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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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Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

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China Ocean engineering 2024年第2期38卷 247-254页

作者： YANG Zhi-xun YIN Xu FAN Zhi-rui YAN Jun LU Yu-cheng SU Qi MAO Yandong WANG Hua-lin Institute of marine machinery College of Mechanical and Electrical EngineeringHarbin Engineering UniversityHarbin 150001China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDepartment of Engineering MechanicsDalian University of TechnologyDalian 116024China Ningbo Institube of Dalian University of Technology Ningbo 315040China

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with *** layout of these components directly affects manufacturing,operation and storage performances of the *** the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage *** the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional ***,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent *** algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout *** feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate ***,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is ***,the multi-layering strategy is effective and *** design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

关键词： umbilical cross-sectional layout multi-layers GA-GLM optimization

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Migrant Resettlement by Evolutionary Multiobjective Optimization

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第1期6卷 51-65页

作者： Liu, Dan-Xuan Gu, Yu-Ran Qian, Chao Mu, Xin Tang, Ke Nanjing University National Key Laboratory for Novel Software Technology School of Artificial Intelligence Nanjing210023 China Peng Cheng Laboratory Shenzhen518000 China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China

Migration has been a universal phenomenon, which brings opportunities as well as challenges for global development. As the number of migrants (e.g., refugees) increases rapidly, a key challenge faced by each country is the problem of migrant resettlement. This problem has attracted scientific research attention, from the perspective of maximizing the employment rate. Previous works mainly formulated migrant resettlement as an approximately submodular optimization problem subject to multiple matroid constraints and employed the greedy algorithm, whose performance, however, may be limited due to its greedy nature. In this article, we propose a new framework called migrant resettlement by evolutionary multiobjective optimization (MR-EMO), which reformulates migrant resettlement as a biobjective optimization problem that maximizes the expected number of employed migrants and minimizes the number of dispatched migrants simultaneously, and employs a multiobjective evolutionary algorithm (MOEA) to solve the biobjective problem. We implement MR-EMO using three MOEAs: the popular nondominated sorting genetic algorithm II (NSGA-II), MOEA based on decomposition (MOEA/D) as well as the theoretically grounded global simple evolutionary multiobjective optimizer (GSEMO). To further improve the performance of MR-EMO, we propose a specific MOEA, called GSEMO using matrix-swap mutation and repair mechanism (GSEMO-SR), which has a better ability to search for feasible solutions. We prove that MR-EMO using either GSEMO or GSEMO-SR can achieve better theoretical guarantees than the previous greedy algorithm. Experimental results under the interview and coordination migration models clearly show the superiority of MR-EMO (with either NSGA-II, MOEA/D, GSEMO or GSEMO-SR) over previous algorithms, and that using GSEMO-SR leads to the best performance of MR-EMO. © 2024 IEEE.

关键词： Multiobjective optimization

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ER-Net:Efficient Recalibration Network for Multi-ViewMulti-Person 3D Pose Estimation

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Computer Modeling in engineering & Sciences 2023年第8期136卷 2093-2109页

作者： Mi Zhou Rui Liu Pengfei Yi Dongsheng Zhou National and Local Joint Engineering Laboratory of Computer Aided Design School of Software EngineeringDalian UniversityDalian116622China School of Computer Science and Technology Dalian University of TechnologyDalian116024China

Multi-view multi-person 3D human pose estimation is a hot topic in the field of human pose estimation due to its wide range of application *** the introduction of end-to-end direct regression methods,the field has entered a new stage of ***,the regression results of joints that are more heavily influenced by external factors are not accurate enough even for the optimal *** this paper,we propose an effective feature recalibration module based on the channel attention mechanism and a relative optimal calibration strategy,which is applied to themulti-viewmulti-person 3D human pose estimation task to achieve improved detection accuracy for joints that are more severely affected by external ***,it achieves relative optimal weight adjustment of joint feature information through the recalibration module and strategy,which enables the model to learn the dependencies between joints and the dependencies between people and their corresponding *** call this method as the Efficient Recalibration Network(ER-Net).Finally,experiments were conducted on two benchmark datasets for this task,Campus and Shelf,in which the PCP reached 97.3% and 98.3%,respectively.

关键词： Multi-view multi-person pose estimation attention mechanism computer vision

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Learning Hierarchical Adaptive Code Clouds for Neural 3D Shape Representation

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Machine Intelligence Research 2025年第2期22卷 304-323页

作者： Yuanxun Lu Xinya Ji Hao Zhu Xun Cao State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China School of Intelligence Science and Technology Nanjing UniversitySuzhou 215163China

Neural implicit representation(NIR)has attracted significant attention in 3D shape representation for its efficiency,generalizability,and flexibility compared with traditional explicit *** works usually parameterize shapes with neural feature grids/volumes,which prove to be inefficient for the discrete position constraints of the *** recent advances make it possible to optimize continuous positions for the latent codes,they still lack self-adaptability to represent various kinds of shapes *** this paper,we introduce a hierarchical adaptive code cloud(HACC)model to achieve an accurate and compact implicit 3D shape ***,we begin by assigning adaptive influence fields and dynamic positions to latent codes,which are optimizable during training,and propose an adaptive aggregation function to fuse the contributions of candidate latent codes with respect to query *** addition,these basic modules are stacked hierarchically with gradually narrowing influence field thresholds and,therefore,heuristically forced to focus on capturing finer structures at higher *** formulations greatly improve the distribution and effectiveness of local latent codes and reconstruct shapes from coarse to fine with high *** qualitative and quantitative evaluations both on single-shape reconstruction and large-scale dataset representation tasks demonstrate the superiority of our method over state-of-the-art approaches.

关键词： Representation learning shape analysis deep implicit function 3D reconstruction 3D modeling

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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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Outlier item detection in bundle recommendation via the attention mechanism

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High-Confidence Computing 2024年第3期4卷 51-57页

作者： Yuan Liang School of Information Engineering Suqian UniversitySuqian 223800China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Bundle recommendation offers users more holistic insights by recommending multiple compatible items at ***,the intricate correlations between items,varied user preferences,and the pronounced data sparsity in combinations present significant challenges for bundle recommendation ***,current bundle recommendation methods fail to identify mismatched items within a given set,a process termed as‘‘outlier item detection’’.These outlier items are those with the weakest correlations within a *** them can aid users in refining their item *** the correlation among items can predict the detection of such outliers,the adaptability of combinations might not be adequately responsive to shifts in individual items during the learning *** limitation can hinder the algorithm’s *** tackle these challenges,we introduce an encoder–decoder architecture tailored for outlier item *** encoder learns potential item correlations through a self-attention ***,the decoder garners efficient inference frameworks by directly assessing item *** have validated the efficacy and efficiency of our proposed algorithm using real-world datasets.

关键词： Bundle recommendation Outlier item detection Attention mechanism Decoder encoder

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Effect of boundary conditions on shakedown analysis of heterogeneous materials

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Applied Mathematics and Mechanics(English Edition) 2024年第1期45卷 39-68页

作者： Xiuchen GONG Yinghao NIE Gengdong CHENG Kai LI State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentInternational Research Center for Computational MechanicsDepartment of Engineering MechanicsDalian University of TechnologyDalian 116023Liaoning ProvinceChina

The determination of the ultimate load-bearing capacity of structures made of elastoplastic heterogeneous materials under varying loads is of great importance for engineering analysis and design. Therefore, it is necessary to accurately predict the shakedown domains of these materials. The static shakedown theorem, also known as Melan's theorem, is a fundamental method used to predict the shakedown domains of structures and materials. Within this method, a key aspect lies in the construction and application of an appropriate self-equilibrium stress field(SSF). In the structural shakedown analysis, the SSF is typically constructed by governing equations that satisfy no external force(NEF) boundary conditions. However, we discover that directly applying these governing equations is not suitable for the shakedown analysis of heterogeneous materials. Researchers must consider the requirements imposed by the Hill-Mandel condition for boundary conditions and the physical significance of representative volume elements(RVEs). This paper addresses this issue and demonstrates that the sizes of SSFs vary under different boundary conditions, such as uniform displacement boundary conditions(DBCs), uniform traction boundary conditions(TBCs), and periodic boundary conditions(PBCs). As a result, significant discrepancies arise in the predicted shakedown domain sizes of heterogeneous materials. Built on the demonstrated relationship between SSFs under different boundary conditions, this study explores the conservative relationships among different shakedown domains, and provides proof of the relationship between the elastic limit(EL) factors and the shakedown loading factors under the loading domain of two load vertices. By utilizing numerical examples, we highlight the conservatism present in certain results reported in the existing literature. Among the investigated boundary conditions, the obtained shakedown domain is the most conservative under ***, utilizing PBCs to

关键词： heterogeneous material self-equilibrium stress field(SSF) shakedown analysis effect of boundary conditions

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Understanding interfacial engineering of surface functionalized boron nitride nanosheets within thermal interface materials

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Science China Materials 2025年第4期68卷 1300-1302页

作者： Gaojie Han Yuezhan Fengg Changyu Shen State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China

The continuous miniaturization and high-power development of electronic devices have given rise to severe interface thermal issues,which urgently demand highly thermally conductive thermal interface materials(TIMs)to ... 详细信息

关键词： interfacial engineering heat accumulation interface thermal issueswhich thermal interface materials surface functionalized boron nitride nanosheets electronic devices thermal conductivity

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Competition for gradient-free tuning of large language models:approaches, results, current challenges and future directions

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National Science Review 2023年第6期10卷 16-19页

作者： Tingfeng Cao Liang Chen Dixiang Zhang Tianxiang Sun Zhengfu He Xipeng Qiu Xing Xu Hai Zhang School of Software Engineering South China University of Technology School of Computer Science Fudan University School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

PROBLEM Recent years have witnessed the rapid progress of self-supervised language models (LMs)[1],especially large language models (LLMs)[2].LLMs not only achieved state-of-the-art performance on many natural language processing tasks,but also captured widespread attention from the public due to their great potential in a variety of real-world applications (***,search engines,writing assistants,etc.)through providing general-purpose intelligent services.A few of the LLMs are becoming foundation models,an analogy to infrastructure,that empower hundreds of downstream applications.

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