检索结果-内蒙古大学图书馆

Artificial Bee Colony algorithm for the Minimum Load Coloring Problem

JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2013年第9期10卷 1968-1971页

作者： Fei, Tang Bo, Wang Jin, Wang Liu, DiChen Wuhan Univ Sch Elect Engn Wuhan 430072 Hubei Peoples R China

Given a graph G = (V, E) with n vertices, m edges, the load distribution of a coloring phi: V -> {red, blue} is a pair d(phi) = (r(phi), b(phi)), where r(phi) is the number of edges with at least one end-vertex colored red and b(phi) is the number of edges with at least one end-vertex colored blue. The minimum load coloring is to find a coloring phi such that the (maximum) load, I-phi: = (1/m)max{r(phi), b(phi)}, is minimized. This problem has been proven to be NP-complete, which arises in Wavelength Division Multiplexing (WDM), and it has been used for complex power grid networks. In this work, Artificial bee colony (ABC) algorithm for this problem is proposed and compared with simulated annealing (SA) algorithm. Experimental results show that ABC algorithm outperforms SA algorithm for solution quality on the average.

关键词： Artificial Bee Colony Simulated Annealing Optimization population based algorithm

来源：评论

学校读者我要写书评

暂无评论

Self balanced particle swarm optimization

引用

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2018年第4期9卷 774-783页

作者： Bhambu, Pawan Kumar, Sandeep Sharma, Kavita Arya Coll Engn & IT Jaipur Rajasthan India Jagannath Univ Jaipur Rajasthan India Govt Polytech Coll Kota India

In the field of swarm intelligence inspired algorithms, particle swarm optimization (PSO) is a renowned meta-heuristic due to its simplicity, performance, and implementation. However, the PSO also have some downsides like stagnation and slow convergence due to improper balance between the diversification and convergence abilities of the population. Therefore, in this paper, solution search process of PSO algorithm is modified to balance the organization of the individuals in the search space. In the proposed approach, artificial bee colony (ABC) algorithm inspired fitness-based solution search process is incorporated with the PSO algorithm. The proposed approach is tested over 20 unbiased benchmark functions, and the reported results are compared with PSO 2011, ABC, differential evaluation, self-adaptive acceleration factor in PSO, and Mean PSO algorithms through proper statistical analyses.

关键词： population based algorithm Swarm intelligence Nature inspired algorithm Optimization

来源：评论

学校读者我要写书评

暂无评论

Feature Selection using Modified Imperialist Competitive algorithm

Feature Selection using Modified Imperialist Competitive Alg...

引用

3rd International Conference on Computer and Knowledge Engineering (ICCKE)

作者： Mousavirad, S. J. Ebrahimpour-Komleh, H. Univ Kashan Dept Comp & Elect Engn Kashan Iran

ISBN: (纸本)9781479920938

Feature selection process is one of the main steps in data mining and knowledge discovery. Feature selection is a process to remove redundant and irreverent features without reducing the classification accuracy. This paper tries to select the best features set using imperialist competitive algorithm. Imperialist competitive algorithm is a novel population based algorithm which is inspired sociopolitical process of imperialist competition. In this paper, a modified imperialist competitive algorithm is presented and then this proposed algorithm is applied to feature selection process. To verify the effectiveness of the proposed approach, experiments carried out on some datasets. Results showed the features set selected by the imperialist competitive algorithm provide the better classification performance compared to the other methods.

关键词： feature selection impeirliast compeitive algorithm population based algorithm data mining knowledge discovery

来源：评论

学校读者我要写书评

暂无评论

Economic Load Dispatch of Thermal-Wind Integrated System Using Jaya algorithm 3

Economic Load Dispatch of Thermal-Wind Integrated System Usi...

引用

3rd International Conference for Convergence in Technology (I2CT)

作者： Bhongade, S. Potfode, A. SGS Inst Technol & Sci Dept Elect Engn Indore 452003 MP India

ISBN: (纸本)9781538642733

Economic Load Dispatch (ED) of Practical Power System is a crucial but important factor. A Proper Scheduling of generating units leads to a good economical saving. This Paper introduce a new method for ED Optimization considering Linear and Non-linear constraints. For Practical Consideration Valve Point loading effect related to Thermal units is also included. Complexity arises due to integration of Wind energy unit also consider. As nature of wind speed is stochastic. So a pdf function is analyzed to consider the wind speed profile. Advanced soft computing technique is required to consider practical complexity of ED optimization. Hence, A simple and flexible algorithm is proposed, this algorithm is free from influence of specific parameters. The algorithm is applied on IEEE-39 bus system with valve-point effect and standard 26 generating unit system with thermal-wind integrated system with cubic cost function.

关键词： Constrained optimization Economic Dispatch Nonsmooth Optimization population based algorithm Jaya algorithm Valve-Point loading effect Wind Energy

来源：评论

学校读者我要写书评

暂无评论

A Rule Induction Model Empowered by Fuzzy-Rough Particle Swarm Optimization algorithm for Classification of Microarray Dataset 1

引用

1st International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Dash, Sujata North Orissa Univ Baripada Odisha India

ISBN: (纸本)9788132222026;9788132222019

Selection of small number of genes from thousands of genes which may be responsible for causing cancer is still a challenging problem. Various computational intelligence methods have been used to deal with this issue. This study introduces a novel hybrid technique based on Fuzzy-Rough Particle Swarm Optimization (FRPSO) to identify a minimal subset of genes from thousands of candidate genes. Efficiency of the proposed method is tested with a rule based classifier MODLEM using three benchmark gene expression cancer datasets. This study reveals that the hybrid evolutionary Fuzzy-Rough induction rule model can identify the hidden relationship between the genes responsible for causing the disease. It also provides a rule set for diagnosis and prognosis of cancer datasets which helps to design drugs for the disease. Finally the function of identified genes are analyzed and validated from gene ontology website, DAVID, which shows the relationship of genes with the disease.

关键词： Particle swarm optimization population based algorithm Induction rule Rough-set Fuzzy-rough Minimal reduction

来源：评论

学校读者我要写书评

暂无评论

Sizing of Two Stage Op-Amp Using OHS algorithm

Sizing of Two Stage Op-Amp Using OHS algorithm

引用

International Electrical Engineering Congress (iEECON)

作者： Mallick, Soumen Suman, Kumari Kar, Rajib Mandal, Durbadal Ghoshal, Sakti Prasad NIT Durgapur ECE Dept Durgapur India NIT Durgapur EE Dept Durgapur India

ISBN: (纸本)9781509046669

An optimally designed CMOS Op-Amp has been presented in this article. Opposition concept based harmony Search (OHS) algorithm is applied for obtaining the minimum MOS area of the proposed Op-Amp. The proposed OHS based analog CMOS Op-Amp circuit design has alleviated from the problems of suboptimal convergence and stagnation, unlike Particle Swarm Optimization (PSO) and Harmony Search (HS). The least total MOS area of 121.8 mu m(2) is obtained in 0.35 mu m CMOS technology with a power dissipation of 616.3 mu W.

关键词： CMOS Sizing Op-Amp Opposition based Harmony Search Swarm intelligence population based algorithm

来源：评论

学校读者我要写书评

暂无评论

I Ching Philosophy Inspired Optimization 13

I Ching Philosophy Inspired Optimization

引用

13th IEEE International Conference on Control & Automation (ICCA)

作者： Li, Zhengyang Feng, Xiaoyi Duan, Wenzhe Yang, Yixin Liu, Bo Chinese Acad Sci Acad Math & Syst Sci Beijing Peoples R China Natl Ctr Math & Interdisciplinary Sci Div Math & Adv Technol Beijing Peoples R China

ISBN: (纸本)9781538626795

I Ching (Chinese characters: philosophy, stemming from ancient Chinese culture, is Chinese view of empiricism, world outlook and dialectics. Over thousands of years of evolving and interpretation, its cosmological wisdom has broad and profound influences not only on Chinese prevailing philosophy, but also on westerns. I Ching concentrates on the virtue of being moderate and appropriate, representing the balance by which it is contended that power/destiny can be well generated/controlled. Among the whole 64 hexagrams in I Ching, is the QIAN hexagram which is ranked in the first place, standing for the strong action and the everlasting desire for success. Behind I Ching philosophy lie the thinking and action models of optimization, specifically, identification from changing states, embracing vision, and optimal action obeying the balance of moderateness and appropriateness. I Ching philosophy could act as the driving force to establish and develop new optimization scheme. In this regard, enlightened by I Ching philosophy, particularly the QIAN hexagram, we propose I Ching philosophy inspired optimization, labeled as ICO for continuous optimization problems. Characterized by population-based, stochastic, iterative, and empiricism inspired features, the ICO evolves the population of solutions by multiple searching operators derived from underlying mechanism of the QIAN hexagram, as expected that the balance between global exploration and local exploitation can be well achieved. Specifically, the whole population is divided into four subpopulations, each of which corresponds to one solid line (state in the QIAN hexagram), then five search operators are developed to perform the learning, emerging, controlling, chasing and stabilizing operations on each subpopulation. The performances of the proposed ICO are investigated on well-known testing benchmarks and digital BR filter designing problem which is crucial in control field. Comparisons with several state-of-the-art algo

关键词： Continuous optimization digital IIR filter designing I Ching population based algorithm the QIAN hexagram

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Memetic Search in Artificial Bee Colony algorithm 7

A Novel Hybrid Memetic Search in Artificial Bee Colony Algor...

引用

7th International Conference on Contemporary Computing (IC3)

作者： Kumar, Sandeep Kumar, Ashutosh Sharma, Vivek Kumar Sharma, Harish Jagannath Univ Jaipur Rajasthan India Vardhaman Mahaveer Open Univ Kota India

ISBN: (纸本)9781479951734

Artificial Bee Colony (ABC) algorithm is a Nature Inspired algorithm (NIA). ABC is motivated by clever food foraging behavior of honey bees. Comparable to other population based stochastic algorithm ABC also lack balance in exploration of local search reason and exploitation of finest possible solutions in search space. The proposed algorithm is a hybrid of two memetic algorithms;it combines Levy Flight search in ABC (LFABC) and Memetic Search in ABC (MeABC) algorithm. The proposed algorithm named as Levy Flight Memetic Search in ABC (LFMABC) algorithm. The proposed LFMABC algorithm is tested over eleven benchmark functions in addition to two real world problems in order to establish its superiority over ABC and its recent variants. Results shows that proposed strategy LFMABC is able to find optimum in less time for considered problems.

关键词： Artificial Bee Colony algorithm Levy Flight Search Memetic algorithm Nature Inspired algorithm population based algorithm

来源：评论

学校读者我要写书评

暂无评论

A Modified DE: population or Generation based Levy Flight Differential Evolution (PGLFDE)

A Modified DE: Population or Generation based Levy Flight Di...

引用

International Conference on Futuristic Trends on Computational Analysis and Knowledge Management

作者： Vishnu Prakash Sharma Harji Ram Choudhary Sandeep Kumar Vikas Choudhary Govt. Engineering College Ajmer Jagannath University Bhagwant University

ISBN: (纸本)9781479984343

Researchers can solve Simple optimization problems using various methods. But differential Evolution (DE) is a method (population based) to solve complex optimization problems in some easy steps that is not possible to handle by mathematical optimization methods. For global optimization problems DE is a probabilistic approach. DE when tested over some bench mark functions and real world problems it performed better than some evolutionary algorithms and swarm - intelligence based algorithms. Balancing between Exploration and Exploitation using DE mutation and crossover with control parameters F and CR (fine tunned) is to be done. DE does not complete demand of good convergence and stagnation. DE Explore better but this exploration capability sometimes may skip the true solution and exhibit premature convergence. To improve this we can decrease the step size but this exhibit stagnation. So for Better exploitation, another approach called Memetic algorithm based on levy flight based local search strategy is used with DE. Further to balance exploration and exploitation in local search area in this paper a population or generation based exploitation of local search area in LFDE is proposed that is called PGLFDE. To show better result proposed strategy is tested on some bench mark functions and compare with recent variants of DE.

关键词： Differential Evolution Levy Flight Search Memetic algorithm Nature Inspired algorithm population based 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：