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ECGID: a human identification method based on adaptive particle swarm optimization and the bidirectional LSTM model Research Article
Yefei Zhang, Zhidong Zhao, Yanjun Deng, Xiaohong Zhang, Yu Zhang,zhangyf@hdu.edu.cn,zhaozd@hdu.edu.cn,yanjund@hdu.edu.cn,xhzhang@hdu.edu.cn,zy2009@hdu.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 12, Pages 1551-1684 doi: 10.1631/FITEE.2000511
Keywords: 心电图生物特征;个体身份识别;长短期记忆网络;自适应粒子群优化算法
Survey on Particle Swarm Optimization Algorithm
Yang Wei,Li Chiqiang
Strategic Study of CAE 2004, Volume 6, Issue 5, Pages 87-94
Particle swarm optimization (PSO) is a new optimization technique originating from artificial life and evolutionary computation. The algorithm completes the optimization through following the personal best solution of each particle and the global best value of the whole swarm. PSO can be implemented with ease and few parameters need to be tuned. It has been successfully applied in many areas. In this paper, the basic principles of PSO are introduced at length, and various improvements and applications of PSO are also presented. Finally, some future research directions about PSO are proposed.
Keywords: swarm intelligence evolutionary algorithm particle swarm optimization
Application prospect of PSO in hydrology
Dong Qianjin,Cao Guangjing,Wang Xianjia,Dai Huichao,Zhao Yunfa
Strategic Study of CAE 2010, Volume 12, Issue 1, Pages 81-85
The basic algorithm and its flow are introduced at first, then its application to scheduling operation of reservoir, economic operation of hydropower and parameter calibration in hydrology field is discussed, the suggestion for future study is pointed out that should strengthen the study of adaptive mechanism and convergence performance in PSO, compare and combine with other technology, broaden the region of application to hydrology which may supply a new method for solving much optimal problem in hydrology field.
Keywords: hydrology science particle swarm optimization scheduling operation economical operation
Solving Knapsack Problem by Hybrid Particle Swarm Optimization Algorithm
Gao Shang,Yang Jingyu
Strategic Study of CAE 2006, Volume 8, Issue 11, Pages 94-98
The classical particle swarm optimization is a powerful method to find the minimum of a numerical function, on a continuous definition domain. The particle swarm optimization algorithm combining with the idea of the genetic algorithm is recommended to solve knapsack problem. All the 6 hybrid particle swarm optimization algorithms are proved effective. Especially the hybrid particle swarm optimization algorithm derived from across strategy A and mutation strategy C is a simple yet effective algorithm and it has been applied successfully to investment problem. It can easily be modified for any combinatorial problem for which there has been no good specialized algorithm.
Keywords: particle swarm algorithm knapsack problem genetic algorithm mutation
Ali Darvish FALEHI,Ali MOSALLANEJAD
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 3, Pages 394-409 doi: 10.1631/FITEE.1500317
Suppression of the dynamic oscillations of tie-line power exchanges and frequency in the affected interconnected power systems due to loading-condition changes has been assigned as a prominent duty of automatic generation control (AGC). To alleviate the system oscillation resulting from such load changes, implementation of flexible AC transmission systems (FACTSs) can be considered as one of the practical and effective solutions. In this paper, a thyristor-controlled series compensator (TCSC), which is one series type of the FACTS family, is used to augment the overall dynamic performance of a multi-area multi-source interconnected power system. To this end, we have used a hierarchical adaptive neuro-fuzzy inference system controller-TCSC (HANFISC-TCSC) to abate the two important issues in multi-area interconnected power systems, i.e., low-frequency oscillations and tie-line power exchange deviations. For this purpose, a multi-objective optimization technique is inevitable. Multi-objective particle swarm optimization (MOPSO) has been chosen for this optimization problem, owing to its high performance in untangling non-linear objectives. The efficiency of the suggested HANFISC-TCSC has been precisely evaluated and compared with that of the conventional MOPSO-TCSC in two different multi-area interconnected power systems, i.e., two-area hydro-thermal-diesel and three-area hydro-thermal power systems. The simulation results obtained from both power systems have transparently certified the high performance of HANFISC-TCSC compared to the conventional MOPSO-TCSC.
Keywords: Hierarchical adaptive neuro-fuzzy inference system controller (HANFISC) Thyristor-controlled series compensator (TCSC) Automatic generation control (AGC) Multi-objective particle swarm optimization (MOPSO) Power system dynamic stability Interconnected multi-source power systems
应用完备集合固有时间尺度分解和混合差分进化和粒子群算法优化的最小二乘支持向量机对柴油机进行故障诊断 Article
俊红 张,昱 刘
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2, Pages 272-286 doi: 10.1631/FITEE.1500337
Han YAN, Chongquan ZHONG, Yuhu WU, Liyong ZHANG, Wei LU
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 11, Pages 1557-1573 doi: 10.1631/FITEE.2200515
Keywords: Convolutional neural network Gaussian process Hybrid model Hyperparameter optimization Mixed-variable Particle swarm optimization
Multi-objective particle swarm cooperative optimization algorithm for state parameters
Ding Lei,Wu Min,She Jinhua,Duan Ping
Strategic Study of CAE 2010, Volume 12, Issue 2, Pages 101-107
To deal with the characters with the strong nonlinear and complex computing of synthetic permeability and burn-through point in the lead-zinc sintering process, an efficient multi-objective particle swarm cooperative optimization algorithm is proposed. Firstly, the multi-objective optimization model for burn-through point and synthetic permeability is established. Secondly, an improved multi-objective particle swarm cooperative optimization algorithm is presented by improving the constraint comparison method and the way of selecting the particles' optima, and using different swarms to optimize corresponding variables respectively. Finally, the proposed multi-objective optimization algorithm is applied to optimize the synthetic permeability and the burn-through point. The simulation results show that the proposed multi-objective optimization algorithm effectively solves the optimization problem of the synthetic permeability and burn-through point.
Keywords: lead-zinc sintering process synthetic permeability burn-through point multi-objective particle swarm cooperative optimization algorithm
Control of Velocity-Constrained Stepper Motor-Driven Hilare Robot for Waypoint Navigation Article
Robins Mathew,Somashekhar S. Hiremath
Engineering 2018, Volume 4, Issue 4, Pages 491-499 doi: 10.1016/j.eng.2018.07.013
Finding an optimal trajectory from an initial point to a final point through closely packed obstacles, and controlling a Hilare robot through this trajectory, are challenging tasks. To serve this purpose, path planners and trajectory-tracking controllers are usually included in a control loop. This paper highlights the implementation of a trajectory-tracking controller on a stepper motor-driven Hilare robot, with a trajectory that is described as a set of waypoints. The controller was designed to handle discrete waypoints with directional discontinuity and to consider different constraints on the actuator velocity. The control parameters were tuned with the help of multi-objective particle swarm optimization to minimize the average cross-track error and average linear velocity error of the mobile robot when tracking a predefined trajectory. Experiments were conducted to control the mobile robot from a start position to a destination position along a trajectory described by the waypoints. Experimental results for tracking the trajectory generated by a path planner and the trajectory specified by a user are also demonstrated. Experiments conducted on the mobile robot validate the effectiveness of the proposed strategy for tracking different types of trajectories.
Keywords: Trajectory tracking Adaptive control Waypoint navigation Hilare robot Particle swarm optimization Probabilistic road map
Prediction of vibration response of powerhouse structures based on LS-SVM optimized by PSO
Lian Jijian,He Longjun,Wang Haijun
Strategic Study of CAE 2011, Volume 13, Issue 12, Pages 45-50
The vibration of powerhouse structures is mainly induced by hydraulics factors, mechanical and electromagnetic factors of the generating unit. It nonlinearly couples with the generating unit. Based on prototype observation data of Ertan Hydropower Station, the paper analyzes the coupling effect between vibration of units and powerhouse,and then the vibration response forecasting model of the powerhouse is built based on LS-SVM optimized by particle swarm optimization algorithm, and the prediction results are coincide with the observed data. Further, the paper introduces the running water head as an input divisor into the intelligent prediction model while the forecasting range is extended, and the result is satisfactory.
Keywords: powerhouse coupled vibration particle swarm optimization algorithm least squares support vector machines response prediction
Xing-chen WU, Gui-he QIN, Ming-hui SUN, He YU, Qian-yi XU
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 9, Pages 1385-1395 doi: 10.1631/FITEE.1601427
Keywords: Cooperative collision avoidance system (CCAS) Improved particle swarm optimization (PSO) PID controller Vehicle comfort Fuel economy
Using PSO to update pheromone for the traveling salesman problem
Cheng Weiming,Tang Zhenmin,Zhao Chunxia,Chen Debao
Strategic Study of CAE 2008, Volume 10, Issue 7, Pages 165-168
Using pheromone of ant coloney system as reference, a novel method of solving TSP problem is proposed. That is using particle swarm optimization ( PSO) . PSO is used because of its simple operation, easy implementation and faster speed. In order to improve the popularity of the particle swarm,make the particle swam not to homogeneous too fast and decrease the possibility of local constrain, the algorithm decides the number of degenerated particles based on a designated popularity function.Experiment results and comparison studies have demonstrated that our work is useful.
Keywords: pheromone particle swarm algorithm TSP
Research on economic operation of microgrid with high temperature energy storage system
Luo Yi and Zhang Lijuan
Strategic Study of CAE 2015, Volume 17, Issue 1, Pages 74-80
With the advantages of high efficiency, environmental protection and energy conservation, the high energy storage system has extensive application prospect, economic operation is becoming a wide concerned issue on microgrid with high temperature energy storage system. By analyzing the microgrid with high temperature energy storage system, based on the characteristics of each micro-source, the model of high temperature energy storage system and economic operation model of the grid-connected microgrid are constructed with time-sharing electricity. The improved immune particle swarm algorithm is used to solve the proposed model, and then field application verifies the effectiveness of model. Results show that the proposed method and model can reach the globally optimal solution of dynamic microgrid, and it is of cost saving and significant economic benefit for high temperature energy storage system to participate in thermal load supplying.
Lin CAO, Shuo TANG, Dong ZHANG
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7, Pages 882-897 doi: 10.1631/FITEE.1601363
Keywords: Air-breathing hypersonic vehicles (AHVs) Stochastic robustness analysis Linear-quadratic regulator (LQR) Particle swarm optimization (PSO) Improved hybrid PSO algorithm
Hao-wei ZHANG, Jun-wei XIE, Wen-long LU, Chuan SHENG, Bin-feng ZONG
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11, Pages 1806-1816 doi: 10.1631/FITEE.1601358
Keywords: Phased array radar Scheduling Particle swarm algorithm Genetic algorithm Pulse interleave
Title Author Date Type Operation
ECGID: a human identification method based on adaptive particle swarm optimization and the bidirectional LSTM model
Yefei Zhang, Zhidong Zhao, Yanjun Deng, Xiaohong Zhang, Yu Zhang,zhangyf@hdu.edu.cn,zhaozd@hdu.edu.cn,yanjund@hdu.edu.cn,xhzhang@hdu.edu.cn,zy2009@hdu.edu.cn
Journal Article
Application prospect of PSO in hydrology
Dong Qianjin,Cao Guangjing,Wang Xianjia,Dai Huichao,Zhao Yunfa
Journal Article
Solving Knapsack Problem by Hybrid Particle Swarm Optimization Algorithm
Gao Shang,Yang Jingyu
Journal Article
RETRACTED ARTICLE: Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO
Ali Darvish FALEHI,Ali MOSALLANEJAD
Journal Article
A hybrid-model optimization algorithm based on the Gaussian process and particle swarm optimization for mixed-variable CNN hyperparameter automatic search
Han YAN, Chongquan ZHONG, Yuhu WU, Liyong ZHANG, Wei LU
Journal Article
Multi-objective particle swarm cooperative optimization algorithm for state parameters
Ding Lei,Wu Min,She Jinhua,Duan Ping
Journal Article
Control of Velocity-Constrained Stepper Motor-Driven Hilare Robot for Waypoint Navigation
Robins Mathew,Somashekhar S. Hiremath
Journal Article
Prediction of vibration response of powerhouse structures based on LS-SVM optimized by PSO
Lian Jijian,He Longjun,Wang Haijun
Journal Article
Using improved particle swarm optimization totune PID controllers in cooperative collision avoidance systems
Xing-chen WU, Gui-he QIN, Ming-hui SUN, He YU, Qian-yi XU
Journal Article
Using PSO to update pheromone for the traveling salesman problem
Cheng Weiming,Tang Zhenmin,Zhao Chunxia,Chen Debao
Journal Article
Research on economic operation of microgrid with high temperature energy storage system
Luo Yi and Zhang Lijuan
Journal Article
Flight control for air-breathing hypersonic vehicles using linear quadratic regulator design based on stochastic robustness analysis
Lin CAO, Shuo TANG, Dong ZHANG
Journal Article