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2nd International Conference on Advanced Measurement and Test (AMT 2011)

作者： Tian, Hongpeng Xian Univ Sci & Technol Coll Comp Sci & Technol Xian 710054 Shaanxi Peoples R China

ISBN: (纸本)9783037851975

To increase the speed of image matching, this paper combines bacterial foraging algorithm (BFA) of swarm intelligence with wavelet transform, and presents a fast matching method. The method regards the problem of image matching as a search for the optimal solution. To provide artificial bacterial swarm algorithm with an appropriate fitness function, the Normalized Product con:elation (NPROD) is employed to measure the similarity between the template image and the searching image. Then the best coarse matching position is gradually approaching by chemotaxis, elimination and dispersal, and reproduction behaviors of artificial bacterial. Finally, the best matching position is found out according to the coarse matching position. Experimental results show that the proposed method is fast and efficient.

关键词： image matching bacterial foraging algorithm swarm intelligence

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The decision model for the optimal configuration management of knowledge employees in enterprises

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Informatica (Slovenia) 2018年第2期42卷 273-278页

作者： Yang, Chunjiang Yang, Yujiang Tan, Xiuli Yantai Nanshan University Longkou Shandong China School of Mining Engineering University of Science and Technology Liaoning Anshan Liaoning China

With the development of knowledge economy, the role of knowledge employees in enterprises is becoming more and more important, and employees with rich knowledge represent the tower of strength in the development of enterprises. Knowledge employees with strong autonomy and creativity have stronger self-awareness in daily work. Thus, how to dispatch knowledge employees and assign them to proper positions, is of utter importance. To solve the problem of employee dispatch, bacterial foraging algorithm was proposed to optimize the configuration management of knowledge employees in enterprises in this study, a mathematical model based on the optimal configuration of knowledge employees was established, and a simulation experiment was carried out on the model. It was found that the algorithm could effectively optimize the configuration of knowledge employees. It is a feasible method for employee dispatch in enterprises. © 2018 Slovene Society Informatika. All rights reserved.

关键词： bacterial foraging algorithm Employee dispatch Knowledge employee

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Multi objective load frequency control using hybrid bacterial foraging and particle swarm optimized PI controller

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年 79卷 196-209页

作者： Dhillon, Sukhwinder Singh Lather, J. S. Marwaha, S. SLIET Elect & Instrumentat Engn Sangrur Punjab India NIT Dept Elect Engn Kurukshetra Haryana India Ambala Coll Engn & Appl Res Flat A-1 Ambala 133001 Haryana India

Excessive load demand with reliability in power availability, demands for interconnection of large number of generating units over existing tie lines. Due to sudden change in demand, the power transfer over existing tie lines working close to their thermal limits results in low frequency power oscillations. Thus, in modern power systems the study of mitigation of these frequency oscillations is more involved and formulates the area of Load Frequency Control (LFC). Many conventional and heuristic control techniques have been recently applied to address the issue of LFC. This paper investigates load frequency control of large interconnected power system consisting of conventional and renewable energy sources, using hybrid heuristic approach. The proposed strategy is shown to result in improved system damping resulting in faster mitigation of low frequency oscillations. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： LFC bacterial foraging algorithm Particle swarm optimization DFIG Multi objective Error analysis

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bacterial foraging algorithm with varying population

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BIOSYSTEMS 2010年第3期100卷 185-197页

作者： Li, M. S. Ji, T. Y. Tang, W. J. Wu, Q. H. Saunders, J. R. Univ Liverpool Dept Elect Engn & Elect Liverpool L69 3GJ Merseyside England Univ Liverpool Sch Biol Sci Liverpool L69 3GJ Merseyside England

Most of evolutionary algorithms (EAs) are based on a fixed population. However, due to this feature, such algorithms do not fully explore the potential of searching ability and are time consuming. This paper presents a novel nature-inspired heuristic optimization algorithm: bacterial foraging algorithm with varying population (BFAVP), based on a more bacterially-realistic model of bacterial foraging patterns, which incorporates a varying population framework and the underlying mechanisms of bacterial chemotaxis, metabolism, proliferation, elimination and quorum sensing. In order to evaluate its merits, BFAVP has been tested on several benchmark functions and the results show that it performs better than other popularly used EAs, in terms of both accuracy and convergency. Crown Copyright (C) 2010 Published by Elsevier Ireland Ltd. All rights reserved.

关键词： bacterial foraging algorithm bacterial colony behaviors Optimization

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An Enhanced bacterial foraging Optimization With Adaptive Elimination-dispersal Probability and PSO Strategy

An Enhanced Bacterial Foraging Optimization With Adaptive El...

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12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Mai Xiong-fa Li Ling Guangxi Teachers Educ Univ Minist Educ Key Lab Environm Change & Resources Use Beibu Gul Nanning 530001 Peoples R China Guangxi Univ Nationalities Guangxi Key Lab Hybrid Computat & IC Design Anal Naning 530006 Peoples R China Chengdu Univ Technol Coll Geophys 1 Dongsanlu Chengdu 610059 Sichuan Peoples R China Guangxi Teachers Educ Univ Guangxi Key Lab Earth Surface Proc & Intelligent Nanning 530001 Peoples R China

ISBN: (纸本)9781509040933

bacterial foraging Optimization(BFO) is a comparatively new optimization algorithm which learn from the foraging behavior of bacteria. The elimination and dispersal step is the major step of BFO to get the global search ability. An Enhanced bacterial foraging algorithm (EBFO) is presented in this paper, which is a variation of the original BFO algorithm. This new algorithm uses an adaptive elimination-dispersal probability according to bacterial fitness, meanwhile it carry out an Particle Swarm Optimization (PSO) operator just after the swim step. From the result of experiment on 6 benchmark functions, we can draw the following conclusions that the new algorithm has the advantages of better global searching ability, speeder convergence and more precise convergence

关键词： bacterial foraging algorithm Particle Swarm Optimization Adaptive Probability Benchmark

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Improving power quality with reducing output harmonics for electric vehicle applications by using bacteria foraging algorithm

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INTERNATIONAL JOURNAL OF ELECTRIC AND HYBRID VEHICLES 2016年第1期8卷 41-60页

作者： Farsadi, Murtaza Ahmadi, Monireh Urmia Univ Dept Elect Engn Orumiyeh *** Iran Islamic Azad Univ Urmia Branch Dept Elect Engn Orumiyeh *** Iran

The requirements for the power inverter of the electric vehicles ( EVs) include high peak power, low output harmonics, inexpensive circuit and low continuous power rating. The purpose of this paper is to reduce the output harmonics of a cascade H-bridge multilevel inverter for EV applications by means of a bacterial foraging algorithm ( BFA). In this study, the modified BFA is proposed as a technique for solving non-linear equations of selective harmonics elimination technique for determining optimal switching angles in multilevel inverters. The proposed optimisation method enhances the convergence rate and accuracy in dealing with complex problems with high dimensions, by adding improved and dynamic aspects to its main algorithm. Also, in this paper, a lower number of DC voltage sources have been used in the provided inverter compared with common multilevel inverters;this has resulted in the reduction in price of the inverter. Simulation results on various conditions were carried out using PSCAD/EMTDC software.

关键词： cascaded H-bridge multilevel inverter power quality modulation method switching angles harmonics BFA bacterial foraging algorithm

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Harmonic Elimination and Optimization of Stepped Voltage of Multilevel Inverter by bacterial foraging algorithm

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2010年第4期5卷 545-551页

作者： Reza-Salehi Behrooz-Vahidi Naeem-Farokhnia Mehrdad-Abedi Amikabir Univ Technol Dept Elect Engn Tehran Iran

A new family of DC to AC converters, referred to as multilevel inverter, has received much attention from industries and researchers for its high power and voltage applications. One of the conventional techniques for implementing the switching algorithm in these inverters is optimized harmonic stepped waveform (OHSW). However, the major problem in using this technique is eliminating low order harmonics by solving the nonlinear and complex equations. In this paper, a new approach called the "bacterial foraging algorithm" (BFA) is employed. This algorithm eliminates and optimizes the harmonics in a multilevel inverter. This method has higher speed, precision, and convergence power compared with the genetic algorithm (GA), a famous evolutionary algorithm. The proposed technique can be expanded in any number of levels. The purpose of optimization is to remove some low order harmonics, as well as to ensure the fundamental harmonic retained at the desired value. As a case study, a 13-level inverter is chosen. The comparison results by MATLAB software between the two optimization methods (BFA and GA) have shown the effectiveness and superiority of BFA over GA where convergence is desired to achieve global optimum.

关键词： Multilevel Inverter Harmonic Elimination bacterial foraging algorithm Genetic algorithm

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Economic emission load dispatch through fuzzy based bacterial foraging algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2010年第7期32卷 794-803页

作者： Hota, P. K. Barisal, A. K. Chakrabarti, R. UCE Dept Elect Engn Burla Orissa India Jadavpur Univ Dept Elect Engn Kolkata India

This paper presents a newly developed optimization approach involving a modified bacterial foraging algorithm (MBFA) applied for the solution of the economic and emission load dispatch (EELD) problem. The approach utilizes the natural selection of global optimum bacterium having successful foraging strategies in the fitness function. The bacterial foraging algorithm (BFA) appears to be a robust and reliable optimization algorithm for the solution of the EELD problems. To obtain the best compromising solution a fuzzy decision making approach using MBFA is applied to the standard IEEE 30-bus six generator test system and a Taiwan power system of 40 generating units with valve point loading effects. The results confirm the potential and effectiveness of the proposed algorithm compared to various methods such as, linear programming (LP), multi-objective stochastic search technique (MOSST), differential evolution (DE), non-dominated sorting genetic algorithm (NSGA), niched pareto genetic algorithm (NPGA), strength pareto evolutionary algorithm (SPEA) and fuzzy clustering based particle swarm optimization (FCPSO) performed in different central load dispatch centers to solve EELD problems. The quality and usefulness of the proposed algorithm is demonstrated through its application to two standard test systems in comparison with the other existing techniques. The current proposal was found to be better than, or at least comparable to them considering the quality of the solutions obtained. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Economic emission dispatch bacterial foraging algorithm Fuzzy decision making Multi-objective optimization

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Hysteretic Damping System Parameter Identification Based on HABC-CS algorithm 13

Hysteretic Damping System Parameter Identification Based on ...

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IEEE International Conference on Mechatronics and Automation

作者： Kang Weixin Ye Youdao Zhao Tianwei Wagan, Raja Asif Harbin Engn Univ Dept Informat & Commun Engn Harbin 150001 Peoples R China

ISBN: (纸本)9781509023967

Least squares estimate method in parameter identification of hysteretic damping system on the application of ubiquitous computing efficiency is not high, or complicated calculation, calculation accuracy is not high, there is always the problem such as error or error approximation ability is limited. Similar problem happened when inversion analysis of the defect is done in a component torsion wave propagation model, how to get these related parameters quickly and precisely with a good inversion algorithm is the main work we want to do. In this paper, an intelligent algorithm called HABC - CS algorithm is proposed. By introducing chaos search and bacterial foraging algorithm, adaptive probability of Boltzman, strengthen the ability of bacteria foraging behaviour, to speed up the global convergence of bees, improve the accuracy of solution to solve the existed problems of the least squares estimation method. Through the function test platform, the reliability of the HABC - CS algorithm is verified. And through the viscous damping system as an example, the Runge-Kutta algorithm is used to get the simulation data, and then the proposed algorithm is applied to identifying the parameters of hysteretic damping system. At last, the detailed process of parameter identification and the identification result of parameter identification of hysteretic damping system is given in this article.

关键词： parameter identification chaotic searching bacterial foraging algorithm adaptive probability Runge-Kutta algorithm

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Bio inspired BFA optimization for Inductor less Voltage gain Converter

Bio inspired BFA optimization for Inductor less Voltage gain...

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International Conference on Energy Efficient Technologies for Sustainability (ICEETS)

作者： Sivakumar, A. Premalatha, L. VIT Univ Sch Elect Engn Madras 127 Tamil Nadu India

ISBN: (纸本)9781467399258

The proposed research work deals with the execution of BFOA control for switched capacitor converter (SCC) with closed loop performance analysis. The above-culled converter is incipiently developed novel DC to DC converter with voltage hoist technique. The dynamic behavioural characteristics of power electronic converters is exceedingly nonlinear due to the nature of switching operation and unstable nature of time and, hence BFOA predicated bio-inspired controller is introduced for the developed novel converter[Intelligent swarm optimization network was developed for the current research work]. The closed loop performance investigation of the above converter utilizing software simulation (MATLAB) and proto type implementation with FPGA was validated. For the conditions like supply perturbances and load transmutes the performance of the converter is found to be preponderant.

关键词： Switched Capacitor converter MATLAB Direct Current bacterial foraging algorithm Field Programmable Gate Array

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