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1st International Conference on Swarm Intelligence

作者： Liu, Suqin Wang, Jing Li, Xingsheng Shuo, Jun Liu, Huihui China Univ Petr Coll Comp Commun Engn Qingdao 266555 Peoples R China

ISBN: (纸本)9783642134975

The job scheduling technology is an effective way to achieve resource sharing and to improve computational efficiency. Scheduling problem has been proved to be NP-complete problems, Particle Swarm Optimization (pso) algorithm has demonstrated outstanding performance in solving such issues. In cognizance of the characteristics of cluster scheduling problem, a schedule strategy based on pso was designed and implemented. Comparing with backfilling algorithm, pso algorithm can improve the fairness of jobs better. It can avoid the problem that bigger jobs can't be executed quickly. The speed and accuracy of strategy generation are improved significantly. The experiment results show that the scheduling strategy based on pso algorithm can increase the utilization of the CPU and reduce average response time significantly.

关键词： scheduling strategy cluster pso algorithm design implement

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The Computation of Concept Similarity Based on pso algorithm

The Computation of Concept Similarity Based on PSO Algorithm

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2nd IEEE International Conference on Information and Financial Engineering (ICIFE)

作者： Liu, Jia Wang, HuaYu Shandong Normal Univ Sch Informat Sci & Engn Jinan Peoples R China

ISBN: (纸本)9781424469284

Ontology heterogeneity restricts the application of ontology. The key of ontology mapping is to compute concept similarity. At present, the method of similarity computation is imperfect. And the computation quantity is high. In order to decrease computation quantity and completely compute concept similarity, the influences of relations and attributes is considered and use candidate set. In this paper, a computation method of similarity based on pso algorithm is proposed. At first, the semantic similarity and descriptive similarity of concepts are computed. Then the attribute priority is specified by pso algorithm. At last, the attribute with high priority is chosen according to the user need. Take two ontologies as example and compute concept similarity. Experiments results show that this calculative method can improve the precision of similarity and reduce the calculated quantity.

关键词： Ontology mapping Concept similarity pso algorithm Priority

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Research on Intrusion Detection algorithm Based on BP Neural Network

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INTERNATIONAL JOURNAL OF SECURITY AND ITS APPLICATIONS 2015年第4期9卷 259-270页

作者： Qiu, Chunmin Shan, Jie Binzhou Polytechn Binzhou Shandong 256603 Peoples R China

In recent years, the problem of network security has been more and more people's attention, as one of the most important technology of network security, intrusion detection technology has gone through nearly thirty years of development, but it still exists some deficiency factors. Aiming at the defects of the traditional BP neural network intrusion detection model in the detection rate and the convergence speed, the improved pso-BP neural network is applied to intrusion detection system model in this paper. Experimental and simulation, verifying the improved effect of system in the false negative rate, false positives rate and convergence speed of Detailed analysis of the standard BP neural network algorithm and improved way of common, including gradient descent algorithm and additional momentum algorithm. Local search capability of BP neural network and the global search ability of particle swarm optimization, we have a detailed description of the pso algorithm is applied to the case of BP neural network and discusses the improved pso-BP neural network algorithm flow.

关键词： Intrusion Detection BP Neural Network pso algorithm

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pso-optimized modular neural network trained by OWO-HWO algorithm for fault location in analog circuits

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NEURAL COMPUTING & APPLICATIONS 2013年第2期23卷 519-530页

作者： Sheikhan, Mansour Sha'bani, Amir Ali Islamic Azad Univ South Tehran Branch Fac Engn Dept Elect Engn Tehran Iran

Fault diagnosis of analog circuits is a key problem in the theory of circuit networks and has been investigated by many researchers in recent decades. In this paper, an active filter circuit is used as the circuit under test (CUT) and is simulated in both fault-free and faulty conditions. A modular neural network model is proposed in this paper for soft fault diagnosis of the CUT. To optimize the structure of neural network modules in the proposed scheme, particle swarm optimization (pso) algorithm is used to determine the number of hidden layer nodes of neural network modules. In addition, the output weight optimization-hidden weight optimization (OWO-HWO) training algorithm is employed, instead of conventional output weight optimization-backpropagation (OWO-BP) algorithm, to improve convergence speed in training of the neural network modules in proposed modular model. The performance of the proposed method is compared to that of monolithic multilayer perceptrons (MLPs) trained by OWO-BP and OWO-HWO algorithms, K-nearest neighbor (KNN) classifier and a related system with the same CUT. Experimental results show that the pso-optimized modular neural network model which is trained by the OWO-HWO algorithm offers higher correct fault location rate in analog circuit fault diagnosis application as compared to the classic and monolithic investigated neural models.

关键词： Fault diagnosis Modular neural model Analog circuits pso algorithm OWO-HWO algorithm

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A particle swarm inspired multi-elitist artificial bee colony algorithm for real-parameter optimization

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2014年第2期57卷 493-516页

作者： Xiang, Yi Peng, Yuming Zhong, Yubin Chen, Zhenyu Lu, Xuwen Zhong, Xuejun Guangdong Baiyun Univ Dept Basic Courses Guangzhou 510450 Guangdong Peoples R China Guangzhou Univ Sch Math & Informat Sci Guangzhou 510006 Guangdong Peoples R China

The Artificial Bee Colony (ABC) algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behavior of honey bee colonies. In this work, a particle swarm inspired multi-elitist ABC algorithm named PS-MEABC is proposed and applied for real-parameter optimization. In this modified version, the global best solution and an elitist randomly selected from the elitist archive are used to modify parameters of each food source in either onlooker bees or employed bees phases. PS-MEABC is compared with 5 state-of-the-art swarm based algorithms on CEC05 and BBOB12 benchmark functions in terms of four metrics: the mean error, the best error, the success rate (SR) and the expected running time (ERT). Wilcoxon signed ranks test results on the mean and the best error show that the performance of PS-MEABC is significantly better than or at least similar to these algorithms, and PS-MEABC has wider application range in terms of the success rate and faster convergence speed in terms of the expected running time. Our algorithm is comparable to its competitors with a fewer control parameters to be tuned.

关键词： Artificial bee colony algorithm Multi-elitist preservation strategy pso algorithm Wilcoxon signed ranks test

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An integrated approach for optimal placement and tuning of power system stabilizer in multi-machine systems

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 63卷 132-139页

作者： Keumarsi, Vahid Simab, Mohsen Shahgholian, Ghazanfar Islamic Azad Univ Dept Elect Engn Najafabad Branch Najafabad Iran Islamic Azad Univ Dept Elect Engn Coll Engn Fars Sci & Res Branch Fars Iran

In this paper, a hybrid approach for tuning and placement of power system stabilizers (PSS) in multi-machine power systems is provided with the aim of reducing low-frequency oscillations (LFO) and improving power system dynamic stability with wide range of changes in system parameters and operating point of the system. PSS parameters are adjusted using Particle Swarm Optimization algorithm (pso), and using Takagi-Sugeno (TS) fuzzy, optimal location for the PSS is determined. The employed fuzzy system has two inputs, the real part and the damping coefficient of network eigenvalues. The results of test on a grid four machine-two area sample, show optimal performance of the proposed method in improving system stability and reducing low-frequency oscillations of local and inter-area modes. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Power system stabilizer Tuning and placement of PSS pso algorithm Fuzzy logic Multi-machine system

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OPTIMIZATION OF IMAGE SEGMENTATION BASED ON A VISUAL POSITIONING SYSTEM FOR DISPENSING MACHINES

OPTIMIZATION OF IMAGE SEGMENTATION BASED ON A VISUAL POSITIO...

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International Copmputer Conference on Wavelet Active Miedia Technology and Information Processing

作者： JIALI YANG HONG HU JIAYU XU Shenzhen Key Lab of Advanced Manufacturing Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong Province (518055) China

ISBN: (纸本)9781467382670

Although dispensing technology plays an important part in the chip packaging process, most dispensing methods are inefficient. A visual positioning system for dispensing machines will greatly improve the efficiency. The key to visual positioning is an image processing technique that, among other things, includes image preprocessing and image segmentation. In this paper, we use the Otsu algorithm to provide segmentation of the original image and then apply the particle swarm optimization (pso) algorithm to optimize the speed and accuracy of the image. By comparing the result with the exhaustion threshold segmentation algorithm we obtain the segmentation time and threshold, which shows that the pso algorithm significantly improves the image processing speed.

关键词： Dispensing Image segmentation pso algorithm

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Two-Stage Force Particle Swarm Optimization algorithm and Application in Hydraulic System Reliability Optimization

Two-Stage Force Particle Swarm Optimization Algorithm and Ap...

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2015 International Conference on Fluid Power and Mechatronics

作者： Chengyu Yao Xueyun Tan Dongning Chen Shijun Lv Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Key Lab of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University

In view of the particle swarm optimization(pso) algorithm's shortages of easily trapping into local optimum and premature convergence, an improvement research from the perspective of interaction mechanism among particles is made in this paper. Consider advantages and disadvantages of the current improved pso algorithms from the aspect of force, the two-stage force particle swarm optimization(TFpso) algorithm is proposed. The proposed algorithm, which employs staged search strategy to achieve a trade-off between global exploration and local exploitation abilities, divides search process into two stages and constructs corresponding force rules combining with the idea of attractive and repulsive forces in artificial physics. In order to demonstrate the performance of the proposed algorithm in solving optimization problems, TFpso algorithm is compared with some well-known pso algorithms in reliability optimization for hydraulic system. Comparison results show that TFpso algorithm obtains the best optimization results and enhances the performance of pso in terms of accuracy of the optimal solution and local search ability.

关键词： pso algorithm force rule TFpso algorithm reliability optimization hydraulic system

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A pso Optimized Fractional-Order PID Controller for a PV System with DC-DC Boost Converter 16

A PSO Optimized Fractional-Order PID Controller for a PV Sys...

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16th International Power Electronics and Motion Control Conference and Exposition (PEMC)

作者： Sahin, Erdinc Ayas, Mustafa Sinasi Altas, Ismail Hakki Karadeniz Tech Univ Surmene Abdullah Kanca VHS Trabzon Turkey Karadeniz Tech Univ Dept Elect & Elect Engn Trabzon Turkey

ISBN: (纸本)9781479920600

In this study, a fractional-order PID (FOPID) controller is designed to control a DC-DC boost converter in a PV-system. Because of the nonlinear V-I characteristic of a PV-panel, a power electronic interface is required to obtain a desired and fixed voltage level. In order to obtain the best system performance, parameters of the proposed controller are tuned by using Particle Swarm Optimization (pso) algorithm. Both of the system responses with the FOPID and classical PID are tested under various power conditions by changing the load resistor and solar irradiation values. The simulation results are compared in terms of integral of time weighted squared error (ITSE) criterion, percentage overshoot (M-p) and rising time (T-r). The results show that the FOPID controller performs better performance than the classical PID controller.

关键词： component FOPID controller PID controller PV panel Boost converter pso algorithm

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Substitution of G.728 vocoder's codebook search module with SOM array trained by pso-optimized supervised algorithm

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NEURAL COMPUTING & APPLICATIONS 2013年第7-8期23卷 2309-2321页

作者： Sheikhan, Mansour Garoucy, Sahar Islamic Azad Univ South Tehran Branch Dept Elect Engn Fac Engn Tehran Iran

Low delay-code excited linear prediction (LD-CELP) is an attractive algorithm in implementing vocoders in voice over Internet protocol networks. This algorithm has been proposed for the coding of speech at 16 kbps with toll quality. However, operation at transmission rates lower than 16 kbps is desirable, so that traffic can be accommodated during system overload conditions. In this paper, an array of self-organizing maps (SOMs) is employed instead of traditional codebook search module, recommended in ITU-T G.728, to determine the optimum index value of shape codebook. It is noted that a modified supervised training algorithm is used for SOMs in which some of the training parameters are optimized using particle swarm optimization (pso) algorithm. Based on the occurrence frequency characteristics of codevectors, six bits for shape codebook and two bits for gain codebook are used in this work to produce a vocoder with lower bit rate as compared with traditional ITU-T G.728 vocoder. The performance comparison of the proposed SOM array trained by pso-optimized supervised algorithm as the codebook search module in the structure of LD-CELP with a conventional implementation of LD-CELP coder shows that execution time of the algorithm is reduced up to 44 %. However, the degradation of voice quality in terms of mean opinion score, perceived evaluation of speech quality and segmental signal-to-noise ratio (SNRseg) is acceptable.

关键词： Vocoder Array of SOMs LD-CELP Codebook search module pso algorithm

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