检索结果-南通市图书馆

Composition of Web Services of multi-population Adaptive genetic algorithm Based on Cosine Improvement

Journal of Computer and Communications 2021年第6期9卷 109-119页

作者： Siyuan Meng Chuancheng Zhang School of Computer Science and Technology Shandong University of Technology Zibo China

Web quality of service (QoS) awareness requires not only the selection of specific services to complete specific tasks, but also the comprehensive quality of service of the whole web service composition. How to select the web service composition with the highest comprehensive QoS is a NP hard problem. In this paper, an improved multi population genetic algorithm is proposed. Cosine adaptive operator is added to the algorithm to avoid premature algorithm caused by improper genetic operator and the disadvantage of destroying excellent individuals in later period. Experimental results show that compared with the common genetic algorithm and multi population genetic algorithm, this algorithm has the advantages of shorter time consumption and higher accuracy, and effectively avoids the loss of effective genes in the population.

关键词： Web Service Composition multi-population genetic algorithm QoS Cosine Improved Adaptive genetic Operator

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Distribution Network Optimization Model of Industrial Park with Distributed Energy Resources under the Carbon Neutral Targets

引用

Energy Engineering 2023年第12期120卷 2741-2760页

作者： Xiaobao Yu Kang Yang College of Economics and Management Shanghai University of Electric PowerShanghai200090China

Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of a distribution network with DERs based on recent power usage *** predict and analyze the load growth of the industrial park,an improved back-propagation algorithm is ***,the study classifies users within the industrial park according to their specific power consumption and supply *** user segmentation allows for the introduction of three constraints:node voltage,wire current,and capacity of *** incorporating these constraints,the study constructs an optimization model for the distribution network in the industrial park,with the objective of minimizing the total operation and maintenance *** primary goal of these optimizations is to address the needs of DERs connected to the distribution network,while simultaneously mitigating their potential adverse impact on the ***,the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources.

关键词： Distributed energy resources improved back-propagation algorithm multi-population genetic algorithm distribution energy carbon neutral

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

SAMPGA Task Scheduling algorithm in Cloud Computing 36

SAMPGA Task Scheduling Algorithm in Cloud Computing

引用

第36届中国控制会议

作者： Xing Jia Wei Wang Bei Li Jun Department of Automation University of Science and Technology of China

ISBN: (纸本)9781538629185

As cloud computing is growing rapidly,efficient task scheduling algorithm plays a vital role to improve the resource utilization and enhance overall performance of the cloud computing ***,task scheduling is the severe challenge needed to solve urgently in cloud ***,the simulated annealing multi-population genetic algorithm(SAMPGA) is proposed for task scheduling in cloud computing,which is the combination of simulated annealing algorithm(SA)and multi-population genetic algorithm(MPGA) in this *** population initialization,SAMPGA adopts max-min algorithm to enhance the search *** incorporated into SAMPGA is employed to avoid local optimum and improve the performance of global optimum,while a family evolution strategy based on adaptive mechanism in MPGA is proposed to find better solution and improve convergence ***,experiments are conducted to evaluate the efficiency of the proposed method in *** with MPGA,SA and simulated annealing genetic algorithm(SAGA),the results of simulation show that the SAMPGA has more excellent performance in terms of the completion time,completion cost,convergence speed and degree of load imbalance.

关键词： Cloud computing task scheduling multi-population genetic algorithm simulated annealing algorithm

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Prediction of resilient modulus for subgrade soils based on ANN approach

引用

Journal of Central South University 2021年第3期28卷 898-910页

作者： ZHANG Jun-hui HU Jian-kun PENG Jun-hui FAN Hai-shan ZHOU Chao National Engineering Laboratory of Highway Maintenance Technology Changsha University of Science&TechnologyChangsha 410114China Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement *** order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this *** MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and *** developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output *** physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input *** MR was directly used as the output ***,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation *** results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.

关键词： resilient modulus subgrade soils artificial neural network multi-population genetic algorithm prediction method

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

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：