检索结果-内蒙古大学图书馆

Modified Metaheuristic algorithms for the Optimal Design of Multiplier-Less Non-uniform Channel Filters

CIRCUITS SYSTEMS AND SIGNAL PROCESSING 2014年第3期33卷 815-837页

作者： Bindiya, T. S. Elias, Elizabeth Natl Inst Technol Dept Elect & Commun Engn Calicut 673601 Kerala India

Reconfigurable non-uniform channel filters are now being widely used in software define radio (SDR). The hardware implementation of these filters requires low complexity, low chip area and low power consumption. The frequency response masking (FRM) approach is proved to be a good candidate for the realization of a sharp digital finite impulse response (FIR) filter with low complexity. To reduce the complexity further, this paper gives an optimal design method which makes the channel filters totally multiplier-less. This is done in two steps. The channel filters are designed using the FRM approach with continuous filter coefficients. To obtain multiplier-less design, these filter coefficients are converted to finite-precision coefficients using signed power of two (SPT) space and the filter coefficients are synthesized in the canonic signed-digit (CSD) format. But this may lead to degradation of the filter performance. Hence the filter coefficients synthesis in the CSD format is formulated as an optimization problem. Several meta-heuristic algorithms like Differential Evolution (DE), Artificial Bee Colony (ABC), Harmony search algorithm (HSA) and gravitational search algorithm (GSA) are modified and deployed and the best one is selected.

关键词： Frequency response masking Canonic signed digit Metaheuristic algorithms Artificial bee colony Harmony search algorithm gravitational search algorithm

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Optimization algorithm for Extreme Learning Machine

A Hybrid Optimization Algorithm for Extreme Learning Machine

引用

2015年中国智能自动化学术会议

作者： Bin Li Yibin Li Xuewen Rong School of Science Qilu University of Technology School of Control Science and Engineering Shandong University

In this paper, a learning algorithm based on particle swarm optimization method(PSO) and a novel heuristic optimization method of gravitational search algorithm(GSA) for extreme learning machine(ELM) is proposed in terms of improving the generalization performance of single hidden-layer feed-forward neural networks, which is called as PSOGSA-ELM learning algorithm. The proposed learning algorithm uses a hybrid approach of PSO and GSA to select the optimal hidden biases and input weights of ELM, and then the output weights of ELM is analytically determined by the Moore-Penrose generalized inverse. The performance of the proposed algorithm is verified by regression and classification benchmark problems and is compared with PSO–ELM, GSA–ELM, and the original ELM learning algorithms, simulation results show that the proposed algorithm performs equal to or better than the other algorithms in terms of generalization performance and has good convergence speed.

关键词： Particle swarm optimization gravitational search algorithm Extreme learning machine

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic algorithms for the design of multiplier-less non-uniform filter banks based on frequency response masking

引用

SOFT COMPUTING 2014年第8期18卷 1529-1547页

作者： Bindiya, T. S. Elias, Elizabeth Natl Inst Technol Calicut Dept Elect & Commun Engn Calicut 673601 Kerala India

In this paper, multiplier-less nearly perfect reconstruction tree structured non-uniform filter banks (NUFB) are proposed. When sharp transition width filter banks are to be implemented, the order of the filters and hence the complexity will become very high. The filter banks employ an iterative algorithm which adjusts the cut off frequencies of the prototype filter, to reduce the amplitude distortion. It is found that the proposed design method, in which the prototype filter is designed by the frequency response masking method, gives better results when compared to the earlier reported results, in terms of the number of multipliers when sharp transition width filter banks are needed. To reduce the complexity and power consumption for hardware realization, a design method which makes the NUFB totally multiplier-less is also proposed in this paper. The NUFB is made multiplier-less by converting the continuous filter bank coefficients to finite precision coefficients in the signed power of two space. The filter bank with finite precision coefficients may lead to performance degradation. This calls for the use of suitable optimization techniques. The classical gradient based optimization techniques cannot be deployed here, because the search space consists of only integers. In this context, meta-heuristic algorithm is a good choice as it can be tailor made to suit the problem under consideration. Thus, this design method results in near perfect NUFBs which are simple and multiplier-less and have linear phase and sharp transition width with very low aliasing. Also, different non-uniform bands can be obtained from the tree structured filter bank by rearranging the branches.

关键词： Tree structured filter banks Frequency response masking Canonic signed digit Metaheuristic optimization algorithms Genetic algorithm Differential evolution Artificial bee colony algorithm gravitational search algorithm Harmony search algorithm

来源：评论

学校读者我要写书评

暂无评论

A survey on nature-inspired optimization algorithms with fuzzy logic for dynamic parameter adaptation

引用

EXPERT SYSTEMS WITH APPLICATIONS 2014年第14期41卷 6459-6466页

作者： Valdez, Fevrier Melin, Patricia Castillo, Oscar Tijuana Inst Technol Tijuana Mexico

Metaheuristic optimization algorithms have become a popular choice for solving complex problems which are otherwise difficult to solve by traditional methods. However, these methods have the problem of the parameter adaptation and many researchers have proposed modifications using fuzzy logic to solve this problem and obtain better results than the original methods. In this study a comprehensive review is made of the optimization techniques in which fuzzy logic is used to dynamically adapt some important parameters in these methods. In this paper, the survey mainly covers the optimization methods of Particle Swarm Optimization (PSO), gravitational search algorithm (GSA), and Ant Colony Optimization (ACO), which in the last years have been used with fuzzy logic to improve the performance of the optimization methods. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Particle Swarm Optimization gravitational search algorithm Ant Colony Optimization Fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

MICROSTRIP MULTISTOPBAND FILTER BASED ON PREFRACTAL SPACE-FILLING CURVE

引用

MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2014年第2期56卷 450-455页

作者： Caramanica, Federico Univ Trent Dept Informat Engn & Comp Sci I-38050 Trento Italy

In this letter, a method for the design of miniaturized multistopband filters is presented. This methodology exploits multiple resonance behavior of a small-size prefractal geometries. The considered fractal structures based on space-filling curve geometry and then, after recasting the design problem as an optimization one by defining a suitable cost function, is optimized by an unsupervised procedure, the gravitational search algorithm, which is a recent and interesting stochastic optimization method. To assess the effectiveness of this approach, a filter with three stopbands has been designed, numerically assessed, and realized. The obtained results are in good agreement with the numerical simulations and this confirms the capabilities of the proposed method as a microwave Computer Aided Design (CAD) tool. (c) 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:450-455, 2014

关键词： microstrip filter notched filter evolutionary algorithm gravitational search algorithm space filling curve

来源：评论

学校读者我要写书评

暂无评论

Joint economic lot sizing problem for a three-Layer supply chain with stochastic demand

引用

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2014年 155卷 272-283页

作者： Abdelsalam, Hisham M. Elassal, Magy M. Cairo Univ Fac Comp & Informat Giza 12613 Egypt

This paper considers the joint economic lot-sizing problem (JELP) for multi-layer supply chain with multi-retailers and single manufacturer and supplier. The paper extends the work of (Ben-Daya et al., 2013) and relaxes the assumption of deterministic demand and constant holding and ordering costs. The paper proposes modifying four computational intelligent algorithms to solve mixed integer problems and compares their performance for solving the problem at hand. The paper, further, compares between adopting a centralized safety stock policy versus a decentralized policy. Results showed cuckoo search to outperform other tested algorithms and, also, favored adopting a centralized policy. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Charged system search Cuckoo search gravitational search algorithm Joint economic lot sizing Particle swarm optimization Production planning Stochastic optimization Supply chain coordination

来源：评论

学校读者我要写书评

暂无评论

Performance assessment of multiobjective approaches in optical Traffic Grooming

引用

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2014年第May期41卷 319-350页

作者： Rubio-Largo, Alvaro Vega-Rodriguez, Miguel A. Gonzalez-Alvarez, David L. Univ Extremadura Escuela Politecn Dept Comp & Commun Technol Caceres 10003 Spain

In wavelength division multiplexing optical networks, the vast majority of traffic demands present a bandwidth request in the range of Mbps which is much lower than the available bandwidth of an optical channel (Gbps). These low-speed traffic requests can be groomed or multiplexed onto one single channel with the aim of optimizing the resources and costs of the network topology. In the literature, this problem of grooming low-speed requests is known as the Traffic Grooming problem, and is considered as an optimization problem. In this work, we present a comparative study of nine multiobjective evolutionary algorithms for solving this NP-hard problem. Two of them are standard metaheuristics in the multiobjective domain: the Fast Non-Dominated Sorting Genetic algorithm and the Strength Pareto Evolutionary algorithm. The rest of them are multiobjective versions of well-known evolutionary algorithms: Differential Evolution, Variable Neighbourhood search, gravitational search algorithm, Artificial Bee Colony, Firefly algorithm, Ant Colony Optimization, and Particle Swarm Optimization. In the comparative study, the approaches are compared when tackling four optical networks with a different number of nodes: 6, 11, 14, and 55 nodes. Furthermore, for each topology, we use different amounts of traffic: small, medium, and large. The results of this comparative study indicate that the multiobjective versions based on swarm intelligence obtain very good performance in almost all optical networks. Finally, we present a comparison between the best multiobjective approach and other methods published in the literature. (c) 2014 Elsevier Ltd. All rights reserved.

关键词： Optical networks Traffic Grooming Multiobjective Optimization Comparative study Differential Evolution Variable Neighbourhood search gravitational search algorithm Artificial Bee Colony Particle Swarm Optimization Ant Colony Optimization Firefly algorithm NSGA-II SPEA2

来源：评论

学校读者我要写书评

暂无评论

Intelligent controller for load-tracking performance of an autonomous power system

引用

AIN SHAMS ENGINEERING JOURNAL 2014年第4期5卷 1167-1176页

作者： Banerjee, Abhik Mukherjee, V. Ghoshal, S. P. Asansol Engn Coll Dept Elect Engn Asansol W Bengal India Indian Sch Mines Dept Elect Engn Dhanbad Jharkhand India Natl Inst Technol Dept Elect Engn Durgapur W Bengal India

The design and performance analysis of a Sugeno fuzzy logic (SFL) controller for an autonomous power system model is presented in this paper. In gravitational search algorithm (GSA), the searcher agents are collection of masses and their interactions are based on Newtonian laws of gravity and motion. The problem of obtaining the optimal tunable parameters of the studied model is formulated as an optimization problem and the same is solved by a novel opposition based GSA (OGSA). The proposed OGSA of the present work employs opposition-based learning for population initialization and also for generation jumping. In OGSA, opposite numbers are utilized to improve the convergence rate of the basic GSA. GSA and genetic algorithm are taken for the sake of comparison. Time-domain simulation reveals that the developed OGSA-SFL based on-line, off-nominal controller parameters for the studied model give real-time on-line terminal voltage response. (C) 2014 Production and hosting by Elsevier B.V. on behalf of Ain Shams University.

关键词： Automatic voltage regulator gravitational search algorithm Load tracking performance Opposite number Optimization Sugeno fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Hybrid Improved Gravitional search algorithm and Kernel Based Extreme Learning Machine Method for Classification Problems

Hybrid Improved Gravitional Search Algorithm and Kernel Base...

引用

IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Ma, Chao Ouyang, JiHong Guan, Jian Jilin Univ Coll Comp Sci & Technol Changchun 130023 Peoples R China Harbin Inst Technol Comp Applicat Res Ctr Shenzhen Peoples R China

ISBN: (纸本)9781479953530

In this paper, we hybridize the improved gravitational search algorithm (IGSA) with kernel based extreme learning machine (KELM) method. Based on this, a novel hybrid system IGSA-KELM is proposed to improve the generalization performance for classification problems. In this system, IGSA is designed by combining the search strategy of particle swarm optimization and GSA to effectively reduce the problem of slow convergence rate, moreover, the continuous-value IGSA and binary IGSA are integrated in one algorithm in order to optimize the KELM parameters and feature subset selection simultaneously. This proposed hybrid algorithm is evaluated on several well-known UCI machine learning datasets. The results indicate that the superiority of the proposed model in terms of classification accuracy. Our hybrid method not only can select the most relevant feature subset, but also achieves a high classification accuracy over other similar state-of-the-art classifier systems.

关键词： gravitational search algorithm kernel based extreme learning machine feature selection parameter optimization hybrid system

来源：评论

学校读者我要写书评

暂无评论

Renewable-Based Generation Expansion Planning Considering Environmental Issues Using GSA

Renewable-Based Generation Expansion Planning Considering En...

引用

Iranian Conference on Intelligent Systems (ICIS)

作者： Sadeghi, H. Mohammadian, M. Abdollahi, A. Rashidinejad, M. Mahdavi, S. Mahmoud Shahid Bahonar Univ Dept Elect Engn Kerman Iran

ISBN: (纸本)9781479933501

Generation expansion planning (GEP) is the problem of finding the optimal strategy to plan the construction of new generation plants while satisfying technical and economic constraints. In recent years, increasing concern for climate change has driven lots of countries all over the world to promote energy generation from renewable resources. Moreover, applying rigid environmental regulations by regulating authorities has been made generation companies (GENCOs) to consider emission as an important constraint in their generation expansion planning. In this circumstance, renewable energy sources (RES) can be pointed out as an appropriate alternative to fossil fuel-fired units which have a remarkable share on releasing different contaminants especially CO2, as the major contributor to greenhouse effect, into the atmosphere. In this paper, to investigate the impact of RES penetration on the greenhouse gases mitigation, an integrated renewable-conventional GEP model including a suitably modified objective function and additional constraints is presented. In order to encourage the GENCO in more investment on renewable resources, one of the most popular incentive-based support schemes, namely feed-in-tariff, is incorporated into the model. The resulting problem is solved by a novel heuristic technique namely, gravitational search algorithm. Obtained results reveal that the penetration of RES is a critical option for emission reduction.

关键词： Generation Expansion planning Renewable Sources Environmental Issues gravitational search algorithm

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：