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Hybrid Framework for Structural Analysis: Integrating Topology Optimization, Adjacent Element Temperature-Driven Pre-Stress, and Greedy Algorithms 认领 引用
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作者 Ibrahim T.Teke Ahmet H.Ertas 《Computers, Materials & Continua》 SCIE EI 2025年第7期243-264,共22页
This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injecti... This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting,runner system optimization,and structural analysis to significantly enhance the performance of injection-molded parts.At its core,the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles,leading to improvements in both mechanical strength and material efficiency.The design optimization is validated through a series of rigorous experimental tests,including three-point bending and torsion tests performed on key-socket frames,ensuring that the optimized designs meet practical performance requirements.A critical innovation of the framework is the development of the Adjacent Element Temperature-Driven Prestress Algorithm(AETDPA),which refines the prediction of mechanical failure and strength fitting.This algorithm has been shown to deliver mesh-independent accuracy,thereby enhancing the reliability of simulation results across various design iterations.The framework’s adaptability is further demonstrated by its ability to adjust optimization methods based on the unique geometry of each part,thus accelerating the overall design process while ensuring struc-tural integrity.In addition to its immediate applications in injection molding,the study explores the potential extension of this framework to metal additive manufacturing,opening new avenues for its use in advanced manufacturing technologies.Numerical simulations,including finite element analysis,support the experimental findings and confirm that the optimized designs provide a balanced combination of strength,durability,and efficiency.Furthermore,the integration challenges with existing injection molding practices are addressed,underscoring the framework’s scalability and industrial relevance.Overall,this hybrid topology optimization framework offers a computationally efficient and robust solution for advanced manufacturing applications,promising significant improvements in design efficiency,cost-effectiveness,and product performance.Future work will focus on further enhancing algorithm robustness and exploring additional applications across diverse manufacturing processes. 展开更多
关键词 Plastic injection molding 3D printing three-point bending tensile test adjacent element temperature-driven pre-stress algorithm D-S-ER S-D-S-ER thermal expansion greedy algorithm
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An Iterated Greedy Algorithm with Memory and Learning Mechanisms for the Distributed Permutation Flow Shop Scheduling Problem 认领 引用
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作者 Binhui Wang Hongfeng Wang 《Computers, Materials & Continua》 SCIE EI 2025年第1期371-388,共18页
The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because o... The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling. 展开更多
关键词 Distributed permutation flow shop scheduling makespan iterated greedy algorithm memory mechanism cooperative reinforcement learning
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A greedy path planning algorithm based on pre-path-planning and real-time-conflict for multiple automated guided vehicles in large-scale outdoor scenarios 认领 引用 被引量：2
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作者 王腾达 WU Wenjun +2 位作者 YANG Feng SUN Teng GAO Qiang 《High Technology Letters》 EI CAS 2023年第3期279-287,共9页
With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path... With the wide application of automated guided vehicles(AGVs) in large scale outdoor scenarios with complex terrain,the collaborative work of a large number of AGVs becomes the main trend.The effective multi-agent path finding(MAPF) algorithm is urgently needed to ensure the efficiency and realizability of the whole system. The complex terrain of outdoor scenarios is fully considered by using different values of passage cost to quantify different terrain types. The objective of the MAPF problem is to minimize the cost of passage while the Manhattan distance of paths and the time of passage are also evaluated for a comprehensive comparison. The pre-path-planning and real-time-conflict based greedy(PRG) algorithm is proposed as the solution. Simulation is conducted and the proposed PRG algorithm is compared with waiting-stop A* and conflict based search(CBS) algorithms. Results show that the PRG algorithm outperforms the waiting-stop A* algorithm in all three performance indicators,and it is more applicable than the CBS algorithm when a large number of AGVs are working collaboratively with frequent collisions. 展开更多
关键词 automated guided vehicle(AGV) multi-agent path finding(MAPF) complex terrain greedy algorithm
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Using Greedy algorithm: DBSCAN revisited II 认领 引用 被引量：2
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作者 岳士弘 李平 +1 位作者 郭继东 周水庚 《Journal of Zhejiang University Science》 2004年第11期1405-1412,共8页
The density-based clustering algorithm presented is different from the classical Density-Based Spatial Clustering of Applications with Noise (DBSCAN) (Ester et al., 1996), and has the following advantages: first, Gree... The density-based clustering algorithm presented is different from the classical Density-Based Spatial Clustering of Applications with Noise (DBSCAN) (Ester et al., 1996), and has the following advantages: first, Greedy algorithm substitutes for R*-tree (Bechmann et al., 1990) in DBSCAN to index the clustering space so that the clustering time cost is decreased to great extent and I/O memory load is reduced as well; second, the merging condition to approach to arbitrary-shaped clusters is designed carefully so that a single threshold can distinguish correctly all clusters in a large spatial dataset though some density-skewed clusters live in it. Finally, authors investigate a robotic navigation and test two artificial datasets by the proposed algorithm to verify its effectiveness and efficiency. 展开更多
关键词 DBSCAN algorithm Greedy algorithm Density-skewed cluster
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Adaptive block greedy algorithms for receiving multi-narrowband signal in compressive sensing radar reconnaissance receiver 认领 引用
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作者 ZHANG Chaozhu XU Hongyi JIANG Haiqing 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第6期1158-1169,共12页
This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, ... This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications. 展开更多
关键词 compressive sensing(CS) adaptive greedy algorithm block sparsity analog-to-information convertor(AIC) multinarrowband signal
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Greedy Constructive Procedure-Based Hybrid Differential Algorithm for Flexible Flow shop Group Scheduling 认领 引用
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作者 郑永前 于萌萌 谢松杭 《Journal of Donghua University(English Edition)》 EI CAS 2015年第4期577-582,共6页
Aiming at the flexible flowshop group scheduling problem,taking sequence dependent setup time and machine skipping into account, a mathematical model for minimizing makespan is established,and a hybrid differential ev... Aiming at the flexible flowshop group scheduling problem,taking sequence dependent setup time and machine skipping into account, a mathematical model for minimizing makespan is established,and a hybrid differential evolution( HDE) algorithm based on greedy constructive procedure( GCP) is proposed,which combines differential evolution( DE) with tabu search( TS). DE is applied to generating the elite individuals of population,while TS is used for finding the optimal value by making perturbation in selected elite individuals. A lower bounding technique is developed to evaluate the quality of proposed algorithm. Experimental results verify the effectiveness and feasibility of proposed algorithm. 展开更多
关键词 flexible flowshop group scheduling hybrid differential evolution(HDE) algorithm greedy constructive procedure(GCP) lower bound
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Greedy Algorithm in m-Term Approximation for Periodic Besov Class with Mixed Smoothness 认领 引用
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作者 宋占杰 叶培新 《Transactions of Tianjin University》 EI CAS 2009年第1期75-78,共4页
Nonlinear m-term approximation plays an important role in machine learning, signal processing and statistical estimating. In this paper by means of a nondecreasing dominated function, a greedy adaptive compression num... Nonlinear m-term approximation plays an important role in machine learning, signal processing and statistical estimating. In this paper by means of a nondecreasing dominated function, a greedy adaptive compression numerical algorithm in the best m -term approximation with regard to tensor product wavelet-type basis is pro-posed. The algorithm provides the asymptotically optimal approximation for the class of periodic functions with mixed Besov smoothness in the L q norm. Moreover, it depends only on the expansion of function f by tensor pro-duct wavelet-type basis, but neither on q nor on any special features of f. 展开更多
关键词 greedy algorithm m -term approximation Besov space mixed smoothness
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Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags 认领 引用 被引量：4
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作者 Ning ZHAO Song YE +1 位作者 Kaidian LI Siyu CHEN 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2017年第3期652-662,共11页
Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem（PFSP with time lags） is concentrated but non-permutation problem（non-PFSP with time lags... Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem（PFSP with time lags） is concentrated but non-permutation problem（non-PFSP with time lags） seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algo- rithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation（IGTLP） and iterated greedy algorithm for non-permutation （IGTLNP）. The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% com- putational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation. 展开更多
关键词 Permutation Non-permutation Flow shopTime lags . Makespan Iterated greedy algorithm
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Dynamic thermal management by greedy scheduling algorithm 认领 引用 被引量：1
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作者 QU Shuang-xi ZHANG Min-xuan +1 位作者 LIU Guang-hui LIU Tao 《Journal of Central South University》 SCIE EI CAS 2012年第1期193-199,共7页
Chip multiprocessors(CMPs) allow thread level parallelism,thus increasing performance.However,this comes with the cost of temperature problem.CMPs require more power,creating non uniform power map and hotspots.Aiming ... Chip multiprocessors(CMPs) allow thread level parallelism,thus increasing performance.However,this comes with the cost of temperature problem.CMPs require more power,creating non uniform power map and hotspots.Aiming at this problem,a thread scheduling algorithm,the greedy scheduling algorithm,was proposed to reduce the thermal emergencies and to improve the throughput.The greedy scheduling algorithm was implemented in the Linux kernel on Intel's Quad-Core system.The experimental results show that the greedy scheduling algorithm can reduce 9.6%-78.5% of the hardware dynamic thermal management(DTM) in various combinations of workloads,and has an average of 5.2% and up to 9.7% throughput higher than the Linux standard scheduler. 展开更多
关键词 greedy scheduling algorithm chip multiprocessor thermal-aware
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A greedy algorithm based on joint assignment of airport gates and taxiways in large hub airports 认领 引用
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作者 Nie Tongtong Wu Wenjun +3 位作者 He Qichang Zhang Xuanyi Sun Yang Zhang Yanhua 《High Technology Letters》 EI CAS 2020年第4期417-423,共7页
With the rapid development of civil aviation in recent years,the management and assignment of airport resources are becoming more and more difficult.Among the various airport resources,gates and taxiways are very impo... With the rapid development of civil aviation in recent years,the management and assignment of airport resources are becoming more and more difficult.Among the various airport resources,gates and taxiways are very important,therefore,many researchers focus on the airport gate and taxiway assignment problem.However,the joint assignment algorithm of airport gates and taxiways with realistic airport data has not been well studied.A greedy algorithm based on joint assignment of airport gates and taxiways using the data of a large hub airport in China is proposed.The objective is maximizing the ratio of fixed gates and minimizing the ratio of taxiway collisions.Simulation results show that it outperforms other assignment schemes. 展开更多
关键词 greedy algorithm airport gate taxiway resources assignment
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Low Complexity Precoded Greedy Power Allocation Algorithms for OFDM Communication Systems 认领 引用 被引量：1
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作者 Najib A. Odhah Moawad I. Dessouky +1 位作者 Waleed Al-Hanafy Fathi E. Abd El-Samie 《Journal of Signal and Information Processing》 2012年第2期185-191,共7页
In this paper, an enhanced greedy bit and power allocation algorithms for orthogonal frequency division multiplexing (OFDM) communication systems are introduced. These algorithms combine low complexity greedy power al... In this paper, an enhanced greedy bit and power allocation algorithms for orthogonal frequency division multiplexing (OFDM) communication systems are introduced. These algorithms combine low complexity greedy power allocation algorithms with a simplified maximum ratio combining (MRC) precoding technique at the transmitter for maximizing the average data throughput of OFDM communication systems. Results of computer simulations show that precoding is an effective technique for improving the throughput performance of the proposed bit and power allocation algorithms. 展开更多
关键词 OFDM Uniform Power Allocation Greedy Algorithm Throughput Enhancement MRC Precoding
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Automatic piano performance interaction system based on greedy algorithm for dexterous manipulator 认领 引用
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作者 Yufei WANG Junfeng YAO +1 位作者 Yalan ZHOU Zefeng WANG 《虚拟现实与智能硬件（中英文）》 EI 2024年第6期473-485,共13页
With continuous advancements in artificial intelligence(AI), automatic piano-playing robots have become subjects of cross-disciplinary interest. However, in most studies, these robots served merely as objects of obser... With continuous advancements in artificial intelligence(AI), automatic piano-playing robots have become subjects of cross-disciplinary interest. However, in most studies, these robots served merely as objects of observation with limited user engagement or interaction. To address this issue, we propose a user-friendly and innovative interaction system based on the principles of greedy algorithms. This system features three modules: score management, performance control, and keyboard interactions. Upon importing a custom score or playing a note via an external device, the system performs on a virtual piano in line with user inputs. This system has been successfully integrated into our dexterous manipulator-based piano-playing device, which significantly enhances user interactions. 展开更多
关键词 Human-robot interaction Piano-playing robot Greedy algorithm Score parsing
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An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time 认领 引用
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作者 Xiaoqing Wang Peng Duan +1 位作者 Leilei Meng Kaidong Yang 《Computers, Materials & Continua》 SCIE EI 2024年第7期931-947,共17页
Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario.In this study,we investigated the post-disaster rescue path planning probl... Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario.In this study,we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem(TSP)with life-strength constraints.To address this problem,we proposed an improved iterated greedy(IIG)algorithm.First,a push-forward insertion heuristic(PFIH)strategy was employed to generate a high-quality initial solution.Second,a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability.Furthermore,three problem-specific swap operators were developed to improve the algorithm’s exploitation ability.Additionally,an improved simulated annealing(SA)strategy was used as an acceptance criterion to effectively prevent the algorithm from falling into local optima.To verify the effectiveness of the proposed algorithm,the Solomon dataset was extended to generate 27 instances for simulation.Finally,the proposed IIG was compared with five state-of-the-art algorithms.The parameter analysiswas conducted using the design of experiments(DOE)Taguchi method,and the effectiveness analysis of each component has been verified one by one.Simulation results indicate that IIGoutperforms the compared algorithms in terms of the number of rescue survivors and convergence speed,proving the effectiveness of the proposed algorithm. 展开更多
关键词 Rescue robot path planning life strength improved iterative greedy algorithm problem-specific swap operators
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Greedy Algorithm Applied to Relay Selection for Cooperative Communication Systems in Amplify-and-Forward Mode 认领 引用 被引量：1
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作者 Cheng-Ying Yang Yi-Shan Lin Jyh-Horng Wen 《Journal of Electronic Science and Technology》 CAS 2014年第1期49-53,共5页
Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be imp... Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward （AF） mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one. 展开更多
关键词 Amplify-and-forward mode cooperativecommunication exhaustive search greedy algorithm,relay selection.
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Efficient Resource Management in IoT Network through ACOGA Algorithm 认领 引用
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作者 Pravinkumar Bhujangrao Landge Yashpal Singh +1 位作者 Hitesh Mohapatra Seyyed Ahmad Edalatpanah 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第5期1661-1688,共28页
Internet of things networks often suffer from early node failures and short lifespan due to energy limits.Traditional routing methods are not enough.This work proposes a new hybrid algorithm called ACOGA.It combines A... Internet of things networks often suffer from early node failures and short lifespan due to energy limits.Traditional routing methods are not enough.This work proposes a new hybrid algorithm called ACOGA.It combines Ant Colony Optimization(ACO)and the Greedy Algorithm(GA).ACO finds smart paths while Greedy makes quick decisions.This improves energy use and performance.ACOGA outperforms Hybrid Energy-Efficient(HEE)and Adaptive Lossless Data Compression(ALDC)algorithms.After 500 rounds,only 5%of ACOGA’s nodes are dead,compared to 15%for HEE and 20%for ALDC.The network using ACOGA runs for 1200 rounds before the first nodes fail.HEE lasts 900 rounds and ALDC only 850.ACOGA saves at least 15%more energy by better distributing the load.It also achieves a 98%packet delivery rate.The method works well in mixed IoT networks like Smart Water Management Systems(SWMS).These systems have different power levels and communication ranges.The simulation of proposed model has been done in MATLAB simulator.The results show that that the proposed model outperform then the existing models. 展开更多
关键词 Energy management IoT networks ant colony optimization(ACO) greedy algorithm hybrid optimization routing algorithms energy efficiency network lifetime
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Sparse Recovery of Decaying Signals by the Piecewise Generalized Orthogonal Matching Pursuit Algorithm 认领 引用
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作者 Hanbing LIU Chongjun LI 《Journal of Mathematical Research with Applications》 CSCD 2025年第6期813-834,共22页
In this paper,we focus on the recovery of piecewise sparse signals containing both fast-decaying and slow-decaying nonzero entries.In order to improve the performance of classic Orthogonal Matching Pursuit(OMP)and Gen... In this paper,we focus on the recovery of piecewise sparse signals containing both fast-decaying and slow-decaying nonzero entries.In order to improve the performance of classic Orthogonal Matching Pursuit(OMP)and Generalized Orthogonal Matching Pursuit(GOMP)algorithms for solving this problem,we propose the Piecewise Generalized Orthogonal Matching Pursuit(PGOMP)algorithm,by considering the mixed-decaying sparse signals as piecewise sparse signals with two components containing nonzero entries with different decay factors.The algorithm incorporates piecewise selection and deletion to retain the most significant entries according to the sparsity of each component.We provide a theoretical analysis based on the mutual coherence of the measurement matrix and the decay factors of the nonzero entries,establishing a sufficient condition for the PGOMP algorithm to select at least two correct indices in each iteration.Numerical simulations and an image decomposition experiment demonstrate that the proposed algorithm significantly improves the support recovery probability by effectively matching piecewise sparsity with decay factors. 展开更多
关键词 piecewise sparse recovery decaying sparse signals mutual coherence greedy algorithm
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Numerical Studies of the Generalized l1Greedy Algorithm for Sparse Signals 认领 引用
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作者 Fangjun Arroyo Edward Arroyo +2 位作者 Xiezhang Li Jiehua Zhu Jiehua Zhu 《Advances in Computed Tomography》 2013年第4期132-139,共8页
The generalized l1 greedy algorithm was recently introduced and used to reconstruct medical images in computerized tomography in the compressed sensing framework via total variation minimization. Experimental results ... The generalized l1 greedy algorithm was recently introduced and used to reconstruct medical images in computerized tomography in the compressed sensing framework via total variation minimization. Experimental results showed that this algorithm is superior to the reweighted l1-minimization and l1 greedy algorithms in reconstructing these medical images. In this paper the effectiveness of the generalized l1 greedy algorithm in finding random sparse signals from underdetermined linear systems is investigated. A series of numerical experiments demonstrate that the generalized l1 greedy algorithm is superior to the reweighted l1-minimization and l1 greedy algorithms in the successful recovery of randomly generated Gaussian sparse signals from data generated by Gaussian random matrices. In particular, the generalized l1 greedy algorithm performs extraordinarily well in recovering random sparse signals with nonzero small entries. The stability of the generalized l1 greedy algorithm with respect to its parameters and the impact of noise on the recovery of Gaussian sparse signals are also studied. 展开更多
关键词 Compressed Sensing Gaussian Sparse Signals l1-Minimization Reweighted l1-Minimization l1 Greedy Algorithm Generalized l1 Greedy Algorithm
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Quality or Quantity?Error-Informed Selective Online Learning With Gaussian Processes in Multi-Agent Systems 认领 引用 被引量：1
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作者 Zewen Yang Xiaobing Dai +2 位作者 Jiajun Cheng Yulong Huang Peng Shi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1325-1338,共14页
Effective cooperation is pivotal in distributed learning for multi-agent systems,where the interplay between the quantity and quality of the machine learning models is crucial.This paper reveals the irrationality of i... Effective cooperation is pivotal in distributed learning for multi-agent systems,where the interplay between the quantity and quality of the machine learning models is crucial.This paper reveals the irrationality of indiscriminate inclusion of all models on agents for joint prediction,highlighting the imperative to prioritize quality over quantity in cooperative learning.Specifically,we present the first selective online learning framework for distributed Gaussian process(GP)regression,namely distributed error-informed GP(EIGP),that enables each agent to assess its neighboring collaborators,using the proposed selection function to choose the higher quality GP models with less prediction errors.Moreover,algorithmic enhancements are embedded within the EIGP,including a greedy algorithm(gEIGP)for accelerating prediction and an adaptive algorithm(aEIGP)for improving prediction accuracy.In addition,approaches for fast prediction and model update are introduced in conjunction with the error-informed quantification term iteration and a data deletion strategy to achieve real-time learning operations.Numerical simulations are performed to demonstrate the effectiveness of the developed methodology,showcasing its superiority over the stateof-the-art distributed GP methods with different benchmarks. 展开更多
关键词 Adaptive algorithm cooperative learning distributed learning Gaussian process regression greedy algorithm multi-agent system
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基于负荷可行域和可靠性跟踪的电力系统扩容规划及其求解算法 认领 引用 被引量：2
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作者 李轩 谢开贵 +1 位作者 邵常政 胡博 《上海交通大学学报》 EI CAS CSCD 北大核心 2026年第2期200-210,I0003,共11页
电力系统可靠性评估计算复杂度高,难以嵌入电力系统扩容规划模型中.为了实现考虑可靠性的系统扩容规划,提出一种基于负荷可行域和可靠性跟踪的电力系统扩容规划模型及其求解算法.建立基于负荷可行域的近似距离模型,将可靠性评估中的切... 电力系统可靠性评估计算复杂度高,难以嵌入电力系统扩容规划模型中.为了实现考虑可靠性的系统扩容规划,提出一种基于负荷可行域和可靠性跟踪的电力系统扩容规划模型及其求解算法.建立基于负荷可行域的近似距离模型,将可靠性评估中的切负荷计算从优化问题求解转变为方程求解,降低可靠性评估计算复杂度.基于近似距离模型,建立可靠性指标对设备容量的灵敏度模型,实现针对设备容量的可靠性跟踪.最后提出以可靠性提升为目标的电力系统扩容规划模型,以及基于可靠性跟踪和贪心算法的优化求解算法.结果表明:近似距离模型能够有效降低可靠性评估的计算复杂度;灵敏度模型能够正确反映设备容量变化对系统可靠性的影响;扩容规划模型及求解算法能够达到最优的系统扩容规划结果. 展开更多
关键词 扩容规划 可靠性跟踪 负荷可行域 近似距离模型 贪心算法
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基于图拓扑结构和贪心算法的锚点选取优化 认领 引用 被引量：1
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作者 戴邵武 顾昊伦 《华南理工大学学报（自然科学版）》 EI CAS CSCD 北大核心 2026年第4期84-100,共17页
针对基于数据分发服务的分散式组网导航系统(DDS-DNNS)的锚点选取问题,构建了节点位置图以及节点位置估计模型,并将锚点选取问题表述为固定基数约束下最大化Fisher信息矩阵的D-最优度量问题,以此为基础,设计了基于图拓扑结构的DDS-DNNS... 针对基于数据分发服务的分散式组网导航系统(DDS-DNNS)的锚点选取问题,构建了节点位置图以及节点位置估计模型,并将锚点选取问题表述为固定基数约束下最大化Fisher信息矩阵的D-最优度量问题,以此为基础,设计了基于图拓扑结构的DDS-DNNS锚点选取优化算法。该算法利用图拓扑结构与Fisher信息矩阵D-最优度量之间的联系,将最大化Fisher信息矩阵的D-最优度量近似转化为最大化降维加权Laplacian矩阵的对数行列式值,并基于集合函数相关性质以及Cauchy交错定理证明了近似优化模型是一个非正则、非单调、非负的子模最大化问题,由此设计了包含基于近似最小度排序的稀疏Cholesky分解、惰性评估、矩阵维度保持及置换向量复用、Cholesky分解结果复用的改进贪心算法,用以求解近似优化模型,同时证明了该算法能提供近似优化性能保证,并具有远小于经典随机贪心算法的计算复杂度。最后,通过算例仿真比较了不同算法下位置估计效果、解算时间与锚点数量的关系,得到了固定基数约束的选取准则,验证了改进贪心算法在不同锚点数量下均能保证较高的估计精度,并有效降低计算复杂度。 展开更多
关键词 锚点选取 图拓扑 D-最优度量 集合函数 子模性 改进贪心算法
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