检索结果-内蒙古大学图书馆

International Conference on Audio, Language and Image Processing

作者： Zhao, Wen-Jiang Yang, Hong-Bin Wu, Yue School of Computer Engineering Science Shanghai University Shanghai 200072 China

ISBN: (纸本)9781424458653

An improved method of classic genetic algorithms is proposed which uses Thread-Level Speculation (TLS) technology for the shortcoming that classic genetic algorithm's search speed is slow. Unlike the classic genetic algorithm, Firstly we replace an individual with a single thread, use TLS technology to process each thread parallel, in order to eliminate the correlation among threads, increase individual diversity in the population, thus accelerate the convergence speed of genetic algorithms. Experimental results demonstrate that the method can increase the individual diversity in the population and accelerate the convergence speed of genetic algorithms, compared with the classic genetic algorithms. ©2010 IEEE.

关键词： convergence convergence speed genetic algorithms parallel genetic algorithm parallel programming thread-level speculation

来源：评论

学校读者我要写书评

暂无评论

Adaptive algorithm of parallel genetic optimization based on orthogonal wavelet of space diversity

Adaptive algorithm of parallel genetic optimization based on...

引用

2015 International Conference on Electric, Electronic and Control Engineering (ICEECE 2015)

作者： Xiaogen Pei Shaohua Zheng Communication Command Department of the Armored Force Institute School of Information Science and Engineering Shandong University

Diversity technology can effectively resist channel multipath fading,and balanced technology can effectively inhibit the inter-symbol interference,so the diversity technology and balanced technology combined can effectively improve the quality of ***,this paper uses parallel genetic algorithm to optimize the space diversity orthogonal wavelet adaptive algorithm,taking the space points on each branch equalizer weight vector as the son species of parallel genetic algorithms for selection,crossover,and mutation;between each species to each other and regularly send the best individual fitness;eliminate the worst individual fitness;and take diversity branch output signal and input orthogonal wavelet adaptive device *** computer simulation results show that the fast algorithm convergence speed and small steadystate errors can achieve the global optimal solution.

关键词： parallel genetic algorithm Space diversity Wavelet transform Adaptive

来源：评论

学校读者我要写书评

暂无评论

Application of Differential Evolution algorithm for Optimization of Strategies Based on Financial Time Series

引用

NUMERICAL ANALYSIS AND APPLICATIONS 2016年第2期9卷 150-158页

作者： Monakhov, O. G. Monakhova, E. A. Pant, M. Russian Acad Sci Inst Computat Math & Math Geophys Siberian Branch Pr Akad Lavrenteva 6 Novosibirsk 630090 Russia Dept Appl Sci & Engn New Technol BlockSaharanpur Campus IIT Roorkee 247667 Saharanpur India

An approach for optimization of trading strategies ( algorithms) based on indicators of financial markets and evolutionary computation is described. A new version of differential evolution algorithm for the search for optimal parameters of trading strategies for maximization of trading profit is used. The experimental results show that this approach can improve several times the profitability of the trading strategies.

关键词： trading strategy parallel genetic algorithm technical analysis financial indicator template evolutionary computation

来源：评论

学校读者我要写书评

暂无评论

A hybrid parallel genetic algorithm for yard crane scheduling

引用

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2010年第1期46卷 136-155页

作者： He, Junliang Chang, Daofang Mi, Weijian Yan, Wei Shanghai Maritime Univ Minist Educ Container Supply Chain Technol Engn Res Ctr Shanghai 200135 Peoples R China Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200030 Peoples R China Shanghai Maritime Univ Sch Logist Engn Shanghai 200135 Peoples R China

This paper aims at postulating a novel strategy in terms of yard crane scheduling. In this study, a dynamic scheduling model using objective programming for yard cranes is initially developed based on rolling-horizon approach. To resolve the NP-complete problem regarding the yard crane scheduling, a hybrid algorithm, which employs heuristic rules and parallel genetic algorithm (PGA), is then employed. Then a simulation model is developed for evaluating this approach. Finally, numerical experiments on a specific container terminal yard are used for system illustration. Computational results suggest that the proposed method is able to solve the problem efficiently. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Yard crane scheduling Objective programming Heuristic rules parallel genetic algorithm Simulation model

来源：评论

学校读者我要写书评

暂无评论

Matched-field inversion of sound speed profile in shallow water using a parallel genetic algorithm

引用

Chinese Journal of Oceanology and Limnology 2010年第5期28卷 1080-1085页

作者：余炎欣李整林何利 National Laboratory of Acoustics Institute of AcousticsChinese Academy of Sciences Haikou Laboratory of Acoustics Institute of AcousticsChinese Academy of Sciences Graduate School Chinese Academy of Sciences

A sound speed profile plays an important role in shallow water sound *** with in-situ measurements,many inversion methods,such as matched-field inversion,have been put forward to invert the sound speed profile from acoustic ***,the time cost of matched-field inversion may be very high in replica field *** studied the feasibility and robustness of an acoustic tomography scheme with matched-field processing in shallow water,and described the sound speed profile by empirical orthogonal *** analyzed the acoustic signals from a vertical line array in ASIAEX2001 in the East China Sea to invert sound speed profiles with estimated empirical orthogonal functions and a parallel genetic algorithm to speed up the *** results show that the inverted sound speed profiles are in good agreement with conductivity-temperature-depth ***,a posteriori probability analysis is carried out to verify the inversion results.

关键词： matched-field processing sound speed profile parallel genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Dynamic Adaboost learning with feature selection based on parallel genetic algorithm for image annotation

引用

KNOWLEDGE-BASED SYSTEMS 2010年第3期23卷 195-201页

作者： Li, Ran Lu, Jianjiang Zhang, Yafei Zhao, Tianzhong PM Univ Sci & Technol Inst Command Automat Nanjing 210007 Peoples R China

Image annotation can be formulated as a classification problem. Recently, Adaboost learning with feature selection has been used for creating an accurate ensemble classifier. We propose dynamic Adaboost learning with feature selection based on parallel genetic algorithm for image annotation in MPEG-7 standard. In each iteration of Adaboost learning, genetic algorithm (GA) is used to dynamically generate and optimize a set of feature subsets on which the weak classifiers are constructed, so that an ensemble member is selected. We investigate two methods of GA feature selection: a binary-coded chromosome GA feature selection method used to perform optimal feature subset selection, and a bi-coded chromosome GA feature selection method used to perform optimal-weighted feature subset selection, i.e. simultaneously perform optimal feature subset selection and corresponding optimal weight subset selection. To improve the computational efficiency of our approach, master-slave GA, a parallel program of GA, is implemented. k-nearest neighbor classifier is used as the base classifier. The experiments are performed over 2000 classified Corel images to validate the performance of the approaches. (C) 2009 Elsevier K.V. All rights reserved.

关键词： Image annotation Adaboost learning Feature selection parallel genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Variable selection method for quantitative trait analysis based on parallel genetic algorithm

引用

ANNALS OF HUMAN geneticS 2010年第1期74卷 88-96页

作者： Mukhopadhyay, Siuli George, Varghese Xu, Hongyan Med Coll Georgia Dept Biostat Augusta GA 30912 USA Indian Inst Technol Dept Math Bombay 400076 Maharashtra India

P>Selection of important genetic and environmental factors is of strong interest in quantitative trait analyses. In this study, we use parallel genetic algorithm (PGA) to identify genetic and environmental factors in genetic association studies of complex human diseases. Our method can take account of both multiple markers across the genome and environmental factors, and also can be used to do fine mapping based on the results of haplotype analysis to select the markers that are associated with the quantitative traits. Using both simulated and real examples, we show that PGA is able to choose the variables correctly and is also an easy-to-use variable selection tool.

关键词： QTL parallel genetic algorithm complex traits

来源：评论

学校读者我要写书评

暂无评论

parallel Differential Evolution in the PGAS Programming Model Implemented with PCJ Java Library 11th

Parallel Differential Evolution in the PGAS Programming Mode...

引用

11th International Conference on parallel Processing and Applied Mathematics (PPAM)

作者： Gorski, Lukasz Rakowski, Franciszek Bala, Piotr Nicolaus Copernicus Univ Fac Math & Comp Sci Torun Poland Univ Warsaw Interdisciplinary Ctr Math & Computat Modelling Warsaw Poland

ISBN: (纸本)9783319321493;9783319321486

New ways to exploit parallelism of large scientific codes are still researched on. In this paper we present parallelization of the differential evolution algorithm. The simulations are implemented in Java programming language using PGAS programing paradigm enabled by the PCJ library. The developed solution has been used to test differential evolution on a number of mathematical function as well as to fine-tune the parameters of nematode's C. Elegans connectome model. The results have shown that a good scalability and performance was achieved with relatively simple and easy to develop code.

关键词： parallel processing Differential evolution parallel genetic algorithm PGAS Java

来源：评论

学校读者我要写书评

暂无评论

BFD-NN: Best Fit Decreasing-Neural Network for Online Energy-Aware Virtual Machine Allocation Problems 16

BFD-NN: Best Fit Decreasing-Neural Network for Online Energy...

引用

7th Symposium on Information and Communication Technology (SoICT)

作者： Thanh Nguyen-Duc Nguyen Quang-Hung Nam Thoai HCMC Univ Technol VNU HCM Fac Comp Sci & Engn Ho Chi Minh City Vietnam

ISBN: (纸本)9781450348157

High performance computing (HPC) clouds consume a lot of energy (kWh);therefore reducing energy consumption is a high priority for any cloud provider. This paper studies the applications of vector bin packing heuristic and Neural Network (NN) to allocate virtual machines (VMs) onto physical machines (PMs) that minimizes total energy consumption of the physical machines. In our scenario, a list of virtual machines from request queue needs to assign to system for every interval time (T) and minimize total energy consumption. We proposed Best Fit Decreasing Neural Network (BFD-NN), which contains an evaluation function (f) that finds the most efficient physical machine for each VM from requests in system. We also proposed a process to optimize weight of coefficients in f for every request which users submit to the system based on information of users' requests in the past by using parallel genetic algorithm (PGA) and Neural Network. Our method is a new approach because it not only uses knowledge from requests of users but also considers time dimension of virtual machines. Two job parallel workload models in parallel Workloads Archive are used to evaluate our approach. The simulation results illustrate that BFD-NN could reduce up to 15% total energy consumption compared with state-of-the-art heuristics (such as Best Fit and First Fit Decreasing) in online allocation virtual machines.

关键词： Cloud Computing Resource Management Energy efficiency Virtual Machine Allocation Vector Bin Packing Neural Network Application parallel genetic algorithm BFD-NN

来源：评论

学校读者我要写书评

暂无评论

Environment for Automatic Development and Tuning of parallel Applications 14

Environment for Automatic Development and Tuning of Parallel...

引用

14th International Conference on High Performance Computing & Simulation (HPCS)

作者： Caymes-Scutari, Paola Bianchini, German Sikora, Anna Margalef, Tomas UTN FRM Lab Invest Comp Paralelo Distribuido LICPaD Mendoza Argentina Consejo Nacl Invest Cient & Tecn Mendoza Argentina Univ Autonoma Barcelona High Performance Comp Applicat Sci & Engn Res Grp Barcelona Spain

ISBN: (纸本)9781509020881

The use of high performance computing has been gaining more and more followers in the different branches of Science and Engineering given the potential offered to cleat with complex and big problems. However, the parallel programming paradigm involves additional aspects to the merely functional, which could provoke different kinds of bottlenecks in the performance of the applications. Such diff culties may represent critical obstacles, especially for the non-expert users. In this work, we consider the limitations of the automatic development of parallel applications, and the obstacles in the performance tuning process, and we propose a built-in environment that integrates these both processes in a transparent manner. We call our proposal as Environment for automatic development and tuning of parallel Applications (EPA). EPA follows a cooperative approach: (i) It provides an interface to guide the user in the depiction of the pair problem-solution by completing a form;(ii) such information is automatically formalized in a specif cation;(iii) the specif ed information is automatically used by EPA to instantiate an instrumented skeleton;(iv) the skeleton of the parallel application is a priori enriched in EPA with tuning instrumentation, for monitoring, analysis and tuning actions;(v) the tunable parallel application is automatically generated by EPA;(vi) the user is able to execute the application with no more effort than having completed a form. Clearly, EPA makes transparent the process of code generation and instrumentation, which represents an important advantage especially for non-expert users. Given that the parallelization of any pair problem-solution is hard to generalize, the environment proposes to tackle different parallel problem solvers. The tuning knowledge injected in the generated applications is based on performance models, which makes the decision-making process concise. The Environment could include as problem solvers as needed. In this article, we

关键词： parallel paradigm automatic development automatic performance tuning dynamic tuning genetic algorithms parallel genetic 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：