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IEEE Swarm Intelligence Symposium

作者： del Valle, Y. Digman, M. Gray, A. Perkel, J. Venayagamoorthy, G. K. Harley, R. G. Georgia Inst Technol Dept Elect & Comp Engn Atlanta GA 30332 USA Univ Missouri Sci & Technol Dept Elect & Comp Engn Real Time Power & Intelligent Syst Lab Rolla 65409 MO USA

ISBN: (纸本)9781424427048

Power system networks are complex systems that are highly nonlinear and non-stationary, and therefore, their performance is difficult to optimize using traditional optimization techniques. This paper presents an enhanced particle swarm optimizer for solving constrained optimization problems for power system applications, in particular, the optimal allocation of multiple STATCOM units. The study focuses on the capability of the algorithm to find feasible solutions in a highly restricted hypergpace. The performance of the enhanced particle swarm optimizer is compared with the classical particle swarm optimization (PSO) algorithm, genetic algorithm (GA) and bacterial foraging algorithm (BFA). Results show that the enhanced PSO is able to find feasible solutions faster and converge to feasible regions more often as compared with other algorithms. Additionally, the enhanced PSO is capable of finding the global optimum without getting trapped in local minims.

关键词： Flexible AC Transmission Systems (FACTS) Static VAR compensators Particle Swarm Optimization Genetic algorithm bacterial foraging algorithm

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Extraction of Retinal Vasculature using Optimization Methods

Extraction of Retinal Vasculature using Optimization Methods

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2020 International Conference on System, Computation, Automation and Networking, ICSCAN 2020

作者： Kalyani, A. Jasmine Chalcedony, C. Sri Madhava Raja, N. Valli, R. St. Joseph's College of Engineering Omr Department of Electronics and Instrumentation Engineering Chennai600119 India Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering Pondicherry605107 India

ISBN: (纸本)9781728162027

A healthy retina is required for proper vision but it is difficult to identify the retinal diseases in the first stage. Several retinal diseases affect the eye such as retinal tear, detachment of retina, glaucoma, macular hole and macular degeneration etc. Since most of these diseases have an effect on the blood vessels within the eye, analyzing the structure and variation in feature of retinal blood vessels help in identifying the disease and its severity. In this paper, we are extracting the blood vessels from retinal fundus image using Tsallis entropy principle and bacterial foraging algorithm. The retinal images are obtained from red-free fundus photography. The performance of this algorithm is compared and analyzed with ground-Truth images of DRIVE database. © 2020 IEEE.

关键词： bacterial foraging algorithm Red-free Fundus Photography Retinal vasculature Tsallis Entropy

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Improved dual-population cooperative bacterial colony algorithm for solving distributed flexible job shop scheduling problem 24

Improved dual-population cooperative bacterial colony algori...

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3rd International Symposium on Control Engineering and Robotics, ISCER 2024

作者： Xun, Xuebin Xu, Keke Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment Zhengzhou University of Light Industry Zhengzhou450002 China

ISBN: (纸本)9798400709951

An improved two-population collaborative bacterial colony algorithm is proposed for the distributed flexible job shop scheduling problem. Different initialization schemes are designed for the two populations to improve the quality and diversity of the initial solutions;different cross-mutation operators are designed for the two populations during the convergence operation to achieve a balance between the exploration and development of the algorithm;on the basis of the method of exchanging elite individuals to perform the replication operation, two migration methods are designed to complete the separation of the populations and the generation of the new populations, which in turn realizes the collaborative optimization between the two populations;Designing the corresponding local search for key plants to improve the local search capability of the algorithm. Finally, fifteen test algorithms are obtained by utilizing the generalized test set of the extended flexible job shop, and twenty-five sets of comparative tests are designed by using the orthogonal test method for parameter selection. Comparing with the existing algorithms, the experimental results confirm that the proposed algorithm is more effective in solving the distributed flexible job shop scheduling problem. © 2024 ACM.

关键词： bacterial foraging algorithm Distributed flexible job shop scheduling dual-population local search

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Dynamic hyperparameter tuning-based path tracking control for robotic rollers working on earth-rock dam under complex construction conditions

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AUTOMATION IN CONSTRUCTION 2022年第0期143卷

作者： Guan, Shiwei Wang, Jiajun Wang, Xiaoling Shi, Mengnan Lin, Weiwei Chen, Wenlong State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

Robotic roller technology is important for ensuring the compaction quality and construction efficiency of earth -rock dams, and its key challenge is related to path tracking control. The current easy-to-use and effective pro-portion-integration-differentiation (PID) path tracking controller requires time-consuming and labor-intensive hyperparameter tuning, making its application in complex construction environments with a set of fixed hyperparameters, such as transition, misalignment, and position drift, difficult. This paper describes the TSABFA-PID path tracking controller based on hybrid tunicate swarm algorithm (TSA) and bacterial foraging algorithm (BFA), and modified kinematic model. The proposed controller can dynamically self-tune hyperparameters to adapt to complex construction condition by optimizing the objective function. The proposed controller achieved better results in both simulation environment and on-site tests than state-of-the-art methods. In the future, the deep reinforcement learning and human-computer interaction techniques will be integrated into the proposed controller to improve the compaction performance.

关键词： Path tracking control Robotic roller PID controller Tunicate swarm algorithm bacterial foraging algorithm Earth -rock dam

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Modeling and Parameter Extraction of OFET Compact Models Using Metaheuristics-Based Approach

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IEEE ACCESS 2019年 7卷 180438-180450页

作者： Akkan, Nihat Altun, Mustafa Sedef, Herman Yildiz Tech Univ Elect & Commun Engn Dept TR-34220 Istanbul Turkey Istanbul Tech Univ Elect & Commun Engn Dept TR-34469 Istanbul Turkey

Research on the fabrication of organic field effect transistors (OFETs) has been dramatically increased in the last decade, considering their lightweight and flexible structure as well as their practical and low-cost production. In the next step of fabrication, building compact models and developing parameter extraction methods have critical importance in designing electronic circuits using fabricated OFETs. In this paper, we propose a parameter extraction approach which benefits from the power of metaheuristics. Although direct extraction tools offer analytical solutions in successive steps to extract model parameters, metaheuristics-based global optimization methods can find all parameters at once by exploring a wide range of parameters. Direct extraction tools are cumbersome and need human expertise. On the other hand, global optimization methods are very flexible, adaptive and can be automated as parameter extraction tools of any compact model. In this study, we introduce three different global optimization algorithms, namely, a genetic algorithm (GA), a hybrid artificial bee colony (h-ABC) algorithm, and bacterial foraging optimization (BFO) algorithm, for the parameter extraction. To the best of our knowledge, h-ABC and BFO algorithms have been used for the first time in extracting parameters of OFET compact models. We use two OFET compact models developed by Estrada et al. and Marinov et al. for two different datasets of OFET transistors, both having pentacene as organic semiconductor. While one of the dataset of transistor (T1) is available in literature, the dataset of the other transistor fabricated in our laboratory (T2) is generated as a new dataset. In order to tune control parameters of the developed algorithms, Taguchi's orthogonal experimental design (OED) method is used. Experimental results show that the proposed metaheuristics-based approach can extract model parameters successfully and can perform better than direct extraction methods. The studie

关键词： Compact models organic field effect transistor (ofet) parameter extraction artificial bee colony algorithm bacterial foraging algorithm genetic algorithm Taguchi method

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Multiple-Kernel MRVM With LBFO algorithm for Fault Diagnosis of Broken Rotor Bar in Induction Motor

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IEEE ACCESS 2019年 7卷 182173-182184页

作者： Zhao, Weiguo Wang, Liying Hebei Univ Engn Sch Water Conservancy & Hydropower Handan 056021 Peoples R China

Induction motors are key equipments widely used in modern industries. Fault diagnosis of broken rotor bar (BRB) timely and accurately is very important to ensure the reliable operation of induction motors (IMs). In this study, a multivariate relevance vector machine with multiple Gaussian kernels (MKMRVM) and principal component analysis (PCA) are developed to construct a classification model. Then an improved bacterial foraging optimization combining with Levy fight mechanism, named LBFO, is employed to tune the kernel parameters of MKMRVM to obtain the optimal fault diagnosis model. Finally, The LBFO-based MKMRVM classification model is used to identify the diagnosis of BRB of IMs. The performance is assessed based on a comprehensive experiment of fault diagnosis of BRB. The experimental results demonstrate that the proposed method may achieve high diagnosis accuracy for different noise levels of diagnosis signals and is superior to other related fault diagnosis techniques.

关键词： Multivariate RVM bacterial foraging algorithm levy flight optimization algorithm PCA broken rotor bar induction motor

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A BFA-CM OPTIMIZATION LOG INTERPRETATION METHOD

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Chinese Journal of Geophysics 2016年第4期59卷 364-372页

作者： PAN Bao-Zhi DUAN Ya-Nan ZHANG Hai-Tao YANG Xiao-Ming HAN Xue College of Earth Exploration Science and Technology Jilin University Changchun 130061 China Material Testing Exploration Institute of Liaoning Province Shenyang 110121 China Exploration and Development Institute of the Changqing Oilfield PetroChina Xi'an 710018 China First Branch of the Logging Company Shengli Petroleum Engineering Co. Ltd. Dongying 257200 China

It is difficult to calculate reservoir parameters of tight sand reservoirs using conventional interpretation methods, due to their complex lithology and variable pore structure. An optimization log interpretation method is able to take full advantage of the log data and geological information. Therefore, it is an effective method to evaluate tight sand reservoirs. In this study, in order to calculate the reservoir parameters of tight sand reservoirs, an appropriate interpretation model needed to be first established according to the reservoirs’ characteristics. Then, the interpretation parameters were chosen, and the specific form of the objective function was determined. Next, an optimization algorithm was adopted to search for the optimal solution. A bacterial foraging algorithm (BFA) is a newly developed algorithm which has strong global search capabilities. It simulates the behavior of the colon bacillus which swims with flagella for food in the human gut. However, since it slowly converges in the later part of the optimization, it was combined in this study with a complex algorithm (CM) for constituting a BFA-CM hybrid algorithm, in order to improve the precision and efficiency of the search process. Also in this study, the unknown reservoir parameters of the optimization log interpretation method were determined using a genetic algorithm (GA), particle swarm optimization (PSO), BFA algorithm, and BFA-CM hybrid algorithm, respectively. The calculation results showed that, when compared with the GA and PSO, the errors of the porosity and the component content calculated by the BFA were minimal. However, the calculation result curves were found to be inconsistent. Therefore, by combining a BFA algorithm with a CM algorithm to constitute a BFA-CM hybrid algorithm for calculating reservoir parameters, the accuracy was improved, and the curves became more stable. The results of the BFA-CM optimization log interpretation method verified that the objective function va

关键词： bacterial foraging algorithm Optimization Log interpretation Complex algorithm Hybrid algorithm

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OPTIMAL ALLOCATION OF FACTS DEVICES: CLASSICAL VERSUS METAHEURISTC APPROACHES

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SAIEE AFRICA RESEARCH JOURNAL 2009年第1期100卷 12-23页

作者： Del Valle, Y. Perkel, J. Verkayagaraporthy, Cr. K. Harley, R. G. Georgia Inst Technol Dept Elect & Comp Engn Atlanta GA 30332 USA Missouri Univ Sci & Technol Dept Elect & Comp Engn Real Time Power & Intelligent Syst Lab Rolla MO 65409 USA

The application of optimization techniques to allocate and size FACTS devices in a power system is still under study. Currently, there is no widely accepted method since many researchers claim their methods to he better than others. This paper compares the effectiveness of classical and metaheuristic optimization approaches in a simple hut realistic ease study of optimal allocation of FACTS (Flexible AC Transmission System) devices, considering steady state and economic criteria, Concepts and details about the optimization process that tend to be overlooked in the literature are discussed together with some considerations about statistical analyses in the case of metaheuristic approaches.

关键词： FACTS devices classical optimization Benders' decomposition branch and hound evolutionary computation techniques genetic algorithm particle swarm optimization bacterial foraging algorithm

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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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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

作者： A. Sivakumar L. Premalatha School of Electrical Engineering VIT University

ISBN: (纸本)9781467399265

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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