检索结果-内蒙古大学图书馆

Synthesis of Linear Antenna Arrays Using enhanced firefly algorithm

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2019年第3期44卷 1961-1976页

作者： Singh, Urvinder Salgotra, Rohit Thapar Univ Dept ECE Patiala Punjab India

Nature inspired algorithms are finding extensive applications in real-world applications. firefly algorithm (FA) is one such swarm intelligent algorithm introduced in the recent past. This algorithm has proved its competitiveness over standard benchmark and real-world applications, but suffers from the problem of slow convergence speed. So, in order to overcome this problem, a modified FA approach called enhanced firefly algorithm (EFA) is proposed. The performance of the proposed EFA with respect to FA and other algorithms has been evaluated for eleven benchmark functions. The numerical results show that the novel method consistently provides better solution at a faster rate. Moreover, as a real-world application, EFA has been used for synthesis of linear antenna array for both equally and unequally spaced arrays. The results demonstrate that EFA provides reduced sidelobe level and faster convergence in comparison with algorithms like FA, biogeography-based optimization, cuckoo search, differential evolution, genetic algorithm, particle swarm optimization, tabu search and Taguchi method.

关键词： Swarm intelligence firefly algorithm enhanced firefly algorithm Linear antenna arrays Side lobe level

来源：评论

学校读者我要写书评

暂无评论

Direct Torque Control of Induction Motor Using enhanced firefly algorithm - ANFIS

引用

JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2017年第6期26卷 1750092-1750092页

作者： Sekhar, J. N. Chandra Marutheswar, G. V. Sri Venkateswara Univ Coll Engn Dept Elect & Elect Tirupati Andhra Pradesh India

In this paper, the hybrid direct torque control (DTC) technique is proposed for controlling the speed of the induction motor (IM). The hybrid technique is the combination of an enhanced firefly algorithm (FA) and the adaptive neuro fuzzy inference system (ANFIS) technique. The performance of the FA is improved by updating the randomized parameter. Here, the genetic algorithm (GA) is utilized for updating the parameter and improved the performance of the FA. Initially, the actual torque and the change of toque are applied to the input of the enhanced FA and form the electromagnetic torque as a dataset. The output of the enhanced FA is given to the input of the ANFIS which is determined from the output of interference system. The dynamic behavior of the IM is analyzed in terms of the parameters such as the speed, torque, flux, etc. Based on the parameters, the motor speed is controlled by utilizing the proposed technique. Then the output of the ANFIS is translated into the stator voltage which is given to the input of the support vector machine (SVM). After that, the control signal is generated for controlling the speed of the IM. The proposed hybrid technique is implemented in the Matlab/Simulink platform. The performance analysis of the proposed method is demonstrated and contrasted with the existing techniques such as without controller, particle swarm optimization (PSO)-based ANFIS and FA-ANFIS controller.

关键词： Induction motor enhanced firefly algorithm GA ANFIS PSO speed and torque

来源：评论

学校读者我要写书评

暂无评论

An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 64卷 1088-1097页

作者： Liang, Ruey-Hsun Wang, Jia-Ching Chen, Yie-Tone Tseng, Wan-Tsun Natl Yunlin Univ Sci & Technol Dept Elect Engn Yunlin 640 Taiwan

This paper presents an enhanced firefly algorithm for solving multi-objective optimal active and reactive power dispatch problems with load and wind generation uncertainties. The optimal dispatches of active and reactive power were considered simultaneously. In reactive power dispatch, the load tap changer positions of transformers, the reactive power injection of capacitors, and the voltages of slack bus and PV buses are controlled to reduce the transmission line losses and the voltage deviations of load buses. In active power dispatch, economic dispatch including losses is used to obtain the active power outputs of thermal generating units and to decrease the fuel costs. The proposed algorithm was based on a firefly algorithm, the formula and parameters of which were updated and modified, and a mutation strategy and local random search were used to enhance the exploration and search capabilities of the algorithm. The IEEE 30-bus system was used to demonstrate the effectiveness of the proposed method for solving multi-objective optimal active and reactive power dispatch problems while considering uncertainties. The results of the proposed method were compared with the results of other algorithms. The results showed that the proposed method achieved a more favorable solution than the other algorithms. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Optimal reactive power dispatch Optimal power flow Capacitor Load tap changer enhanced firefly algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimal scheduling for many-to-many on-orbit service manoeuvers considering variances in target accessibility

引用

AERONAUTICAL JOURNAL 2025年第1336期129卷 1550-1578页

作者： Zhang, J. Xia, H. Li, L. Harbin Inst Technol Space Control & Inertial Technol Res Ctr Harbin Peoples R China Harbin Inst Technol Coll New Energy Weihai Peoples R China

In this article, we delve into the optimal scheduling challenge for many-to-many on-orbit services, taking into account variations in target accessibility. The scenario assumes that each servicing satellite is equipped with singular or multiple service capabilities, tasked with providing on-orbit services to multiple targets, each characterised by distinct service requirements. The mission's primary objective is to determine the optimal service sequence, orbital transfer duration and on-orbit service time for each servicing satellite, with the ultimate goal of minimising the overall cost. We frame the optimal scheduling dilemma as a time-related colored travelling salesman problem (TRCTSP) and propose an enhanced firefly algorithm (EFA) to address it. Finally, experimental results across various scenarios validate the effectiveness and superiority of the proposed algorithm. The principal contribution of this work lies in the modeling and resolution of the many-to-many on-orbit service challenge, considering accessibility variations - a domain that has, until now, remained unexplored.

关键词： optimal scheduling problem many-to-many on-orbit service variances in target accessibility time-dependent coloured traveling salesman problem enhanced firefly algorithm

来源：评论

学校读者我要写书评

暂无评论

Community Detection in Complex Networks: Multi-objective enhanced firefly algorithm

引用

KNOWLEDGE-BASED SYSTEMS 2013年第Jul.期46卷 1-11页

作者： Amiri, Babak Hossain, Liaquat Crawford, John W. Wigand, Rolf T. Univ Sydney Ctr Complex Syst Res Sydney NSW 2006 Australia Univ Sydney Charles Perkins Ctr Sydney NSW 2006 Australia Univ Arkansas Dept Informat Sci & Management Little Rock AR 72701 USA

Studying the evolutionary community structure in complex networks is crucial for uncovering the links between structures and functions of a given community. Most contemporary community detection algorithms employs single optimization criteria (i.e.., modularity), which may not be adequate to represent the structures in complex networks. We suggest community detection process as a Multi-objective Optimization Problem (MOP) for investigating the community structures in complex networks. To overcome the limitations of the community detection problem, we propose a new multi-objective optimization algorithm based on enhanced firefly algorithm so that a set of non-dominated (Pareto-optimal) solutions can be achieved. In our proposed algorithm, a new tuning parameter based on a chaotic mechanism and novel self-adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The experimental results on synthetic and real world complex networks suggest that the multi-objective community detection algorithm provides useful paradigm for discovering overlapping community structures robustly. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Complex network Community Multi-objective enhanced firefly algorithm Pareto-optimal front

来源：评论

学校读者我要写书评

暂无评论

An efficient fault tolerance scheme based enhanced firefly optimization for virtual machine placement in cloud computing

引用

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2023年第7期35卷 e7610-e7610页

作者： Sheeba, Adlin Maheswari, B. Uma St Josephs Inst Technol Dept Comp Sci & Engn Chennai Tamil Nadu India Anna Univ St Josephs Coll Engn Comp Sci & Engn Chennai Tamil Nadu India

The virtual machine placement for the highly reliable cloud application is considered as one of the challenging and critical issues. To tackle such an issue, this article proposes the enhanced firefly algorithm based virtual machine placement model. But the migration time of the virtual machine placement is high and to reduce the migration time of the virtual machine placement, this article utilizes the K-means clustering algorithm. In addition, to obtain the optimal cluster for the virtual machine placement, the adaptive particle swarm optimization with the coyote optimization algorithm is employed. The experimental results are conducted for the proposed approach using various measures such as transmission overhead, total execution time, packet size, parallel applications numbers, and virtual machine numbers. The results demonstrate that the proposed method offers improved performance and an optimal virtual machine placement scheme with respect to the various constraint factors. The evaluation exposes that the proposed method offers less execution time when compared to other methods.

关键词： cloud computing coyote optimization algorithm enhanced firefly algorithm fault tolerance K-means algorithm particle swarm optimization virtual machine placement

来源：评论

学校读者我要写书评

暂无评论

Modified firefly algorithm for multidimensional optimization in structural design problems

引用

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2017年第6期55卷 2013-2028页

作者： Chou, Jui-Sheng Ngoc-Tri Ngo Natl Taiwan Univ Sci & Technol Dept Civil & Construct Engn 43Sec 4Keelung Rd Taipei Taiwan Univ Sci & Technol Fac Project Management Univ Danang 54 Nguyen Luong Bang Danang Vietnam

An enhanced nature-inspired metaheuristic optimization algorithm, called the modified firefly algorithm (MFA) is proposed for multidimensional structural design optimization. The MFA incorporates metaheuristic components, namely logistic and Gauss/mouse chaotic maps, adaptive inertia weight, and L,vy flight with a conventional firefly algorithm (FA) to improve its optimization capability. The proposed MFA has several advantages over its traditional FA counterpart. Logistic chaotic maps provide a diverse initial population. Gauss/mouse maps allow the tuning of the FA attractiveness parameter. The adaptive inertia weight controls the local exploitation and the global exploration of the search process. L,vy flight is used in the exploitation of the MFA. The proposed MFA was evaluated by comparing its performance in solving a series of benchmark functions with those of the FA and other well-known optimization algorithms. The efficacy of the MFA was then proven by its solutions to three multidimensional structural design optimization problems;MFA yielded the best solutions among the observed algorithms. Experimental results revealed that the proposed MFA is more efficient and effective than the compared algorithms. Therefore, the MFA serves as an alternative algorithm for solving multidimensional structural design optimization problems.

关键词： Nature-inspired optimization Structural engineering design enhanced firefly algorithm Chaotic maps Adaptive inertia weight Levy flight

来源：评论

学校读者我要写书评

暂无评论

A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch

引用

ENERGY 2012年第1期42卷 530-545页

作者： Niknam, Taher Azizipanah-Abarghooee, Rasoul Roosta, Alireza Amiri, Babak Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Sydney Fac Engn & IT Sydney NSW 2006 Australia

Combined heat and power units are playing an ever increasing role in conventional power stations due to advantages such as reduced emissions and operational cost savings. This paper investigates a more practical formulation of the complex non-convex, non-smooth and non-linear multi-objective dynamic economic emission dispatch that incorporates combined heat and power units. Integrating these types of units, and their power ramp constraints, require an efficient tool to cope with the joint characteristics of power and heat. Unlike previous approaches, the spinning reserve requirements of this system are clearly formulated in the problem. In this way, a new multi-objective optimisation based on an enhanced firefly algorithm is proposed to achieve a set of non-dominated (Pareto-optimal) solutions. A new tuning parameter based on a chaotic mechanism and novel self adaptive probabilistic mutation strategies are used to improve the overall performance of the algorithm. The numerical results demonstrate how the proposed framework was applied in real time studies. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Combined heat and power unit Dynamic economic emission dispatch enhanced firefly algorithm Pareto-optimal front Spinning reserve constraint

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：