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Simulation of unmanned survey path planning in debris flow gully based on GRE-Bat algorithm

Journal of Mountain Science 2024年第12期21卷 4062-4082页

作者： LIU Dunlong FENG Duanguo SANG Xuejia ZHANG Shaojie YANG Hongjuan College of Software Engineering Chengdu University of Information TechnologyChengdu 610225China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China

Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data *** planning of UAV advancing along river valleys in wild environments is one of the first and most difficult problems faced by unmanned surveys of debris flow *** study proposes a new hybrid bat optimization algorithm,GRE-Bat(Good point set,Reverse learning,Elite Pool-Bat algorithm),for unmanned exploration path planning of debris flow sources in outdoor *** the GRE-Bat algorithm,the good point set strategy is adopted to evenly distribute the population,ensure sufficient coverage of the search space,and improve the stability of the convergence accuracy of the ***,a reverse learning strategy is introduced to increase the diversity of the population and improve the local stagnation problem of the *** addition,an Elite pool strategy is added to balance the replacement and learning behaviors of particles within the population based on elimination and local perturbation *** demonstrate the effectiveness of the GRE-Bat algorithm,we conducted multiple simulation experiments using benchmark test functions and digital terrain *** to commonly used path planning algorithms such as the Bat Algorithm(BA)and the Improved Sparrow Search Algorithm(ISSA),the GRE-Bat algorithm can converge to the optimal value in different types of test functions and obtains a near-optimal solution after an average of 60 *** GRE-Bat algorithm can obtain higher quality flight routes in the designated environment of unmanned investigation in the debris flow gully basin,demonstrating its potential for practical application.

关键词： Bat algorithm Unmanned surveys Debris flow gully Path planning Unmanned aerial vehicle Reverse learning

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Landslide susceptibility prediction method based on HSOM and IABPA-CNN in Wenchuan earthquake disaster area

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Journal of Mountain Science 2024年第12期21卷 4001-4018页

作者： LIU Dunlong XIANG Qian SANG Xuejia ZHANG Shaojie YANG Hongjuan College of Software Engineering Chengdu University of Information TechnologyChengdu 610225China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China

Landslide susceptibility prediction assesses the likelihood of landslides occurring in specific areas,providing crucial scientific support for mitigating the threat to people’s lives and property posed by landslide *** address the challenges in the existing landslide susceptibility prediction methods,such as insufficient representativeness of selected nonlandslide points,limited ability to capture nonlinear relationships,and a tendency to fall into local optima,the traditional Self-Organizing Maps(SOM)is improved in this paper by using a hierarchical approach to form Hierarchical Self-Organizing Maps(HSOM),and a model integrating the Information Value(IV),Adaptive Bat Precise Algorithm(ABPA),and Convolutional Neural Network(CNN)is proposed,termed *** factors such as topography,basic geology and hydrometeorology were selected with the 2008 Wenchuan earthquake-hit disaster area as the study *** data were preprocessed,Pearson correlation coefficient,tolerance(TOL),and variance inflation factor(VIF)were employed to assess the correlation among all the ***,the information value for each evaluation factor's classification was calculated,thereby establishing a high-quality sample dataset,which was input into the IABPA-CNN model and IVCNN model(contrast model),*** Receiver Operating Characteristic(ROC)curve was used to compare and analyze the accuracy and *** Area Under Curve(AUC)values for the two models is 0.89 and 0.85,respectively,indicating that the IABPA-CNN model has higher predictive *** with the IV-CNN model,the proportion of landslides predicted by the IABPA-CNN model in the high susceptibility and very high susceptibility area increased to 28.18%and 30.76%,*** the area proportions of very low susceptibility and low susceptibility area increased,the proportion of landslides quantity ***,Monte Carlo method was employed to analyze the uncertaint

关键词： Landslide Susceptibility Information value Convolutional neural network Bat algorithm Monte Carlo

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An Adaptively Filtered Precise Integration Method Considering Perturbation for Stochastic Dynamics Problems

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Acta Mechanica Solida Sinica 2023年第2期36卷 317-326页

作者： Li Zhu Keqi Ye Dongwei Huang Feng Wu Wanxie Zhong State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDepartment of MechanicsFaculty of Vehicle Engineering and MechanicsDalian University of TechnologyDalian 116024China

The difficulty in solving stochastic dynamics problems lies in the need for a large number of repeated computations of deterministic dynamic equations,which has been a challenge in stochastic dynamics analysis and was discussed in this *** efficiently and accurately compute the exponential of the dynamics state matrix and the matrix functions due to external loads,an adaptively filtered precise integration method was proposed,which inherits the high precision of the precise integrationmethod,improves the computational efficiency and saves the memory ***,the perturbation method was introduced to avoid repeated computations of matrix exponential and terms due to external *** on the filtering and perturbation techniques,an adaptively filtered precise integration method considering perturbation for stochastic dynamics problems was *** numerical experiments,including a model of phononic crystal and a bridge model considering random parameters,were performed to test the performance of the proposed method in terms of accuracy and *** results show that the accuracy and efficiency of the proposed method are better than those of the existing precise integration method,the Newmark-βmethod and the Wilson-θmethod.

关键词： Precise integration method Stochastic dynamics problem Perturbation Filtered Computational efficiency

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A Transparent Polymer-Composite Film for Window Energy Conservation

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Nano-Micro Letters 2025年第7期17卷 9-19页

作者： Xianhu Liu Haoyu Zhang Yamin Pan Jun Ma Chuntai Liu Changyu Shen College of Materials Science and Engineering State Key Laboratory of Structural AnalysisOptimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou University Uni SA STEM and Future Industries Institute University of South Australia

As living standards improve, the energy consumption for regulating indoor temperature keeps increasing. Windows, in particular, enhance indoor brightness but also lead to increased energy loss, especially in sunny weather. Developing a product that can maintain indoor brightness while reducing energy consumption is a challenge. We developed a facile, spectrally selective transparent ultrahigh-molecular-weight polyethylene composite film to address this trade-off. It is based on a blend of antimony-doped tin oxide and then spin-coated hydrophobic fumed silica, achieving a high visible light transmittance(> 70%) and high shielding rates for ultraviolet(> 90%) and near-infrared(> 70%). When applied to the acrylic window of containers and placed outside, this film can cause a 10 ℃ temperature drop compared to a pure polymer film. Moreover, in building energy simulations, the annual energy savings could be between 14.1% ～ 31.9% per year. The development of energy-efficient and eco-friendly transparent films is crucial for reducing energy consumption and promoting sustainability in the window environment.

关键词： Composite Energy conservation Polymer Radiative cooling Transparent films

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Intelligent design of mechanical metamaterials: a GCNN-based structural genome database approach

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National Science Review 2025年第4期12卷 268-281页

作者： Wenyu Hao Zongliang Du Xiuquan Hou Yilin Guo Chang Liu Weisheng Zhang Huajian Gao Xu Guo State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDepartment of Engineering Mechanics Dalian University of Technology Ningbo Institute of Dalian University of Technology Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Mechano-X Institute Applied Mechanics LaboratoryDepartment of Engineering Mechanics Tsinghua University

The reciprocal mapping between the geometry and properties of a unit cell is crucial for the intelligent and inverse design of advanced materials and structural *** classical homogenization-based numerical methods,this paper presents an efficient and accurate mapping between the geometry and properties of a class of unit cells described by moving morphable components,achieved via a graph convolutional neural *** leads to a structural genome database(SGD) approach for the intelligent design of mechanical *** the SGD approach,metamaterials exhibiting the Hashin-Shtrikman upper bound of bulk modulus,auxetic behavior and the unimodal property have been created,with design efficiency improved by 3-4 orders of ***,transfer learning and a small amount of training data allow the SGD to predict non-local behaviors beyond a unit cell,such as optimized unit cells with critical buckling strength enhanced by nearly 200% and a bandgap metamaterial with a relative bandgap width of 51%.Experimentally validated optimized metamaterials demonstrate auxetic behavior and superior buckling *** proposed SGD approach holds promise for the advanced design of multi-scale and multi-physics systems.

关键词： mechanical metamaterial structural genome database moving morphable component graph convolutional neural network structure-property mapping

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On the evidential reasoning rule for dependent evidence combination

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Chinese Journal of Aeronautics 2023年第5期36卷 306-327页

作者： Peng ZHANG Zhijie ZHOU Shuaiwen TANG Jie WANG Guanyu HU Dao ZHAO You CAO Rocket Force University of Engineering Xi’an 710025China State Key Laboratory of Astronautic Dynamics Xi’an Satellite Control CenterXi’an 710043China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Evidential Reasoning(ER)rule,which can combine multiple pieces of independent evidence conjunctively,is widely applied in multiple attribute decision ***,the assumption of independence among evidence is often not satisfied,resulting in ER rule *** this paper,an Evidential Reasoning rule for Dependent Evidence combination(ERr-DE)is ***,the aggregation sequence of multiple pieces of evidence is determined according to evidence *** this basis,a calculation method of evidence Relative Total Dependence Coefficient(RTDC)is proposed using the distance correlation ***,as a discounting factor,RTDC is introduced into the ER rule framework,and the ERr-DE model is *** aggregation process of two pieces of dependent evidence by ERr-DE is investigated,which is then generalized to aggregate multiple pieces of non-independent ***,sensitivity analysis is carried out to investigate the relationship between the model output and the *** properties of sensitivity coefficient are explored and mathematically *** conjunctive probabilistic reasoning process of ERr-DE and the properties of sensitivity coefficient are verified by two numerical examples ***,the practical application of the ERr-DE is validated by a case study on the performance assessment of satellite turntable system.

关键词： Evidential reasoning rule Dependent evidence Relative total dependence coefficient Aggregation sequence Performance assessment

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Optimizing Monitoring Utility of Unmanned Aerial Vehicles Considering Adverse Effects

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5996-6013页

作者： Zhang, Haihan Dai, Haipeng Qiu, Yu Yu, Enze Zhou, Ruiben Wang, Weijun Wang, Jingwu Chen, Guihai Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China South China University of Technology School of Computer Science and Engineering Guangzhou China Beijing China

For Unmanned Aerial Vehicles (UAVs) monitoring tasks, capturing high quality images of target objects is important for subsequent recognition. Concerning the problem, many prior works study placement/trajectory planning for UAVs to maximize the quality of captured images. However, all of them overlook a fact that UAV monitoring may cause a huge risk/annoyance on living objects. In this paper, we investigate the novel problem of oPtimizing unmanned aErial vehicles plAcement by Considering both monitoring utility and adverse Effects (PEACE). We propose an approach to solve PEACE, which is proved to be NP-hard. Overall, our approach achieves a 1-1/e- approximation ratio. First, we approximate the original problem of PEACE as a classical problem of Monotone Submodular function Maximization under a Uniform Matroid constraint (MSMUM) with a controlled gap. Then, for MSMUM, we propose a combination of algorithms achieving a 1-1/e approximation and O(n\log n) time complexity considering the correlation among the UAV monitoring strategies. The proposed algorithms outperform existing algorithms for MSMUM through theoretical analysis and experimental results. Extensive simulations and field experiments demonstrate the effectiveness of our approach, achieving performance gains of 9.0% to 1434.5% compared to existing methods. © 2002-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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DYNAMIC REPLAY TRAINING FOR CLASS-INCREMENTAL LEARNING 49

DYNAMIC REPLAY TRAINING FOR CLASS-INCREMENTAL LEARNING

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49th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yang, Yan Ren, Dongdong Peng, Chenglei Huo, Jing Li, Wenbin Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China The School of Electronic Science and Engineering Nanjing University China

ISBN: (纸本)9798350344868;9798350344851

Replay-based methods for Class-Incremental Learning (CIL) typically employ new classes and a limited subset of old classes stored in memory to facilitate the model training. However, these methods often lead to class imbalance and catastrophic forgetting, where the model forgets previously learned tasks. While some studies have attempted to address such a class imbalance issue, they do not fully consider the dynamic nature of forgetting in the model. In this paper, we propose a novel method called Dynamic Replay Training (DRT) to address the dynamic forgetting of previously learned tasks by the model. DRT replays memory data with dynamically changing frequencies, offering a novel perspective to tackle catastrophic forgetting and class imbalance. The proposed method is evaluated on CIFAR-100 and ImageNet-100 in various settings, showing significant improvements of 8.28% and 4.53% in terms of classification accuracy compared to the baseline method on the two datasets, respectively.

关键词： Class Imbalance Catastrophic Forgetting Class-Incremental Learning Replay-based CIL

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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Structural evolution and high-temperature sensing performance of polymer-derived SiAlBCN ceramics

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Journal of Advanced Ceramics 2024年第4期13卷 478-485页

作者： Chao Ma Kun Liu Pengfei Shao Daoyang Han Kang Wang Mengmeng Yang Rui Zhao Hailong Wang Rui Zhang Gang Shao School of Materials Science and Engineering Zhengzhou UniversityZhengzhou 450001China Zhongyuan Critical Metal Laboratory Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentZhengzhou UniversityZhengzhou 450002China

In situ temperature monitoring has become extremely imperative in high-temperature harsh environments and polymer-derived ceramics(PDCs)as sensing materials have attracted great ***,the stability and oxidation/corrosion resistance of PDCs cannot be simultaneously achieved at the moment,limiting their practical ***,polymer-derived SiAlBCN ceramics were synthesized via polymer conversion method under different pyrolysis *** microstructure evolution,high temperature sensing properties,and stability were investigated in *** results show that the amorphous SiAlBCN phase grows more orderly and the size of the free carbon phase enlarges with the increasing *** defect concentration displays a decreasing ***,the SiAlBCN ceramics as sensing materials exhibit a good temperature-resistance property from roo temperature to 1100℃.The fabricated SiAlBCN temperature sensor possesses excellent stability,repeatability,and ***,SiAlBCN ceramics exhibit distinguished oxidation/corrosion resistance after 100 h treatment at 1200℃in a water/oxygen environment,which is attributed to their low corrosive rate constant(0.57 mg/(cm^(2)·h))and oxidative rate constant(3.43 mg^(2)/(cm^(4)·h)).Therefore,polymer-derived SiAlBCN ceramics as sensing materials,which possess outstanding stability and oxidation/corrosion resistance,have great potential for in-situ monitoring of extreme environmental temperatures in the future.

关键词： polymer-derived SiAlBCN ceramics temperature sensor harsh environments oxidation and corrosion resistance

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