检索结果-内蒙古大学图书馆

Smart piezoelectric patch in non-linear beam: design, vibration control and optimal location

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2014年第1期36卷 131-144页

作者： Moradi, Abbas Shirazi, Kourosh H. Keshavarz, Masoud Falehi, Ali D. Moradi, Mosayeb Shahid Chamran Univ Dept Mech Engn Ahvaz Iran Islamic Azad Univ Dept Elect Engn Izeh Branch Izeh Iran Islamic Azad Univ Dept Elect Engn Damavand Branch Damavand Iran

In this paper, the concept of smart materials has been engaged in order to control and abate the vibrations of non-linear beams. In the meantime, flexural vibration of viscoelastic has been taken into account aimed at reinforcing the carbon nanotube beams. This theory has applied the viscoelastic model to draw out the classical viscoelastic Kelvin-Voigt model. Likewise, the Hamilton's principle has been employed to derive the non-linear differential equations of beam's motion as for the piezoelectric patches and also the multiple scales method has been engaged in order to solve the non-linear equation of system motion. A fuzzy controller has been desirably arranged in the piezoelectric actuator/sensor loop to reduce the forced vibrations for any arbitrary stimulation. Due to majestic efficiency of the bees algorithm (BA) in the solution of many different engineering problems, it has been engaged for this work. To ensure and confirm the robustness of the proposed approach, three different conditions of forced stimulation have been taken into account for the studied system. In all, the non-linear simulation results unveil the robust performance of the proposed approach based on the BA technique in the damping of the system's vibrations.

关键词： Vibration of non-linear beam fuzzy controller optimization bees algorithm smart piezoelectric patch vibration control Multiple Scales

来源：评论

学校读者我要写书评

暂无评论

Solving Parameter Identification of Nonlinear Problems by Artificial Bee Colony algorithm

引用

MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-6页

作者： Talatahari, S. Mohaggeg, H. Najafi, Kh. Manafzadeh, A. Univ Tabriz Dept Civil Engn Tabriz Iran Azad Univ Mahabad Dept Civil Engn Mahabad Iran

A new optimization method based on artificial bee colony (ABC) algorithm is presented for solving parameter identification problems. The ABC algorithm as a swarm intelligent optimization algorithm is inspired by honey bee foraging. In this paper, for the first time, the ABC method is developed to determine the optimum parameters of Bouc-Wen hysteretic systems. The proposed method exhibits efficiency, robustness, and insensitivity to noise-corrupted data. The results of the ABC are compared with those other optimization algorithms from the literature to show the efficiency of this technique for solving parameter identification problems.

关键词： PARAMETER identification NUMERICAL solutions for nonlinear theories bees algorithm PARTICLE swarm optimization ROBUST control

来源：评论

学校读者我要写书评

暂无评论

Dynamical and topological robustness of the mammalian cell cycle network: A reverse engineering approach

引用

BIOSYSTEMS 2014年第1期115卷 23-32页

作者： Ruz, Gonzalo A. Goles, Eric Montalva, Marco Fogel, Gary B. Univ Adolfo Ibanez Fac Ingn & Ciencias Santiago Chile Nat Select Inc San Diego CA 92121 USA

A common gene regulatory network model is the threshold Boolean network, used for example to model the Arabidopsis thaliana floral morphogenesis network or the fission yeast cell cycle network. In this paper, we analyze a logical model of the mammalian cell cycle network and its threshold Boolean network equivalent. Firstly, the robustness of the network was explored with respect to update perturbations, in particular, what happened to the attractors for all the deterministic updating schemes. Results on the number of different limit cycles, limit cycle lengths, basin of attraction size, for all the deterministic updating schemes were obtained through mathematical and computational tools. Secondly, we analyzed the topology robustness of the network, by reconstructing synthetic networks that contained exactly the same attractors as the original model by means of a swarm intelligence approach. Our results indicate that networks may not be very robust given the great variety of limit cycles that a network can obtain depending on the updating scheme. In addition, we identified an omnipresent network with interactions that match with the original model as well as the discovery of new interactions. The techniques presented in this paper are general, and can be used to analyze other logical or threshold Boolean network models of gene regulatory networks. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

关键词： Gene regulatory networks Boolean networks Threshold networks Update robustness Topology robustness bees algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal design of frequency selective surfaces with fractal motifs

引用

IET MICROWAVES ANTENNAS & PROPAGATION 2014年第9期8卷 627-631页

作者： da Silva, Marcelo Ribeiro Nobrega, Clarissa de Lucena Silva, Paulo Henrique da F. D'Assuncao, Adaildo Gomes Univ Fed Rio Grande do Norte UFRN CT DCO BR-59078970 Natal RN Brazil Fed Inst Educ Sci & Technol Paraiba IFPB BR-58015430 Joao Pessoa Paraiba Brazil

An alternative electromagnetic (EM) optimisation technique for the optimal design of frequency selective surfaces (FSSs) with fractal motifs is described. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated with FSS parametric full-wave analysis. In an application example, a fast and accurate multilayer perceptrons model of a FSS band-stop spatial filter with a Vicsek fractal motif is developed. This neural network model is used for repetitive cost function computations in population-based search algorithm simulations. A bees algorithm, continuous genetic algorithm and particle swarm optimisation are used for FSS optimisation with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of numerical convergence. Consistent results are presented for a second-pass of designed FSS prototype with Vicsek fractal elements.

关键词： electrical engineering computing frequency selective surfaces genetic algorithms multilayer perceptrons particle swarm optimisation search problems spatial filters frequency selective surfaces optimal design alternative electromagnetic optimisation technique computational intelligence tools FSS parametric full-wave analysis multilayer perceptrons FSS band-stop spatial fllter Vicsek fractal motif neural network model repetitive cost function computations population-based search algorithm simulations particle swarm optimisation continuous genetic algorithm bees algorithm

来源：评论

学校读者我要写书评

暂无评论

A Persian writer identification method using swarm-based feature selection approach

引用

INTERNATIONAL JOURNAL OF BIOMETRICS 2014年第1期6卷 53-74页

作者： Ram, Soheila Sadeghi Moghaddam, Mohsen Ebrahimi Univ Mohaghegh Ardabili Fac Engn Daneshagah Ave Ardebil Iran Shahid Beheshti Univ Elect & Comp Engn Dept Tehran Iran

Handwriting is one of the most famous biometrics which is processed based on image processing and pattern recognition techniques. However, there are a lot of reports that have already been published on handwritten text identification methods and researchers try to improve the accuracy and speed of such methods. This paper presents an offline Persian handwriting identification method in which some new text features are extracted and best ones are selected using a swarm-based approach. The essence of this feature selection method is bees algorithm, which is a modern swarm-based meta-heuristic approach. In the proposed technique, the adaptive neuro-fuzzy inference system (ANFIS) is employed as classifier and trained by the input feature vectors. It is also compared with a multi-layer perceptron (MLP) and fuzzy K-nearest neighbour classifiers. To test the proposed method, we have collected a handwritten Persian text dataset from 125 people who have written six sheets with five lines in each of optional Persian texts. Experimental results showed that the prediction accuracy was about 98% in average while the method training time is less than most related works. It seems this method can be extended for other languages by adjusting its parameters.

关键词： handwritten identification feature selection meta-heuristic bees algorithm adaptive neuro-fuzzy inference system ANFIS

来源：评论

学校读者我要写书评

暂无评论

Optimal Design and Performance Evaluation of A Grid Independent Hybrid Micro Hydro-Solar-Wind-Fuel Cell Energy System Using Meta-Heuristic Techniques

Optimal Design and Performance Evaluation of A Grid Independ...

引用

1st International Conference on Non Conventional Energy (ICONCE)

作者： Tudu, B. Mandal, K. K. Chakraborty, N. Jadavpur Univ Dept Power Engn Kolkata India

ISBN: (纸本)9781479933396

This paper presents the design and optimal sizing of a grid independent hybrid energy system consisting of micro hydro, solar, wind and fuel cell for catering a specific load. The optimal sizing is obtained using a comparatively new optimization technique called bees algorithm (BA) and the performance of the algorithm is compared with an established meta-heuristic techniques called particle swarm optimization (PSO) and also the system performance is evaluated in terms of the cost of the system. For obtaining the optimal sizing, net present cost (NPC) of the system has been considered. The system is designed such a way that the maximum utilization of the resources and carbon free electricity can be achieved. Keeping in mind this aspect, apart from renewable resources, electrolyser is introduced for production of hydrogen utilizing the excess power. It is observed that the system is quite feasible in meeting the load and in terms of cost of energy and also observed that though both the algorithms are capable of giving global solution, but Particle swarm optimization is fast in reaching optimal solution and takes less CPU time as compared to bees algorithm.

关键词： Hybrid energy system Unit sizing Micro-hydro plant Wind turbine Particle swarm optimization bees algorithm

来源：评论

学校读者我要写书评

暂无评论

BPEL - Business Process Execution Language Process Creation and Fault Localization Framework 5

BPEL - Business Process Execution Language Process Creation ...

引用

5th International Conference on Confluence - The Next Generation Information Technology Summit (Confluence)

作者： Kaur, Usvir Singh, Dheerendra Sri Guru Granth Sahib World Univ Dept Comp Sci & Engn Fatehgarh Sahib India SUS Coll Engn & Technol Dept Comp Sci & Engn Tangori India

ISBN: (纸本)9781479942367

Context: WS-BPEL has been recognized as service composition language which is both executable and process-oriented. Customers are benefited from the collaboration of various providers of web services. An XML format based language known as BPEL different from syntax and semantics from traditional program language. Objective: In this paper, we create a BPEL process creation example and framework for fault localization by implementing bees algorithm. Method: Based on the example of BPEL process creation we create an environment for local fault localization and uses bees optimization algorithm to generate combinations of different base roots that result in lower fault occurrence. Result: bees optimization algorithm is used to calculate number of faults occurrence. Results show that different combinations of different base tags result in lower fault occurrence. Conclusion: We conclude that our proposed framework of BPEL process creation and fault localization is effective in locating faults by generating test cases in BPEL programs.

关键词： Web Services- Business Process Execution Language(WSBPEL) Fault Localization Framework bees algorithm

来源：评论

学校读者我要写书评

暂无评论

Biological System Behaviours and Natural-inspired Methods and Their Applications to Supply Chain Management

Biological System Behaviours and Natural-inspired Methods an...

引用

4th International Conference of Bionic Engineering (ICBE 2013)

作者： Fan, Xuemei Zhang, Shujun Hapeshi, Kevin Yang, Yinsheng Jilin Univ Coll Quartermaster Technol Changchun 130023 Jilin Peoples R China Univ Gloucestershire Sch Comp & Technol Cheltenham Glos England Jilin Univ Coll Biol & Agr Engn Changchun Kagawa Peoples R China

ISBN: (纸本)9783037859322

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 management. An efficient supply chain is very important for companies to survive in global competitive market. An effective SCM (supply chain management) is the key for implement an efficient supply chain. Though there have been considerable amount of study of SCM, there have been very limited publications of applying the findings from the biological system study into SCM. In this paper, through systematic literature review, various SCM issues and requirements are discussed and some typical biological system behaviours and natural-inspired algorithms are evaluated for the purpose of SCM. Then the principle and possibility are presented on how to learn the biological systems' behaviours and natural-inspired algorithms for SCM and a framework is proposed as a guide line for users to apply the knowledge learnt from the biological systems for SCM. In the framework, a number of the procedures have been presented for using XML to represent both SCM requirement and bioinspiration data. To demonstrate the proposed framework, a case study has been presented for users to find the bio-inspirations for some particular SCM problems in automotive industry.

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

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Artificial Bee Colony Optimizer with Divide-and-Conquer and Crossover for Multilevel Threshold Image Segmentation

引用

DISCRETE DYNAMICS IN NATURE AND SOCIETY 2014年第1期2014卷 1-22页

作者： He, Maowei Hu, Kunyuan Zhu, Yunlong Ma, Lianbo Chen, Hanning Song, Yan Chinese Acad Sci Shenyang Inst Automat Dept Informat Serv & Intelligent Control Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), for multilevel threshold image segmentation, which employs a pool of optimal foraging strategies to extend the classical artificial bee colony framework to a cooperative and hierarchical fashion. In the proposed hierarchical model, the higher-level species incorporates the enhanced information exchange mechanism based on crossover operator to enhance the global search ability between species. In the bottom level, with the divide-and-conquer approach, each subpopulation runs the original ABC method in parallel to part-dimensional optimum, which can be aggregated into a complete solution for the upper level. The experimental results for comparing HABC with several successful EA and SI algorithms on a set of benchmarks demonstrated the effectiveness of the proposed algorithm. Furthermore, we applied the HABC to the multilevel image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the performance superiority of the proposed algorithm.

关键词： bees algorithm MULTILEVEL models (Statistics) SEGMENTATION (Image processing) THRESHOLDING algorithms INFORMATION sharing

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Artificial Bee Colony algorithm for the Service Selection Problem

引用

DISCRETE DYNAMICS IN NATURE AND SOCIETY 2014年第1期2014卷 1-13页

作者： Zhang, Changsheng Zhang, Bin Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

To tackle the QoS-based service selection problem, a hybrid artificial bee colony algorithm called h-ABC is proposed, which incorporates the ant colony optimizationmechanism into the artificial bee colony optimization process. In this algorithm, a skyline query process is used to filter the candidates related to each service class, which can greatly shrink the search space in case of not losing good candidates, and a flexible self-adaptive varying construct graph is designed to model the search space based on a clustering process. Then, based on this construct graph, different foraging strategies are designed for different groups of bees in the swarm. Finally, this approach is evaluated experimentally using different standard real datasets and synthetically generated datasets and compared with some recently proposed related service selection algorithms. It reveals very encouraging results in terms of the quality of solutions.

关键词： bees algorithm ANT algorithms SEARCH algorithms MATHEMATICAL optimization ADAPTIVE control systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：