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Survey on Particle Swarm Optimization Algorithm

Yang Wei,Li Chiqiang

Strategic Study of CAE 2004, Volume 6, Issue 5,   Pages 87-94

Abstract:

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    

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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

Abstract:

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    

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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

Abstract:

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    

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Tumor Molecular Imaging with Nanoparticles Review

Zhen Cheng,Xuefeng Yan,Xilin Sun,Baozhong Shen,Sanjiv Sam Gambhir

Engineering 2016, Volume 2, Issue 1,   Pages 132-140 doi: 10.1016/J.ENG.2016.01.027

Abstract:

Molecular imaging (MI) can provide not only structural images using traditional imaging techniques but also functional and molecular information using many newly emerging imaging techniques. Over the past decade, the utilization of nanotechnology in MI has exhibited many significant advantages and provided new opportunities for the imaging of living subjects. It is expected that multimodality nanoparticles (NPs) can lead to precise assessment of tumor biology and the tumor microenvironment. This review addresses topics related to engineered NPs and summarizes the recent applications of these nanoconstructs in cancer optical imaging, ultrasound, photoacoustic imaging, magnetic resonance imaging (MRI), and radionuclide imaging. Key challenges involved in the translation of NPs to the clinic are discussed.

Keywords： Tumor     Molecular imaging     Nanoparticles    

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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

Abstract:

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    

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The horizontal distribution of a flight of steps when　the β-particles fly across the copper narrow slot

Zhu Yongqiang,Hao Jianyu

Strategic Study of CAE 2008, Volume 10, Issue 8,   Pages 81-86

Abstract:

This paper researches the electrons horizontal vibration when the electrons have high velocity. Its experimental method is using the characteristics that β-particles of 90Sr source in different magnetic fields by half circle-focus β- spectrum and in the same radius have different energy and momentum to study the functional relationship between the particle number (n) and the width of the copper narrow slot (δ) when the particles fly across the copper narrow slots with different widths (thickness is 8 mm)and find that the β-particles have the horizontal movement tendency no matter what energy and momentum the β-particles have, and when they fly across the copper narrow step there is the distribution of a flight of steps. The reason may be that β-particles have the horizontal amplitude A and the interaction of energy fluctuation in vacuum.

Keywords： the horizontal vibration of β-particles     the width of copper narrow slot     horizontal distribution of a flight of steps    

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Pulsed holography diagnosis of high-speed particles

Cao Na,Cao Liang,Xu Qing,Cui Guangbin,Ma Jiming,Zhang Zhanhong,Du Jiye,Dong Jingran

Strategic Study of CAE 2009, Volume 11, Issue 9,   Pages 48-51

Abstract:

Based on the theory of particle field holography, a set of corresponding pulsed holographic diagnostic system was developed, on which series of experiments were carried out. In this paper, the measuring principle of ejected particles shocked by explosive is analyzed simply, the assemblies of the diagnostic system and their functions are described, and the experiment results obtained with the system are showed. The results show that the system can realize the three-dimensional diagnosis of high-speed particles and meet the requirements of actual needs. Meanwhile, the developing direction of the application and the limitation of the system are pointed out.

Keywords： pulsed holography     particle field     diagnosis system     high-speed movement    

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A hybrid-model optimization algorithm based on the Gaussian process and particle swarm optimization for mixed-variable CNN hyperparameter automatic search Research Article

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

Abstract: s (CNNs) have been developed quickly in many real-world fields. However, CNN’s performance depends heavily on its hyperparameters, while finding suitable hyperparameters for CNNs working in application fields is challenging for three reasons: (1) the problem of encoding for different types of hyperparameters in CNNs, (2) expensive computational costs in evaluating candidate hyperparameter configuration, and (3) the problem of ensuring convergence rates and model performance during hyperparameter search. To overcome these problems and challenges, a hybrid-model optimization algorithm is proposed in this paper to search suitable hyperparameter configurations automatically based on the and (GPPSO) algorithm. First, a new encoding method is designed to efficiently deal with the CNN hyperparameter problem. Second, a hybrid-surrogate-assisted model is proposed to reduce the high cost of evaluating candidate hyperparameter configurations. Third, a novel activation function is suggested to improve the model performance and ensure the convergence rate. Intensive experiments are performed on imageclassification benchmark datasets to demonstrate the superior performance of GPPSO over state-of-the-art methods. Moreover, a case study on metal fracture diagnosis is carried out to evaluate the GPPSO algorithm performance in practical applications. Experimental results demonstrate the effectiveness and efficiency of GPPSO, achieving accuracy of 95.26% and 76.36% only through 0.04 and 1.70 GPU days on the CIFAR-10 and CIFAR-100 datasets, respectively.

Keywords： Convolutional neural network     Gaussian process     Hybrid model     Hyperparameter optimization     Mixed-variable     Particle swarm optimization    

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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

Abstract: 针对固有时间尺度分解算法的模态混叠问题和最小二乘支持向量机的参数优化问题，本文提出了一种新的基于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最小二乘支持向量机的柴油机故障诊断方法。最后，提出了混合差分进化和粒子群算法对最小二乘支持向量机的参数进行优化的方法，并通过将故障特征输入训练好的最小二乘支持向量机模型实现故障诊断。

Keywords： 柴油机；故障诊断；完备集合固有时间尺度分解；最小二乘支持向量机；混合差分进化和粒子群优化算法    

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The Electrically Controlled Flame Synthesis of Oxide Nanop article

Zhuang Qingping

Strategic Study of CAE 2007, Volume 9, Issue 2,   Pages 74-78

Abstract:

For precise control of the nanophase powder characteristics, electrically assisted hydrocarbon flames using electrodes have shown quite effective, either by ion or electron attachment, so the coagulation rate of the particles is reduced, as unipolarly charged particles repel each other. Charged particles are also attracted towards electrodes, thus lowering the local particle concentration and therefore the collision rate. The flame structure, height, and temperature are also altered by the electric field, which can significantly influence the particle residence time at high temperatures and therefore affect particle growth or sintering and crystallinity. It was shown that field generated by the electrodes across the flame decreases the particle residence time in the high temperature region of the flame.

Keywords： gas combustion     electrically controlled     flame     nanoparticle     aggregates    

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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

Abstract: Physiological signal based biometric analysis has recently attracted attention as a means of meeting increasing privacy and security requirements. The real-time nature of an electrocardiogram (ECG) and the hidden nature of the information make it highly resistant to attacks. This paper focuses on three major bottlenecks of existing deep learning driven approaches: the lengthy time requirements for optimizing the hyperparameters, the slow and computationally intense identification process, and the unstable and complicated nature of ECG acquisition. We present a novel deep neural network framework for learning feature representations directly from ECG time series. The proposed framework integrates deep bidirectional long short-term memory (BLSTM) and . The overall approach not only avoids the inefficient and experience-dependent search for hyperparameters, but also fully exploits the spatial information of ordinal local features and the memory characteristics of a recognition algorithm. The effectiveness of the proposed approach is thoroughly evaluated in two ECG datasets, using two protocols, simulating the influence of electrode placement and acquisition sessions in identification. Comparing four recurrent neural network structures and four classical machine learning and deep learning algorithms, we prove the superiority of the proposed algorithm in minimizing overfitting and self-learning of time series. The experimental results demonstrated an average identification rate of 97.71%, 99.41%, and 98.89% in training, validation, and test sets, respectively. Thus, this study proves that the application of APSO and LSTM techniques to biometric can achieve a lower algorithm engineering effort and higher capacity for generalization.

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    

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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

Abstract:

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    

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A scheduling method based on a hybrid genetic particle swarm algorithm for multifunction phased array radar Article

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

Abstract: A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic inter-leaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing parameters using chaos theory, designing the dynamic inertia weight for the particle swarm algorithm as well as introducing crossover operation and mutation operation of the genetic algorithm, both the efficiency and exploration ability of the hybrid algorithm are improved. Under the frame of the intelligence algorithm, the heuristic interleaving scheduling algorithm is presented to further use the time resource of the task waiting duration. A large-scale simulation demonstrates that the proposed algorithm is more robust and effi-cient than existing algorithms.

Keywords： Phased array radar     Scheduling     Particle swarm algorithm     Genetic algorithm     Pulse interleave    

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Effects of Structure of Opening Hole in Gas Distributor on Detained Mass of Material for Fluidized Drying

Liu Wei,Tang Wencheng

Strategic Study of CAE 2006, Volume 8, Issue 6,   Pages 41-43

Abstract:

The value of detained mass of material is important for researching the dead bed point of fluidized drying. In order to acquire the effect law of structure of opening hole in gas distributor on detained mass of material, the drying processes of detergent suspension liquor were investigated in the inert particle fluidized bed drier. The curves of detained mass of material for drier with vertical-hole distributor and tithed-hole distributor were measured and compared under the same experimental parameters, such as feed volume, diameter of inert particles, gas temperature of entrance, height of static bed, gas rate of entrance, and concentration of material. Based on the result, the relationship data of drier with tilted-hole distributor were determined between the production capacity and the hole ratio of distributor. The results show that the detained mass of material increase with adding the feed volume or concentration of material, and decrease with adding the diameter of inert particles, gas temperature of entrance, height of static bed, or gas rate of entrance. In addition, changing the hole shape of distributor from vertical-hole to tilted-hole and adding the hole ratio of distributor, can help drier reduce the detained mass of material and enhance the production capacity.

Keywords： inert particles     fluidized drying     gas distributor     hole shape     hole ratio     detained mass of material    

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Several Theoretical Problems in Faster-than-Light Research

Huang Zhixun,Geng Tianming

Strategic Study of CAE 2007, Volume 9, Issue 4,   Pages 6-17

Abstract:

In the early stage of the universe, during the hadronic era, the light velocity was larger than c,  in fact was v=75c. This implies that light velocity has been decreasing in time slowly, from v down to the present value c. On the other hand, based on the measurements of 128 quasar absorption lines, the average increase in fine-structure constantαwas6×10-6 over the past 6~12Ga. Scientists think it was aroused by the light-speed variation. It would be interesting to investigate if these facts have influenced the past history of the universe. This paper also discusses some problems of faster-than-light research profoundly, such as the velocity definition of the microscopic particles, the velocity of gravitation, the interaction speed of the quantum-entangle-state(QES), and the over distance action.

Keywords： variable light velocity     faster-than-light     velocity of microscopic particles     velocity ofgravitation     interaction speed of the QES     over distance action    

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Title Author Date Type Operation

Survey on Particle Swarm Optimization Algorithm

Yang Wei,Li Chiqiang

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

Tumor Molecular Imaging with Nanoparticles

Zhen Cheng,Xuefeng Yan,Xilin Sun,Baozhong Shen,Sanjiv Sam Gambhir

Journal Article

Using PSO to update pheromone for the traveling salesman problem

Cheng Weiming,Tang Zhenmin,Zhao Chunxia,Chen Debao

Journal Article

The horizontal distribution of a flight of steps when　the β-particles fly across the copper narrow slot

Zhu Yongqiang,Hao Jianyu

Journal Article

Pulsed holography diagnosis of high-speed particles

Cao Na,Cao Liang,Xu Qing,Cui Guangbin,Ma Jiming,Zhang Zhanhong,Du Jiye,Dong Jingran

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

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

俊红 张,昱 刘

Journal Article

The Electrically Controlled Flame Synthesis of Oxide Nanop article

Zhuang Qingping

Journal Article

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

Multi-objective particle swarm cooperative optimization algorithm for state parameters

Ding Lei,Wu Min,She Jinhua,Duan Ping

Journal Article

A scheduling method based on a hybrid genetic particle swarm algorithm for multifunction phased array radar

Hao-wei ZHANG, Jun-wei XIE, Wen-long LU, Chuan SHENG, Bin-feng ZONG

Journal Article

Effects of Structure of Opening Hole in Gas Distributor on Detained Mass of Material for Fluidized Drying

Liu Wei,Tang Wencheng

Journal Article

Several Theoretical Problems in Faster-than-Light Research

Huang Zhixun,Geng Tianming

Journal Article