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A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization

EXPERT SYSTEMS WITH APPLICATIONS 2015年第17-18期42卷 6350-6364页

作者： Meng, Xian-Bing Gao, X. Z. Liu, Yu Zhang, Hengzhen Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China Aalto Univ Sch Elect Engn Dept Elect Engn & Automat FI-00076 Aalto Finland Chengdu Green Energy & Green Mfg R&D Ctr Chengdu 610200 Peoples R China

A novel bat algorithm (NBA) is proposed for optimization in this paper, which focuses on further mimicking the bats' behaviors and improving bat algorithm (BA) in view of biology. The proposed algorithm incorporates the bats' habitat selection and their self-adaptive compensation for Doppler effect in echoes into the basic BA. The bats' habitat selection is modeled as the selection between their quantum behaviors and mechanical behaviors. Having considered the bats' self-adaptive compensation for Doppler effect in echoes and the individual's difference in the compensation rate, the echolocation characteristics of bats can be further simulated in NBA. A self-adaptive local search strategy is also embedded into NBA. Simulations and comparisons based on twenty benchmark problems and four real-world engineering designs demonstrate the effectiveness, efficiency and stability of NBA compared with the basic BA and some well-known algorithms, and suggest that to improve algorithm based on biological basis should be very efficient. Further research topics are also discussed. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： bat algorithm Habitat selection Doppler effect in echoes Mechanical behavior Quantum behavior Optimization

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The online parameter identification of chaotic behaviour in permanent magnet synchronous motor by Self-Adaptive Learning bat-inspired algorithm

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2016年 78卷 285-291页

作者： Rahimi, Abdolah Bavafa, Farhad Aghababaei, Sara Khooban, Mohammad Hassan Naghavi, S. Vahid Shiraz Univ Technol Elect & Elect Dept Shiraz Iran Univ Tehran Dept Management Tehran Iran Tech & Vocat Univ Shahid Bahonar Coll Inst Elect Engn Shiraz Iran Islamic Azad Univ Zarghan Branch Young Researchers & Elite Club Zarghan Iran

One of the main issues in engineering is the identification of nonlinear systems. Because of the complicated as well as unexpected behaviours of these chaotic systems, it is introduced as special nonlinear systems. A minute change in the primary conditions of such systems would lead to significant variations in their behaviours. On the other hand, due to simple structure of Permanent Magnet Synchronous Motors (PMSM) and its high applications in industry, the use of this machine is dramatically increasing these days. The reflection of a chaotic behaviour as the Permanent Magnet Synchronous Motor is positioned in a particular area. In the model of PMSM, the exact parameters of the system are required to properly control and spot the error. In this paper, Self-Adaptive Learning bat-inspired Optimization algorithm is used for solving both offline and online parameter estimation problems for this chaotic system. In addition, noise is considered as one of influential factors in control of PMSM. According to simulation results, it can be claimed that the proposed algorithm is a very powerful algorithm for online parameter identification for PMSM. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Permanent Magnet Synchronous Motor (PMSM) System identification Chaotic bat algorithm Self-Adaptive Learning bat-inspired algorithm

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bat algorithm for Fingerprint Image Enhancement 12

Bat Algorithm for Fingerprint Image Enhancement

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12th IEEE International Conference on Programming and Systems (ISPS)

作者： Bouaziz, Amira Draa, Amer Chikhi, Salim Univ Constantine 2 MISC Lab Constantine Algeria

ISBN: (纸本)9781479977000

Fingerprint biometric systems performance is affected by the quality of fingerprint images. To overtake the low quality fingerprint images as well as overmaster the traditional image enhancers, the paper proposes a bat algorithm for gray scale fingerprint image contrast enhancement. The purpose is for the bat algorithm to map the gray level distributions for contrast enhancement ends. To assess the approach, the enhancement process is evaluated on low quality images from the FVC 2000 and compared to one of the traditional related-work contrast-based enhancers. The results show that the proposed bat algorithm has proven to qualitatively and numerically improve the fingerprint image quality through contrast manipulation on the general level of noise eradication and quality metrics in addition to ridge structure clarification and minutiae detection specificities.

关键词： component fingerprint recognition fingerprint image contrast enhancement bat algorithm gray level mapping

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Enhanced Shuffled bat algorithm (EShbat)

Enhanced Shuffled Bat Algorithm (EShBAT)

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International Conference on Advances in Computing, Communications and Informatics

作者： Hema Banati Reshu Chaudhary Dyal Singh College University of Delhi Department of Computer Science University of Delhi

ISBN: (纸本)9781509020300

bat algorithm (BA) is a simple and effective global optimization algorithm which has been applied to a wide range of real-world optimisation problems. Various extensions to bat algorithm have been proposed in the past;prominent amongst them being Shbat. Shbat is a hybrid between BA and Shuffled Frog Leaping algorithm-SFLA;a memetic algorithm based on food search behavior of frogs. Shbat integrates the shuffling and reorganization technique of SFLA to enhance the exploitation capabilities of bat. This paper proposes Enhanced Shuffled bat algorithm (EShbat) an extension to Shbat. In Shbat, different memeplexes evolve independently, with different cultures. EShbat improves the exploitation capabilities of Shbat by grouping together the best of each memeplex to form a super-memeplex. This super-memeplex evolves independently to further exploit the best solutions. The performance of EShbat is verified over 30 well-known benchmark functions. Experimental results indicate a significant improvement of EShbat over BA and Shbat.

关键词： bat algorithm Shuffled Frog Leaping algorithm Swarm intelligence Global Optimisation Numerical optimisation

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Design of Robust PID Controller for Buck Converter using bat algorithm

Design of Robust PID Controller for Buck Converter using Bat...

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International Conference on Power Electronics, Intelligent Control and Energy Systems

作者： Prabhu Omer Jagdish Kumar Balwinder Singh Surjan Electrical Engineering Department PEC University of Technology

ISBN: (纸本)9781467385886

Buck converters are still used as an efficient step down DC-DC converters for constant load voltage for many power supply applications under variable input voltage and different loading conditions. In most of the applications DC-DC converters are controlled by either voltage or by current mode controller. DC-DC converters exhibit nonlinear behavior due to switching, hence controller design comes with complexities. With ordinary PI controller, dynamic response of Buck converter is sluggish and exhibits large deviations. In this paper robust PID controller based on Hoo paradigm has been designed for voltage mode controlled buck converter with both variable input voltage and load variation. The controller design problem has been formulated as mixed sensitivity minimization problem and solved using bat algorithm. From the results obtained, the designed controller exhibits robust behavior by satisfying the robust stability criterion. The design and simulation has been carried out using MATLAB/SIMULINK and results verify the robustness of the controller for large input voltage and load variations.

关键词： Robust Control DC-DC Converters Buck Converter bat algorithm Continuous Current Mode

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bat algorithm for Scheduling Workflow Applications in Cloud 1

Bat Algorithm for Scheduling Workflow Applications in Cloud

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International Conference on Electronic Design, Computer Networks & Automated Verification (EDCAV 2015)

作者： Raghavan, S. Marimuthu, C. Sarwesh, P. Chandrasekaran, K. Natl Inst Technol Karnataka Mangalore India

ISBN: (纸本)9781479962075

Workflow is one of the important aspects of cloud computing today. Cloud computing is one of the fastest growing technologies in the world. Workflows can be used in cloud as we use them in grid. Many operations in the cloud are based on workflow execution. Workflow systems are now becoming more complex and for such kind of systems efficient workflow management is important. Workflow scheduling is an important part of workflow management. Scheduling in general is NP-hard problem. To solve such kind of problems exhaustive methods cannot be used. Only non-exhaustive techniques can be used. In this paper we have used a metaheuristic approach called bat algorithm. bat algorithm is specifically designed for optimizing hard problems. Here, bat algorithm with the help of binary bat algorithm is used for scheduling workflow in a cloud. Specifically the mapping of tasks and resources is done using this method. The optimal resources are selected such that the overall cost of the workflow is minimal.

关键词： Workflow Scheduling Cloud Workflow Scheduling bat algorithm Binary bat algorithm (BBA)

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Automatic generation control of multi area thermal system using bat algorithm optimized PD-PID cascade controller

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 68卷 364-372页

作者： Dash, Puja Saikia, Lalit Chandra Sinha, Nidul Natl Inst Technol Silchar Dept Elect Engn Silchar Assam India

This article presents automatic generation control (AGC) of an interconnected multi area thermal system. The control areas are provided with single reheat turbine and generation rate constraints of 3%/min. A maiden attempt has been made to apply a Proportional derivative-Proportional integral derivative (PD-PID) cascade controller in AGC. Controller gains are optimized simultaneously using more recent and powerful evolutionary computational technique bat algorithm (BA). Performance of classical controllers such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controller are investigated and compared with PD-PID cascade controller. Investigations reveal that PI, and PID provide more or less same response where as PD-PID cascade controller provides much better response than the later. Dynamic analysis has also been carried out for the controllers in presence of random load pattern, which reveals the superior performance of the PD-PID cascade controller. Sensitivity analysis reveals that the BA optimized PD-ND Cascade controller parameters obtained at nominal condition of loading, size and position of disturbance and system parameter (Inertia constant, H) are robust and need not be reset with wide changes in system loading, size, position of disturbance and system parameters. The system dynamic performances are studied with 1% step load perturbation in Area1. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Automatic generation control Cascade controller bat algorithm Sensitivity analysis Random load pattern

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Planning the sports training sessions with the bat algorithm

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NEUROCOMPUTING 2015年第PartB期149卷 993-1002页

作者： Fister, Iztok Rauter, Samo Yang, Xin-She Ljubic, Karin Fister, Iztok, Jr. Univ Maribor Fac Elect Engn & Comp Sci Maribor 2000 Slovenia Univ Ljubljana Fac Sport Ljubljana 1000 Slovenia Middlesex Univ Sch Sci & Technol London N17 8HR England Univ Maribor Fac Med Maribor 2000 Slovenia

Planning proper sports training has always been a very challenging task for coaches. In line with this, they need to have almost two special abilities: firstly, to have a lot of earlier experiences with sports training and secondly, to know the capability of their athletes very well. New ways in planning sports training have emerged with development of pervasive and mobile technologies. Recently, a GPS receiver is one of the most useful parts of each standard sports watch that enables athletes to track the duration of their sports activities and analyze them later on digital computers using GPS viewers. Most sport's watches are also capable of measuring an athlete's heart rate during activities. Both measures represent reliable data sources that can be used for planning the sports trainings by coaches. In this paper, we introduce a novel intelligent planning method for sports training sessions, where the training plans are generated on digital computers using the bat algorithm according to reliable data obtained from sports watches. Real-world experiments showed promising results that encouraged us to proceed with this research also in the future. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Sport training Training load bat algorithm Swarm intelligence

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Optimal placement of steel plate shear walls for steel frames by bat algorithm

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STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS 2015年第1期24卷 1-18页

作者： Gholizadeh, Saeed Shahrezaei, Amir Masoud Urmia Univ Dept Civil Engn Orumiyeh Iran Islamic Azad Univ Sci & Res Branch Dept Civil Engn Orumiyeh Iran

Layout optimization of steel frames with steel plate walls (SPWs) using a meta-heuristic search algorithm is the main aim of the present study. SPWs are lateral load-resisting systems, especially against earthquake excitation. These systems offer significant advantages in terms of cost, performance and ease of design compared with other systems. In this study, orthotropic membrane model is used to model the behaviour of steel plate shear walls. The newly developed bat algorithm, which is based on the echolocation behaviour of bats, is employed as the present study optimizer. Design variables of the optimization problem consist of the cross sections of beams and columns of the frame, the web plate thicknesses of SPWs and the placement of SPW in the frame. The bat algorithm performs suitable selection of sections from the AISC wide-flange (W) shapes list. Strength constraints of the American Institute of Steel Construction Load and Resistance Factor Design and displacement constraints are checked during the optimization process. The results reveal the effectiveness of the proposed method for optimization of steel frames with SPWs. Copyright (c) 2014 John Wiley & Sons, Ltd.

关键词： steel frame steel plate shear walls optimum design layout optimization bat algorithm meta-heuristic

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The Application Research of Improved bat algorithm for Time Table Problem

The Application Research of Improved Bat Algorithm for Time ...

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2016 4th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2016)

作者： Wenxiang Liu Gansu Normal University for Nationalities

The time table problem is a typical NP complete problem, when the bat algorithm solves this problem;it will quickly converge, and can get the local optimal solution but not the global optimal solution. Therefore, we use the advantage of active evolutionary operator to improve the bat algorithm, and to solve TTP problem. We do a lot of experiments and evaluate the performance of the improved bat algorithm. The experiment results show that improved bat algorithm is a more superior algorithm to apply to the TTP problem.

关键词： bat algorithm Time table problem active evolutionary operator invalid bat

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