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Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment 被引量:1
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作者 ZHAO Yang LIU Jicheng +1 位作者 JIANG Ju ZHEN Ziyang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第4期1007-1019,共13页
The dynamic weapon target assignment(DWTA)problem is of great significance in modern air combat.However,DWTA is a highly complex constrained multi-objective combinatorial optimization problem.An improved elitist non-d... The dynamic weapon target assignment(DWTA)problem is of great significance in modern air combat.However,DWTA is a highly complex constrained multi-objective combinatorial optimization problem.An improved elitist non-dominated sorting genetic algorithm-II(NSGA-II)called the non-dominated shuffled frog leaping algorithm(NSFLA)is proposed to maximize damage to enemy targets and minimize the self-threat in air combat constraints.In NSFLA,the shuffled frog leaping algorithm(SFLA)is introduced to NSGA-II to replace the inside evolutionary scheme of the genetic algorithm(GA),displaying low optimization speed and heterogeneous space search defects.Two improvements have also been raised to promote the internal optimization performance of SFLA.Firstly,the local evolution scheme,a novel crossover mechanism,ensures that each individual participates in updating instead of only the worst ones,which can expand the diversity of the population.Secondly,a discrete adaptive mutation algorithm based on the function change rate is applied to balance the global and local search.Finally,the scheme is verified in various air combat scenarios.The results show that the proposed NSFLA has apparent advantages in solution quality and efficiency,especially in many aircraft and the dynamic air combat environment. 展开更多
关键词 dynamic weapon-target assignment(DWTA)problem shuffled frog leaping algorithm(SFLA) air combat research
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Quantitative algorithm for airborne gamma spectrum of large sample based on improved shuffled frog leaping-particle swarm optimization convolutional neural network 被引量:1
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作者 Fei Li Xiao-Fei Huang +5 位作者 Yue-Lu Chen Bing-Hai Li Tang Wang Feng Cheng Guo-Qiang Zeng Mu-Hao Zhang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2023年第7期242-252,共11页
In airborne gamma ray spectrum processing,different analysis methods,technical requirements,analysis models,and calculation methods need to be established.To meet the engineering practice requirements of airborne gamm... In airborne gamma ray spectrum processing,different analysis methods,technical requirements,analysis models,and calculation methods need to be established.To meet the engineering practice requirements of airborne gamma-ray measurements and improve computational efficiency,an improved shuffled frog leaping algorithm-particle swarm optimization convolutional neural network(SFLA-PSO CNN)for large-sample quantitative analysis of airborne gamma-ray spectra is proposed herein.This method was used to train the weight of the neural network,optimize the structure of the network,delete redundant connections,and enable the neural network to acquire the capability of quantitative spectrum processing.In full-spectrum data processing,this method can perform the functions of energy spectrum peak searching and peak area calculations.After network training,the mean SNR and RMSE of the spectral lines were 31.27 and 2.75,respectively,satisfying the demand for noise reduction.To test the processing ability of the algorithm in large samples of airborne gamma spectra,this study considered the measured data from the Saihangaobi survey area as an example to conduct data spectral analysis.The results show that calculation of the single-peak area takes only 0.13~0.15 ms,and the average relative errors of the peak area in the U,Th,and K spectra are 3.11,9.50,and 6.18%,indicating the high processing efficiency and accuracy of this algorithm.The performance of the model can be further improved by optimizing related parameters,but it can already meet the requirements of practical engineering measurement.This study provides a new idea for the full-spectrum processing of airborne gamma rays. 展开更多
关键词 Large sample Airborne gamma spectrum(AGS) Shuffled frog leaping algorithm(SFLA) Particle swarm optimization(PSO) Convolutional neural network(CNN)
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Enhanced minimum attribute reduction based on quantum-inspired shuffled frog leaping algorithm 被引量:3
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作者 Weiping Ding Jiandong Wang +1 位作者 Zhijin Guan Quan Shi 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第3期426-434,共9页
Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial (NP)-hard problem. Therefore, it i... Attribute reduction in the rough set theory is an important feature selection method, but finding a minimum attribute reduction has been proven to be a non-deterministic polynomial (NP)-hard problem. Therefore, it is necessary to investigate some fast and effective approximate algorithms. A novel and enhanced quantum-inspired shuffled frog leaping based minimum attribute reduction algorithm (QSFLAR) is proposed. Evolutionary frogs are represented by multi-state quantum bits, and both quantum rotation gate and quantum mutation operators are used to exploit the mechanisms of frog population diversity and convergence to the global optimum. The decomposed attribute subsets are co-evolved by the elitist frogs with a quantum-inspired shuffled frog leaping algorithm. The experimental results validate the better feasibility and effectiveness of QSFLAR, comparing with some representa- tive algorithms. Therefore, QSFLAR can be considered as a more competitive algorithm on the efficiency and accuracy for minimum attribute reduction. 展开更多
关键词 minimum attribute reduction quantum-inspired shuf- fled frog leaping algorithm multi-state quantum bit quantum rotation gate and quantum mutation elitist frog.
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Membrane-inspired quantum shuffled frog leaping algorithm for spectrum allocation 被引量:2
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作者 Hongyuan Gao Jinlong Cao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第5期679-688,共10页
To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping(MQSFL) algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane... To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping(MQSFL) algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing. 展开更多
关键词 quantum shuffled frog leaping algorithm membrane computing spectrum allocation cognitive radio
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Improved Shuffled Frog Leaping Algorithm Optimizing Integral Separated PID Control for Unmanned Hypersonic Vehicle 被引量:2
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作者 梁冰冰 江驹 +1 位作者 甄子洋 马坤 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2015年第1期110-114,共5页
To solve the flight control problem for unmanned hypersonic vehicles,a novel intelligent optimized control method is proposed.A flight control system based on integral separated proportional-integral-derivative(PID)co... To solve the flight control problem for unmanned hypersonic vehicles,a novel intelligent optimized control method is proposed.A flight control system based on integral separated proportional-integral-derivative(PID)control is designed for hypersonic vehicle,and an improved shuffled frog leaping algorithm is presented to optimize the control parameters.A nonlinear model of hypersonic vehicle is established to examine the dynamic characteristics achieved by the flight control system.Simulation results demonstrate that the proposed optimized controller can effectively achieve better flight control performance than the traditional controller. 展开更多
关键词 hypersonic vehicles flight control shuffled frog leaping algorithm unmanned aerial vehicles(UAVs)
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Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm 被引量:1
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作者 Nour Ben Ammar Hegazy Rezk Soufiene Bouallègue 《Computers, Materials & Continua》 SCIE EI 2021年第6期4081-4100,共20页
This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler form... This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler formalism,a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes.Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law,which are usually selected by repetitive and time-consuming trials-errors based procedures,a constrained optimization problem is formulated for the systematically tuning of these unknown variables.Under time-domain operating constraints,such an optimization-based tuning problem is effectively solved using the proposed SFLA metaheuristic with an empirical comparison to other evolutionary computation-and swarm intelligence-based algorithms such as the Crow Search Algorithm(CSA),Fractional Particle Swarm Optimization Memetic Algorithm(FPSOMA),Ant Bee Colony(ABC)and Harmony Search Algorithm(HSA).Numerical experiments are carried out for various sets of algorithms’parameters to achieve optimal gains of the sliding mode controllers for the altitude and attitude dynamics stabilization.Comparative studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature convergence.Demonstrative results verified that the proposed metaheuristicsbased approach is a promising alternative for the systematic tuning of the effective design parameters in the integral sliding mode control framework. 展开更多
关键词 QUADROTOR MODELING integral sliding mode control gains tuning advanced metaheuristics memetic algorithms shuffled frog leaping algorithm
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Modified Shuffled Frog Leaping Algorithm for Solving Economic Load Dispatch Problem 被引量:2
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作者 Priyanka Roy A. Chakrabarti 《Energy and Power Engineering》 2011年第4期551-556,共6页
In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem... In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem which accounts for minimization of both generation cost and power loss is itself a multiple conflicting objective function problem. In this paper, a modified shuffled frog-leaping algorithm (MSFLA), which is an improved version of memetic algorithm, is proposed for solving the ELD problem. It is a relatively new evolutionary method where local search is applied during the evolutionary cycle. The idea of memetic algorithm comes from memes, which unlike genes can adapt themselves. The performance of MSFLA has been shown more efficient than traditional evolutionary algorithms for such type of ELD problem. The application and validity of the proposed algorithm are demonstrated for IEEE 30 bus test system as well as a practical power network of 203 bus 264 lines 23 machines system. 展开更多
关键词 ECONOMIC Load DISPATCH Modified Shuffled frog Leaping algorithm GENETIC algorithm
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A ε-indicator-based shuffled frog leaping algorithm for many-objective optimization problems
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作者 WANG Na SU Yuchao +2 位作者 CHEN Xiaohong LI Xia LIU Dui 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第1期142-155,共14页
Many-objective optimization problems take challenges to multi-objective evolutionary algorithms.A number of nondominated solutions in population cause a difficult selection towards the Pareto front.To tackle this issu... Many-objective optimization problems take challenges to multi-objective evolutionary algorithms.A number of nondominated solutions in population cause a difficult selection towards the Pareto front.To tackle this issue,a series of indicatorbased multi-objective evolutionary algorithms(MOEAs)have been proposed to guide the evolution progress and shown promising performance.This paper proposes an indicator-based manyobjective evolutionary algorithm calledε-indicator-based shuffled frog leaping algorithm(ε-MaOSFLA),which adopts the shuffled frog leaping algorithm as an evolutionary strategy and a simple and effectiveε-indicator as a fitness assignment scheme to press the population towards the Pareto front.Compared with four stateof-the-art MOEAs on several standard test problems with up to 50 objectives,the experimental results show thatε-MaOSFLA outperforms the competitors. 展开更多
关键词 evolutionary algorithm many-objective optimization shuffled frog leaping algorithm(SFLA) ε-indicator
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基于离散混合蛙跳算法的地震应急物资调度 被引量:1
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作者 申晓宁 葛忠佩 +2 位作者 姚铖滨 宋丽妍 王玉芳 《系统仿真学报》 CAS CSCD 北大核心 2024年第1期97-109,共13页
建立震后应急物资调度数学模型。该模型根据各灾区的受灾情况评估其救援紧急程度,并设计一种需求拆分供应的运输机制,提高车辆的利用效率。为求解该模型,提出一种多源信息学习的离散混合蛙跳算法。所提算法引入多种信息源以扩展算法的... 建立震后应急物资调度数学模型。该模型根据各灾区的受灾情况评估其救援紧急程度,并设计一种需求拆分供应的运输机制,提高车辆的利用效率。为求解该模型,提出一种多源信息学习的离散混合蛙跳算法。所提算法引入多种信息源以扩展算法的搜索方向,降低种群的同化速度。同时,让子组最差个体学习种群中的有效信息,提高算法的收敛精度。实验结果表明,所提算法能够搜索到精度更优的调度方案,对问题规模具有良好的可扩展性。 展开更多
关键词 应急物资调度 混合蛙跳算法 灾区紧急程度 需求拆分供应 车辆路径问题
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基于改进SFLA-Elman神经网络的电离层杂波抑制方法
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作者 刘强 尚尚 +2 位作者 乔铁柱 祝健 石依山 《电讯技术》 北大核心 2024年第6期848-856,共9页
针对高频地波雷达目标检测中电离层杂波的干扰问题,提出了一种基于改进混合蛙跳算法优化Elman神经网络预测抑制电离层杂波的策略。为解决混合蛙跳算法初始种群分布不均匀、收敛精度低、易陷于局部极值等问题,引入Cubic混沌映射、莱维飞... 针对高频地波雷达目标检测中电离层杂波的干扰问题,提出了一种基于改进混合蛙跳算法优化Elman神经网络预测抑制电离层杂波的策略。为解决混合蛙跳算法初始种群分布不均匀、收敛精度低、易陷于局部极值等问题,引入Cubic混沌映射、莱维飞行策略、非线性平衡因子和复制操作,增强种群多样性,提高算法搜索能力。利用改进后的算法和其他算法分别优化Elman神经网络预测抑制模型,结果表明,改进后的算法无论是在收敛精度和稳定性上,还是在临近距离单元电离层杂波的预测抑制上,都取得了显著的提升。在基本保留目标信号的基础上,平均信杂比较原始回波提升18.52 dB,较原始混合蛙跳算法提升1.08 dB,对于电离层杂波的抑制具有较高应用价值。 展开更多
关键词 高频地波雷达 电离层杂波抑制 混合蛙跳算法 ELMAN神经网络 莱维飞行
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基于RF-SFLA-SVM的装配式建筑高空作业工人不安全行为预警
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作者 王军武 何娟娟 +3 位作者 宋盈辉 刘一鹏 陈兆 郭婧怡 《中国安全科学学报》 CAS CSCD 北大核心 2024年第3期1-8,共8页
为有效预警装配式建筑高空作业工人不安全行为的发生趋势或状态,增强对装配式建筑工人不安全行为(PBWUBs)的管控,采用随机森林(RF)-混合蛙跳算法(SFLA)-支持向量机(SVM)模型,开展工人不安全行为预警研究。首先,采用SHEL模型分析处于高... 为有效预警装配式建筑高空作业工人不安全行为的发生趋势或状态,增强对装配式建筑工人不安全行为(PBWUBs)的管控,采用随机森林(RF)-混合蛙跳算法(SFLA)-支持向量机(SVM)模型,开展工人不安全行为预警研究。首先,采用SHEL模型分析处于高空作业危险中的PBWUBs的影响因素,并通过RF确定关键预警指标;然后,采用SFLA对SVM的参数进行寻优改进;最后,利用RF-SFLA-SVM预警高空作业PBWUBs,提出应对措施,并与其他预警模型对比。研究结果表明:基于RF-SFLA-SVM预警高空作业PBWUBs,准确率最高,为91.67%,与其他模型的预警性能相比,最高提升14%。研究结果可为高空作业PBWUBs的防控提供参考。 展开更多
关键词 随机森林(RF) 蛙跳算法(SFLA) 支持向量机(SVM) 装配式建筑 高空作业 不安全行为
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输电网中储能电站的智能预测系统设计
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作者 朱明 《自动化仪表》 CAS 2024年第6期63-67,共5页
针对输电网中风电场与储能电站的容量配置问题,设计了一种输电网中储能电站的智能预测系统。采用直流系统、站用电低压系统、监控系统、微机保护装置、测控装置、计量装置、人工智能、5G移动通信以及综合自动化设备,创建智能预测系统。... 针对输电网中风电场与储能电站的容量配置问题,设计了一种输电网中储能电站的智能预测系统。采用直流系统、站用电低压系统、监控系统、微机保护装置、测控装置、计量装置、人工智能、5G移动通信以及综合自动化设备,创建智能预测系统。通过基于混合蛙跳算法(SFLA)的人工智能,实现储能电站容量的计算、研究、预测,同时对储能电站进行优化配置。将外连接口与卡线器进行对接。通过传感设备采集检测单元需要的硬件信息、运行状态、设备情况和额定负载等数据,并对数据进行优化。试验结果表明,该系统在储能电站的预测精准度高达90%以上。该系统对解决电能浪费问题具有较强的实用性,也符合储能电站的特性。 展开更多
关键词 智能预测系统 混合蛙跳算法 测控装置 5G移动通信 人工智能
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数字图像混沌序列抽样加权强置乱算法仿真
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作者 贺国平 张国荣 《计算机仿真》 2024年第10期192-195,350,共5页
数字图像置乱关系到个人隐私和信息安全问题,为了保护图像中的敏感信息,提出一种基于位交换和混沌优化的数字图像置乱算法。使用散列函数获得数字图像明文的密钥流,采用与明文相关的子密钥推导像素初始值,通过非线性交叉生成位交换算子... 数字图像置乱关系到个人隐私和信息安全问题,为了保护图像中的敏感信息,提出一种基于位交换和混沌优化的数字图像置乱算法。使用散列函数获得数字图像明文的密钥流,采用与明文相关的子密钥推导像素初始值,通过非线性交叉生成位交换算子,增强明文信息敏感性;运用Logistic方程得到混沌序列,引入抽样加权方法提高图像置乱强度,采用混合蛙跳方法按照族群划分实施信息传输,将混沌序列内的实数从小到大排列,初始混沌抽样后构成的混沌序列用于图像中,显著提升图像置乱强度,完成数字图像置乱。仿真结果表明,上述方法拥有极高的安全性和优秀的加密性能,可以为数字图像在各领域的安全使用提供可靠借鉴。 展开更多
关键词 位交换 混沌优化 数字图像 置乱算法 敏感性增强 混合蛙跳方法
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混合蛙跳算法在旋转货架货位优化中的应用
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作者 屈新怀 杜志杰 《机械工程师》 2024年第10期53-57,共5页
以集群旋转式货架存储货物的自动化立体仓库为研究对象,以提高货架整体和运动状态的单层稳定性、货物相关性和出入库效率等基本货位优化原则为目标,提出一种通用性较强的多参数混合蛙跳算法,对多目标优化问题进行建模,使用MATLAB工具进... 以集群旋转式货架存储货物的自动化立体仓库为研究对象,以提高货架整体和运动状态的单层稳定性、货物相关性和出入库效率等基本货位优化原则为目标,提出一种通用性较强的多参数混合蛙跳算法,对多目标优化问题进行建模,使用MATLAB工具进行仿真。通过实验结果的对比可知,多参数混合蛙跳算法比混合蛙跳算法具有一定的优越性,并且对于分析其他问题的适应性较强,对于多目标优化问题具有一定的理论意义。 展开更多
关键词 自动化立体仓库 旋转式货架 货位优化 多目标优化 混合蛙跳算法
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混合蛙跳算法求解车辆无人机协同配送问题
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作者 段浩浩 李晓玲 +1 位作者 路庆昌 林杉 《浙江大学学报(工学版)》 EI CAS CSCD 北大核心 2024年第11期2258-2269,共12页
为了充分发挥无人机与车辆各自的优势,研究无人机起飞后可服务多个客户的车辆-无人机协同配送问题,其中考虑了车辆因区域限制、无人机因载重和续航限制导致2类运输工具配送范围均受到限制的约束.针对这类运输工具配送受限的车辆-多投递... 为了充分发挥无人机与车辆各自的优势,研究无人机起飞后可服务多个客户的车辆-无人机协同配送问题,其中考虑了车辆因区域限制、无人机因载重和续航限制导致2类运输工具配送范围均受到限制的约束.针对这类运输工具配送受限的车辆-多投递无人机协同配送问题(MDVCP-DR),以最小化总配送时间为优化目标,建立对应的数学模型,提出混合蛙跳算法(HSFLA)进行求解.提出新的编码与预调整解码方法,得到满足各种约束的可行解.建立基于4种交叉算子和精英表的个体生成方法,更新种群中的个体.设计自适应局部搜索策略来增强算法的局部开发能力,通过种群多样性检测策略来保证个体的多样性.通过仿真实验,验证了建立的数学模型的正确性和HSFLA的有效性. 展开更多
关键词 车辆-无人机 协同配送 配送限制 蛙跳算法 路径优化
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基于SFLA优化变分模态提取的滚动轴承故障诊断
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作者 张怀彬 陈志刚 +1 位作者 杨远鹏 王衍学 《振动与冲击》 EI CSCD 北大核心 2024年第10期132-139,173,共9页
为解决变分模态提取(variational mode extraction, VME)在分解轴承故障信号过程中近似中心频率和惩罚因子的选择过于依赖专家经验的问题,提出混合蛙跳算法(shuffled frog leaping algorithm, SFLA)与VME相结合的滚动轴承故障诊断方法... 为解决变分模态提取(variational mode extraction, VME)在分解轴承故障信号过程中近似中心频率和惩罚因子的选择过于依赖专家经验的问题,提出混合蛙跳算法(shuffled frog leaping algorithm, SFLA)与VME相结合的滚动轴承故障诊断方法。首先,为解决单一指标作为目标函数提取特征时信息不全面的问题,结合信息熵(information entropy, IE)、包络谱峭度和相关系数建立新的参数优化指标—KIC;然后,将KIC的极小值作为SFLA的目标函数自适应地选取VME期望模态的中心频率和惩罚因子;最后,通过包络解调分析期望模态进行故障诊断。仿真信号与轴承试验台相关数据集的分析结果表明,所提出的SFLA-VME方法能够准确地提取出期望模态并诊断轴承故障。 展开更多
关键词 滚动轴承 变分模态提取 混合蛙跳算法 包络谱峭度 信息熵
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基于改进混合蛙跳算法优化SVM的道岔故障诊断
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作者 孙波 孟庆虎 何晖 《铁道学报》 EI CAS CSCD 北大核心 2024年第7期81-90,共10页
针对道岔故障难以模拟导致的故障样本少、故障诊断困难等问题,提出一种改进混合蛙跳算法优化的支持向量机模型,基于小样本数据进行道岔故障诊断。支持向量机需要对参数择优选择,否则会造成过拟合或者欠拟合现象。将差分进化算法及模拟... 针对道岔故障难以模拟导致的故障样本少、故障诊断困难等问题,提出一种改进混合蛙跳算法优化的支持向量机模型,基于小样本数据进行道岔故障诊断。支持向量机需要对参数择优选择,否则会造成过拟合或者欠拟合现象。将差分进化算法及模拟退火算法与混合蛙跳算法相融合,解决了混合蛙跳算法易陷入局部最优的问题,并将其用于优化支持向量机参数,提高支持向量机模型的故障诊断能力。通过对实测数据进行试验,测试结果表明:在相同条件下,本文提出的模型比支持向量机模型与混合蛙跳算法优化的支持向量机模型的平均故障诊断准确率提高了34.28%,比仅融合差分进化算法的混合蛙跳算法优化的支持向量机模型的平均故障诊断准确率提高了5.71%。故障诊断结果表明,本文提出的方法对基于小样本数据的道岔故障诊断更加有效。 展开更多
关键词 道岔 故障诊断 支持向量机 混合蛙跳算法 模拟退火算法 差分进化算法
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基于IVMD算法的动车组滚动轴承故障特征提取方法研究
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作者 安国平 《智慧轨道交通》 2024年第1期10-14,60,共6页
动车组转向架滚动轴承的运行安全一直是影响列车安全运行的重要环节,目前国内外有多套监测体系进行了车载应用,但误报、漏报等现象时有发生,滚动轴承故障特征提取方法的准确性是该领域研究的重点之一。本文提出了一种基于改进的变分模... 动车组转向架滚动轴承的运行安全一直是影响列车安全运行的重要环节,目前国内外有多套监测体系进行了车载应用,但误报、漏报等现象时有发生,滚动轴承故障特征提取方法的准确性是该领域研究的重点之一。本文提出了一种基于改进的变分模态分解算法(Improved Variational Mode Decomposition,IVMD)的故障特征提取算法,采用混合蛙跳算法(Shuffled Frog Leaping Algorithm,SFLA)对模态数K和带宽控制参数α进行最优自适应选择。建立了基于包络熵、峭度和相关系数的多目标评价函数来选择最优模态分量。利用功效系数法将多目标优化问题转化为单目标优化问题,用频谱分析法对最优模态分量进行重构和处理。最后利用全实物电机轴承滚动实验台数据进行了方法的测试,有效验证了提出的改进方法分解故障信号及提取故障特征频率的准确性。 展开更多
关键词 动车组 滚动轴承 故障诊断 变分模态分解 混合蛙跳算法
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基于人工智能技术的复杂光学曲面加工轨迹跟踪 被引量:2
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作者 张樊 王晶 《激光杂志》 CAS 北大核心 2023年第11期209-213,共5页
为提升复杂光学曲面加工轨迹跟踪效果提出基于人工智能技术的复杂光学曲面加工轨迹跟踪方法。建立复杂光学曲面加工轨迹跟踪模型,改进蛙跳算法,提升参数优化效果;利用改进蛙跳算法,优化径向基函数神经网络权值,补偿加工轨迹跟踪模型误差... 为提升复杂光学曲面加工轨迹跟踪效果提出基于人工智能技术的复杂光学曲面加工轨迹跟踪方法。建立复杂光学曲面加工轨迹跟踪模型,改进蛙跳算法,提升参数优化效果;利用改进蛙跳算法,优化径向基函数神经网络权值,补偿加工轨迹跟踪模型误差,获取加工轨迹跟踪反馈控制律;设计加工轨迹跟踪控制器,完成加工轨迹跟踪。实验证明:对于简单与繁琐的复杂光学曲面零件,该方法均可精准跟踪加工轨迹;在车床进给速度为0.03 mm/r、0.04 mm/r和0.05 mm/r,步长为3时,应用该方法的加工轨迹跟踪误差最低,分别为0.03μm、0.04μm和0.05μm,与对比方法相比误差较低。 展开更多
关键词 人工智能技术 复杂光学 曲面加工 轨迹跟踪 蛙跳算法 神经网络
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基于改进蛙跳算法的多无人机协同任务分配研究 被引量:1
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作者 张耀中 赵雪芳 丰文成 《火力与指挥控制》 CSCD 北大核心 2023年第4期52-58,64,共8页
针对多无人机协同任务分配问题,提出了一种基于Levy飞行的改进随机蛙跳算法用于解决多无人机的协同任务预分配问题,通过引入动态跳跃步长、Levy飞行因子和族群认知因子有效改进了算法的搜索性能,提高了搜索效率。针对多无人机协同执行... 针对多无人机协同任务分配问题,提出了一种基于Levy飞行的改进随机蛙跳算法用于解决多无人机的协同任务预分配问题,通过引入动态跳跃步长、Levy飞行因子和族群认知因子有效改进了算法的搜索性能,提高了搜索效率。针对多无人机协同执行任务时可能遭遇的突发任务,通过引入市场拍卖机制提高了算法的计算收敛效率。通过仿真算例分析,验证了改进的随机蛙跳算法解决多无人机协同任务分配问题的有效性。 展开更多
关键词 多无人机协同任务 任务分配 随机蛙跳算法 拍卖机制
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