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第四届国际仿生工程学术会议

作者： Xuemei Fan Shujun Zhang Kevin Hapeshi Yinsheng Yang College of Quartermaster Technology Jilin University School of Computing and Technology The University of Gloucestershire College of Biological and Agricultural Engineering Jilin University

＜正＞People have learnt from biological system behaviours and structures to design and develop a number of different kinds of optimisation algorithms that have been widely used in both theoretical study and practical applications in engineering and business *** efficient supply chain is very important for companies to survive in global competitive ***

关键词： learn from nature biological system behaviours supply chain management ACO bees algorithm Genetic algorithm Firefly algorithm

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bees algorithm for design of dual-beam linear antenna arrays with digital attenuators and digital phase shifters

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2008年第4期18卷 337-347页

作者： Guney, K. Onay, M. Erciyes Univ Fac Engn Dept Elect & Elect Engn TR-38039 Kayseri Turkey Erciyes Univ Civil Aviat Sch Dept Aircraft Elect & Elect TR-38039 Kayseri Turkey

This article describes a method of designing a reconfigurable dual-beam linear antenna array using bees algorithm (BA). The BA is an optimization algorithm inspired by the behavior of the honey bees to find the optimal way of harvesting food resources around the hive. The proposed method is very simple and can be used directly in practice to synthesize multiple beam antenna arrays with digital attenuators and digital phase shifters. A good agreement between the desired pattern and the synthesized pattern using BA is obtained. (C) 2008 Wiley Periodicals, Inc.

关键词： antenna array bees algorithm pattern synthesis multiple-beam antenna array

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Quality of service in manufacturing networks: a service framework and its implementation

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2012年第9-12期63卷 1227-1237页

作者： Xu, Wenjun Zhou, Zude Pham, D. T. Liu, Quan Ji, C. Meng, Wei Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Univ Birmingham Sch Mech Engn Birmingham W Midlands England Cardiff Univ Sch Engn Cardiff S Glam Wales

Due to the continuous growth in the application of networks in manufacturing, quality of service (QoS) has become an important issue. In this paper, the concept of QoS for manufacturing networks is discussed. To provide overall performance assurance for manufacturing networks, a service framework integrating the QoS mechanisms of the networked resource service management function and the communication networks is proposed. The novel framework maps an application to resource services and then to communication networks, adopts an intelligent optimisation algorithm for QoS management of resource services, and provides QoS schemes for data transfer across communication networks. A prototype implementation has been realised and a set of simulation experiments conducted to evaluate the validity of the framework. The results obtained demonstrate the ability of the framework to satisfy the various performance requirements posed by such applications and provide efficient overall performance assurance for manufacturing networks.

关键词： Manufacturing networks Quality of service Networked resource service management bees algorithm Communication networks

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Modeling and solving constrained two-sided assembly line balancing problem via bee algorithms

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APPLIED SOFT COMPUTING 2012年第11期12卷 3343-3355页

作者： Tapkan, Pinar Ozbakir, Lale Baykasoglu, Adil Erciyes Univ Dept Ind Engn Kayseri Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey

Designing and operating two-sided assembly lines are crucial for manufacturing companies which assemble large-sized products such as trucks, buses and industrial refrigerators. This type of assembly line structure has several advantages over one-sided assembly lines such as shortened line length and reduced throughput time. The research area has recently focused on balancing two-sided assembly lines owing to these advantages. However, due to the complex structure of this problem, some practical constraints have been disregarded or have not been fully incorporated. In order to overcome these deficiencies, a fully constrained two-sided assembly line balancing problem is addressed in this research paper. Initially, a mathematical programming model is presented in order to describe the problem formally. Due to the problem complexity, two different swarm intelligence based search algorithms are implemented to solve large-sized instances. bees algorithm and artificial bee colony algorithm have been applied to the fully constrained two-sided assembly line balancing problem so as to minimize the number of workstations and to obtain a balanced line. An extensive computational study has also been performed and the comparative results have been evaluated. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Two-sided assembly line balancing bees algorithm Artificial bee colony algorithm Swarm intelligence Integer programming

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Optimization of semi-trailing arm suspension for improving handling and stability of passenger car

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART K-JOURNAL OF MULTI-BODY DYNAMICS 2012年第K2期226卷 108-121页

作者： Kazemi, Mohsen Shirazi, Kourosh Heydari Ghanbarzadeh, Afshin Shahid Chamran Univ Dept Mech Engn Fac Engn Ahvaz Iran

Semi-trailing arm is an extended form of two suspension systems trailing arm and swing axle that compromises advantages and disadvantages of those systems. In this article, using bees algorithm optimization method, the characteristic parameters of a semi-trailing arm suspension system to optimize the handling and stability performances of a passenger car are determined. Two types of objective functions, namely off-line and on-line, are defined. In off-line objective function, variation of camber, toe angle, and wheel track due to roll are considered. In the on-line objective function, handling and stability performance of a moving vehicle in a standard J-turn maneuver are considered. A nine degree-of-freedom non-linear vehicle model consists of semi-trailing arm and MacPherson suspensions in rear and front axle, respectively, is considered. The optimized suspension systems obtained from both off-line and on-line objective functions are utilized in making two accurate vehicle models in ADAMS-Car for experimental field test. A comparison between the behaviors of the two vehicles shows that despite the simplicity of optimization with off-line objective functions relative to on-line1, it returns the satisfactory results and improves both the handling and stability performances.

关键词： Semi-trailing arm suspension handling and stability performance non-linear vehicle model bees algorithm

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A novel method for automatic modulation recognition

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APPLIED SOFT COMPUTING 2012年第1期12卷 453-461页

作者： Sherme, Ataollah Ebrahimzade Babol Univ Technol Fac Elect & Comp Engn Babol Sar Iran

Automatic recognition of the digital modulation plays an important role in various applications. This paper investigates the design of an accurate system for recognition of digital modulations. First, it is introduced an efficient pattern recognition system that includes two main modules: the feature extraction module and the classifier module. Feature extraction module extracts a suitable combination of the higher order moments up to eighth, higher order cumulants up to eighth and instantaneous characteristics of digital modulations. These combinations of the features are applied for the first time in this area. In the classifier module, two important classes of supervised classifiers, i.e., multi-layer perceptron (MLP) neural network and hierarchical multi-class support vector machine based classifier are investigated. By experimental study, we choose the best classifier for recognition of the considered modulations. Then, we propose a hybrid heuristic recognition system that an optimization module is added to improve the generalization performance of the classifier. In this module we have used a new optimization algorithm called bees algorithm. This module optimizes the classifier design by searching for the best value of the parameters that tune its discriminant function, and upstream by looking for the best subset of features that feed the classifier. Simulation results show that the proposed hybrid intelligent technique has very high recognition accuracy even at low levels of SNR with a little number of the features. (C) 2011 Elsevier B. V. All rights reserved.

关键词： Modulation recognition Pattern recognition bees algorithm Hierarchical support vector machine based classifier Combination of the higher order moments (up to eighth) and higher order cumulants (up to eighth) Spectral characteristics

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Data Missing Solution Using Rough Set Theory and Swarm Intelligence

Data Missing Solution Using Rough Set Theory and Swarm Intel...

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International Conference on Advanced Computer Science Applications and Technologies (ACSAT)

作者： Sadiq, Ahmed Tariq Duaimi, Mehdi Gzar Shaker, Samir Adil Univ Technol Baghdad Dept Comp Sci Baghdad Iraq Univ Baghdad Dept Comp Sci Baghdad Iraq

ISBN: (纸本)9780769549590;9781467358323

This paper presents a hybrid approach for solving null values problem;it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estimation through working with rough set theory. The results obtained from most code sets show that bees algorithm better than ID3 in decreasing the number of extracted rules without affecting the accuracy and increasing the accuracy ratio of null values estimation, especially when the number of null values is increasing.

关键词： COMPONENT NULL VALUES PROBLEM ROUGH SET bees algorithm ID3 INCOMPLETE DATABASES

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Improving fusion with optimal weight selection in Face Recognition

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INTEGRATED COMPUTER-AIDED ENGINEERING 2012年第3期19卷 229-237页

作者： Quang Duc Tran Kantartzis, Panagiotis Liatsis, Panos City Univ London Informat Engn & Med Imaging Grp Sch Engn & Math Sci London EC1V 0HB England

Face recognition has a large number of applications, including security/counterterrorism, person identification, Internet communications, E-commerce, and computer entertainment. Although research in automatic face recognition has been conducted since the 1960s, there exist research challenges in its practical application in the terms of performance accuracy, which deteriorates significantly with changes in illumination, pose, expression and occlusions. However, these inherent limitations can be potentially alleviated by fusing biometric information based on multiple facial features. Following this vision, the work presented here offers three contributions. Firstly, we present a Face Recognition System, where diverse biometrics features such as total face, eyes, nose, mouth, etc are extracted from the face image. Secondly, we analyse a number of approaches for combining the aforementioned information at matching score level. Thirdly, we proposed a new approach, based on a recently proposed optimisation technique, the bees algorithm, to determine the optimal weight parameters to enhance the performance of the fusion system. Experiments on the CASIA and ORL face databases indicate that the proposed method achieves consistently high recognition rates, compared to traditional FR approaches, such as the Eigenfaces, Fisherfaces, and D-LDA methods.

关键词： Face recognition multibiometric system Linear Discriminant Analysis density based score fusion bees algorithm

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Building synthetic networks of the budding yeast cell-cycle using swarm intelligence

Building synthetic networks of the budding yeast cell-cycle ...

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11th IEEE International Conference on Machine Learning and Applications (ICMLA)

作者： Ruz, Gonzalo A. Timmermann, Tania Goles, Eric Univ Adolfo Ibanez Fac Ingn & Ciencias Av Diagonal Las Torres 2640 Santiago Chile

ISBN: (纸本)9780769549132;9781467346511

A swarm intelligence technique called the bees algorithm is formulated to build synthetic networks of the budding yeast cell-cycle. The resulting networks contain the original fixed points of the budding yeast cell-cycle network plus additional fixed points to reduce the basin size of the fixed point associated to the G1 phase of the cell-cycle, with the purpose of promoting cell proliferation for biotechnological applications. One thousand synthetic networks were found using the bees algorithm, 84.5% had basins size for the G1 fixed point less or equal to 10, whereas the original model has a basin size for that fixed point of 1764. One of the synthetic networks was analyzed by a biologist concluding that the resulting model was quite consistent from a biological point of view, supporting the proposed method as a tool for biologist to construct synthetic networks with desired characteristics.

关键词： Boolean networks bees algorithm cell-cycle gene regulatory networks computational biology

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The bees algorithm and mechanical design optimisation

The Bees Algorithm and mechanical design optimisation

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5th International Conference on Informatics in Control, Automation and Robotics

作者： Pham, D. T. Castellani, M. Sholedolu, M. Ghanbarzadeh, A. Cardiff Univ Mfg Engn Ctr Cardiff Wales

ISBN: (纸本)9789898111302

The bees algorithm is a search procedure inspired by the way honey-bees forage for food. A standard mechanical design problem, the design of a welded beam structure, was used to benchmark the bees algorithm against other optimisation techniques. The paper presents the results obtained showing the robust performance of the bees algorithm.

关键词： bees algorithm optimisation mechanical design

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