Contour Point(ICCP)algorithm and compare the matching results with that of the gravity gradient Tzz.The results show that they have almost the same performance when there is no noise,and the background data noises have a large impact on the matching results.There are differences in the anti-interference ability of observation noises for the different components.Under the same random noises in the observations,I2performs a little better than the other two components in terms of position error standard deviation.According to the investigations,since attitude errors can not be avoided and influence the positioning based on Tzz,we recommend adopting invariants of gravity gradients,especially I2,for matching navigation in actual cases. 展开更多
关键词 Invariants of gravityg radient tensor Matching accuracy The iterative closest contour point algorithm Gravity gradient noises
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基于LGWO-XGBoost-LightGBM-GRU的短期电力负荷预测算法 认领 引用 被引量：3
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作者 王海文 谭爱国 +4 位作者 彭赛 黄佳欣怡 田相鹏 廖红华 柳俊 《湖北民族大学学报（自然科学版）》 CAS 2025年第1期73-79,共7页
针对历史负荷特征提取困难所导致的短期电力负荷预测精度不高的问题,提出了基于堆叠泛化集成思想的逻辑斯谛灰狼优化-极限梯度提升-轻量级梯度提升机-门控循环单元(logistic grey wolf optimizer-extreme gradient boosting-light gradi... 针对历史负荷特征提取困难所导致的短期电力负荷预测精度不高的问题,提出了基于堆叠泛化集成思想的逻辑斯谛灰狼优化-极限梯度提升-轻量级梯度提升机-门控循环单元(logistic grey wolf optimizer-extreme gradient boosting-light gradient boosting machine-gated recurrent unit, LGWO-XGBoost-LightGBM-GRU)的短期电力负荷预测算法。该算法首先使用逻辑斯谛映射对灰狼优化(grey wolf optimizer, GWO)算法进行改进得到LGWO算法,接着使用LGWO算法分别对XGBoost、LightGBM、GRU算法进行参数寻优,然后使用XGBoost、LightGBM算法对数据的不同特征进行初步提炼,最后将提炼的特征合并到历史负荷数据集中作为输入,并使用GRU进行最终的负荷预测,得到预测结果。以某工业园区的负荷预测为例进行验证,结果表明,该算法与最小二乘支持向量机(least squares support vector machines, LS-SVM)算法相比,均方根误差降低了68.85%,平均绝对误差降低了69.57%,平均绝对百分比误差降低了69.97%,决定系数提高了8.42%。该算法提高了短期电力负荷预测的精度。 展开更多
关键词 短期负荷预测 集成学习 灰狼算法 极限梯度提升 轻量级梯度提升机 门控循环单元
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ADAPTIVE EXPONENT SMOOTHING GRADIENT ALGORITHM 认领 引用
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作者 裴炳南 李传光 《Transactions of Nanjing University of Aeronautics and Astronautics》 1997年第1期25-31,共7页
A new algorithm, called the adaptive exponent smoothing gradient algorithm (AESGA), is developed from Widrow′s LMS algorithm. It is based on the fact that LMS algorithm has properties of time delaying and low pass fi... A new algorithm, called the adaptive exponent smoothing gradient algorithm (AESGA), is developed from Widrow′s LMS algorithm. It is based on the fact that LMS algorithm has properties of time delaying and low pass filtering. This paper shows that the algorithm, on the domain of {Ω 1:α∈(0,1)}×{Ω 2:β(0,∞)} , unbiasedly and asymptotically converges to the Winner solution when the signal is a stationary Gauss stochastic process. The convergent property and the performance misadjustment are analyzed in theory. And calculation method of the algorithm is also suggested. Numerical results given by computer simulations show that the algorithm is effective. 展开更多
关键词 signal processing adaptive filtering gradient algorithm LMS algorithm computer simulation
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基于XGBoost-GRNN算法的分段式风功率预测 认领 引用 被引量：4
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作者 李进友 李媛 +2 位作者 黄露秋 王海鑫 李超然 《计算机集成制造系统》 EI CSCD 北大核心 2025年第10期3831-3845,共15页
针对风电大数据背景下风电机组功率预测准确性、预测功率曲线契合率低等问题,提出一种基于XGBoost-GRNN的风功率预测算法,建立考虑分段式风电数据的风电机组功率预测模型。首先,提出基于风电机组运行状态特征、风速分布模型的SCADA数据... 针对风电大数据背景下风电机组功率预测准确性、预测功率曲线契合率低等问题,提出一种基于XGBoost-GRNN的风功率预测算法,建立考虑分段式风电数据的风电机组功率预测模型。首先,提出基于风电机组运行状态特征、风速分布模型的SCADA数据分段划分方法,并基于数据多维度分析构建功率关联指标架构。其次,提出一种基于改进极端梯度提升(XGBoost)变量的广义神经网络(GRNN)联合风电机组分段式功率预测算法,以获取准确性较高、误差较小的功率预测值。进一步,基于预测偏差、曲线契合率等指标评估所提预测模型的预测性能。最后,以内蒙古塞罕坝风电场20台风电机组为例进行实验分析,结果表明:与传统预测方法相比,所提方法R2均值至少提高了0.0101;与全段数据预测相比,分段式预测R2提高了0.0084。所提模型预测曲线契合率为0.9184,相比其余4种模型预测曲线契合率至少提高了0.036。 展开更多
关键词 风电大数据 风电机组 极端梯度提升 广义神经网络 分段式功率预测算法
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基于XGBoost-MSIWOA-LSTM的车辆油耗优化预测模型 认领 引用 被引量：4
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作者 师国东 胡明茂 +3 位作者 宫爱红 龚青山 郭庆贺 谭浩 《计算机集成制造系统》 EI CSCD 北大核心 2025年第9期3467-3484,共18页
为有效预测车辆油耗,提高燃油经济性,促进节能减排,提出一种基于XGBoost-MSIWOA-LSTM的车辆油耗优化预测模型。该模型首先采用极端梯度提升树(XGBoost)算法提取车辆油耗特征,以优化模型的输入变量,提高模型的泛化性和鲁棒性。然后,利用... 为有效预测车辆油耗,提高燃油经济性,促进节能减排,提出一种基于XGBoost-MSIWOA-LSTM的车辆油耗优化预测模型。该模型首先采用极端梯度提升树(XGBoost)算法提取车辆油耗特征,以优化模型的输入变量,提高模型的泛化性和鲁棒性。然后,利用多策略改进的鲸鱼优化算法(MSIWOA)对长短期记忆神经网络(LSTM)中的超参数进行自适应寻优,并将优化后的超参数代入LSTM中对车辆油耗进行建模预测。结合实际车辆油耗算例进行对比实验,结果表明,相对于其他对比模型,XGBoost-MSIWOA-LSTM预测模型预测精度更高,对降低车辆油耗具有一定的指导意义。 展开更多
关键词 油耗预测 极端梯度提升树 多策略改进的鲸鱼优化算法 长短期记忆神经网络 自适应寻优
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Research on three-dimensional attack area based on improved backtracking and ALPS-GP algorithms of air-to-air missile 认领 引用
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作者 ZHANG Haodi WANG Yuhui HE Jiale 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第1期292-310,共19页
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t... In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10-4s,thus meeting the requirements of real-time combat scenarios. 展开更多
关键词 air combat three-dimensional attack area improved backtracking algorithm age-layered population structure genetic programming(ALPS-GP) gradient descent algorithm
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Gradient Optimizer Algorithm with Hybrid Deep Learning Based Failure Detection and Classification in the Industrial Environment 认领 引用 被引量：3
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作者 Mohamed Zarouan Ibrahim M.Mehedi +1 位作者 Shaikh Abdul Latif Md.Masud Rana 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1341-1364,共24页
Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Indu... Failure detection is an essential task in industrial systems for preventing costly downtime and ensuring the seamlessoperation of the system. Current industrial processes are getting smarter with the emergence of Industry 4.0.Specifically, various modernized industrial processes have been equipped with quite a few sensors to collectprocess-based data to find faults arising or prevailing in processes along with monitoring the status of processes.Fault diagnosis of rotating machines serves a main role in the engineering field and industrial production. Dueto the disadvantages of existing fault, diagnosis approaches, which greatly depend on professional experienceand human knowledge, intellectual fault diagnosis based on deep learning (DL) has attracted the researcher’sinterest. DL reaches the desired fault classification and automatic feature learning. Therefore, this article designs a Gradient Optimizer Algorithm with Hybrid Deep Learning-based Failure Detection and Classification (GOAHDLFDC)in the industrial environment. The presented GOAHDL-FDC technique initially applies continuous wavelettransform (CWT) for preprocessing the actual vibrational signals of the rotating machinery. Next, the residualnetwork (ResNet18) model was exploited for the extraction of features from the vibration signals which are thenfed into theHDLmodel for automated fault detection. Finally, theGOA-based hyperparameter tuning is performedtoadjust the parameter valuesof theHDLmodel accurately.The experimental result analysis of the GOAHDL-FD Calgorithm takes place using a series of simulations and the experimentation outcomes highlight the better resultsof the GOAHDL-FDC technique under different aspects. 展开更多
关键词 Fault detection Industry 4.0 gradient optimizer algorithm deep learning rotating machineries artificial intelligence
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Genetic Algorithm Optimization Design of Gradient Conformal Chiral Metamaterials and 3D Printing Verifiction for Morphing Wings 认领 引用 被引量：1
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作者 Qian Zheng Weijun Zhu +3 位作者 Quan Zhi Henglun Sun Dongsheng Li Xilun Ding 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第6期346-364,共19页
This paper proposes a gradient conformal design technique to modify the multi-directional stiffness characteristics of 3D printed chiral metamaterials,using various airfoil shapes.The method ensures the integrity of c... This paper proposes a gradient conformal design technique to modify the multi-directional stiffness characteristics of 3D printed chiral metamaterials,using various airfoil shapes.The method ensures the integrity of chiral cell nodal circles while improving load transmission efficiency and enhancing manufacturing precision for 3D printing applications.A parametric design framework,integrating finite element analysis and optimization modules,is developed to enhance the wing’s multidirectional stiffness.The optimization process demonstrates that the distribution of chiral structural ligaments and nodal circles significantly affects wing deformation.The stiffness gradient optimization results reveal a variation of over 78%in tail stiffness performance between the best and worst parameter combinations.Experimental outcomes suggest that this strategy can develop metamaterials with enhanced deformability,offering a promising approach for designing morphing wings. 展开更多
关键词 Morphing wings Chiral metamaterials Gradient conformal design Genetic algorithm optimization 3D printing
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A Hybrid Conjugate Gradient Algorithm for Solving Relative Orientation of Big Rotation Angle Stereo Pair 认领 引用 被引量：4
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作者 Jiatian LI Congcong WANG +5 位作者 Chenglin JIA Yiru NIU Yu WANG Wenjing ZHANG Huajing WU Jian LI 《Journal of Geodesy and Geoinformation Science》 2020年第2期62-70,共9页
The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochast... The fast convergence without initial value dependence is the key to solving large angle relative orientation.Therefore,a hybrid conjugate gradient algorithm is proposed in this paper.The concrete process is:①stochastic hill climbing(SHC)algorithm is used to make a random disturbance to the given initial value of the relative orientation element,and the new value to guarantee the optimization direction is generated.②In local optimization,a super-linear convergent conjugate gradient method is used to replace the steepest descent method in relative orientation to improve its convergence rate.③The global convergence condition is that the calculation error is less than the prescribed limit error.The comparison experiment shows that the method proposed in this paper is independent of the initial value,and has higher accuracy and fewer iterations. 展开更多
关键词 relative orientation big rotation angle global convergence stochastic hill climbing conjugate gradient algorithm
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