检索结果-南通市图书馆

A Constraint Adaptive Multi-Tasking Differential Evolution Algorithm:Designed for Dispatch of Integrated Energy System in Coal Mine

引用

Tsinghua Science and Technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang dunwei gong School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China School of Information Science and Technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions reduction.However,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong multi-constraint.Existing constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch performance.To tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint adaptive.Then we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks effectively.The helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible domain.The purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local search.Additionally,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and convergence.Finally,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM scenarios.Results demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

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

A review of intelligent optimization for group scheduling problems in cellular manufacturing

引用

工程管理前沿:英文版 2023年第3期10卷 406-426页

作者： Yuting WANG Yuyan HAN dunwei gong Huan LI School of Computer Science Liaocheng UniversityLiaocheng 252059China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Given that group technology can reduce the changeover time of equipment,broaden the productivity,and enhance the flexibility of manufacturing,especially cellular manufacturing,group scheduling problems(GSPs)have elicited considerable attention in the academic and industry practical literature.There are two issues to be solved in GSPs:One is how to allocate groups into the production cells in view of major setup times between groups and the other is how to schedule jobs in each group.Although a number of studies on GSPs have been published,few integrated reviews have been conducted so far on considered problems with different constraints and their optimization methods.To this end,this study hopes to shorten the gap by reviewing the development of research and analyzing these problems.All literature is classified according to the number of objective functions,number of machines,and optimization algorithms.The classical mathematical models of single-machine,permutation,and distributed flowshop GSPs based on adjacent and position-based modeling methods,respectively,are also formulated.Last but not least,outlooks are given for outspread problems and problem algorithms for future research in the fields of group scheduling.

关键词： cellular manufacturing group scheduling flowshop literature review

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

An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation

引用

CAAI Transactions on Intelligence Technology 2023年第3期8卷 734-754页

作者： Yong Zhang Ying Hu Xiaozhi Gao dunwei gong Yinan Guo Kaizhou Gao Wanqiu Zhang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina School of Computing University of Eastern FinlandKuopioFinland The Macao Institute of Systems Engineering Macao University of Science and TechnologyTaipaChina

In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy protection.The case that different attributes/features of the same instance are stored in different institutions is called vertically distributed data.The pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature set.To solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first time.By optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more accurate.At the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'data.Moreover,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each participant.Finally,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation strategies.Experi-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.

关键词： Evolutionary optimization feature selection privacy protection vertical‐federated learning

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

Generating test data for both paths coverage and faults detection using genetic algorithms： multi-path case

引用

Frontiers of Computer Science 2014年第5期8卷 726-740页

作者： Yan ZHANG dunwei gong School of Technology Mudanjiang Normal University Mudanjiang 157012 China School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221116 China

Generating test data that can expose the faults of the program is an important issue in software testing. Al- though previous methods of covering path can generate test data to traverse target path, the test data generated by these methods are difficult in detecting some low-probabilistic faults that lie on the covered paths. We present a method of generating test data for covering multiple paths to detect faults in this study. First, we transform the problem of cover- ing multiple paths and detecting faults into a multi-objective optimization problem with constraint, and construct a mathe- matical model for it. Then, we give a strategy of solving the model based on a weighted genetic algorithm. Finally, we ap- ply our method to several real-world programs, and compare it with several methods. The experimental results confirm that the proposed method can more efficiently generate test data that not only traverse the target paths but also detect faults lying in them than other methods.

关键词： software testing multiple paths coverage faultsdetection multi-objective optimization

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

Generating test data for both path coverage and fault detection using genetic algorithms

引用

Frontiers of Computer Science 2013年第6期7卷 822-837页

作者： dunwei gong Yan ZHANG School of Information and Electrical Engineering China University of Mining and Technology Xuzhou 221116 China School of Technology Mudanjiang Normal University Mudanjiang 157012 China

The aim of software testing is to find faults in a program under test, so generating test data that can expose the faults of a program is very important. To date, current stud- ies on generating test data for path coverage do not perform well in detecting low probability faults on the covered path. The automatic generation of test data for both path coverage and fault detection using genetic algorithms is the focus of this study. To this end, the problem is first formulated as a bi-objective optimization problem with one constraint whose objectives are the number of faults detected in the traversed path and the risk level of these faults, and whose constraint is that the traversed path must be the target path. An evolution- ary algorithm is employed to solve the formulated model, and several types of fault detection methods are given. Finally, the proposed method is applied to several real-world programs, and compared with a random method and evolutionary opti- mization method in the following three aspects： the number of generations and the time consumption needed to generate desired test data, and the success rate of detecting faults. The experimental results confirm that the proposed method can effectively generate test data that not only traverse the target path but also detect faults lying in it.

关键词： software testing path coverage fault detection test data multi-objective optimization genetic algorithms

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

基于重构误差和极端模式识别的综合能源系统短期负荷预测

引用

中国电机工程学报 2024年第9期44卷 3476-3488,I0011页

作者：邢晓萱巩敦卫孙晓燕张勇梁睿中国矿业大学信息与控制工程学院江苏省徐州市221116 青岛科技大学自动化与电子工程学院山东省青岛市266000 中国矿业大学电气工程学院江苏省徐州市221116

综合能源系统的运行场景存在极端模式,且含有异常数据,亟剧增加了综合能源负荷预测的难度。该文提出基于极端模式识别和误差重构的综合能源系统极端模式短期负荷预测方法,通过极端模式的识别,异常数据的检测,提高综合能源负荷预测的精... 详细信息

综合能源系统的运行场景存在极端模式,且含有异常数据,亟剧增加了综合能源负荷预测的难度。该文提出基于极端模式识别和误差重构的综合能源系统极端模式短期负荷预测方法,通过极端模式的识别,异常数据的检测,提高综合能源负荷预测的精度。首先,基于最小累积距离的综合能源负荷数据聚类,识别系统的极端模式;然后,利用深度学习模型的残差和聚类误差进行误差重构,检测异常数据;最后,采用改进的Stacking集成学习方法,进行极端模式的综合能源负荷预测。将所提方法应用于典型的综合能源系统,并与已有方法比较,实验结果表明,所提方法能够很好地解决极端模式的综合能源系统短期负荷预测问题。

关键词：综合能源系统负荷预测极端模式识别重构误差集成学习

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

Optimal active-disturbance-rejection control for propulsion of anchor-hole drillers

引用

Science China(Information Sciences) 2021年第5期64卷 224-226页

作者： Yinan GUO Zhen ZHANG dunwei gong Xiwang LU Yang ZHANG Wei CHENG School of Information and Control Engineering China University of Mining and Technology School of Electrical and Power Engineering China University of Mining and Technology

Dear editor,The propulsion module of an anchor-hole driller controls the drilling speed with a hydraulic cylinder that provides the axial force when driving a drilling rig to break the surrounding rocks. This drilling process is traditionally controlled manually by operators that tend to set the machine at the maximum drilling speed.

关键词： Active-disturbance-rejection control particle swarm optimization hydraulic force-servo system propulsion anchor-hole driller

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

煤流-潮流协同的矿山供电系统低碳优化运行

引用

中国电机工程学报 2024年第6期44卷 2245-2256,I0013页

作者：梁睿张鸽袁乐童黄宏旭张小彤吕超贤巩敦卫中国矿业大学电气工程学院江苏省徐州市221116 中国矿业大学信息与控制工程学院江苏省徐州市221116

双碳目标的提出对我国矿山绿色高效开采提出了更高的需求。为此,该文提出煤流-潮流协同的矿山供电系统优化调度方法。首先,基于煤流在采煤工作面、带式运输机、储煤筒仓等环节的连续性特征,抽象出运输煤流和节点功率耦合的运输设备模型... 详细信息

双碳目标的提出对我国矿山绿色高效开采提出了更高的需求。为此,该文提出煤流-潮流协同的矿山供电系统优化调度方法。首先,基于煤流在采煤工作面、带式运输机、储煤筒仓等环节的连续性特征,抽象出运输煤流和节点功率耦合的运输设备模型;其次,整合煤流运输安全约束与配网潮流约束,建立煤流-潮流协同的运行优化模型;最后,以矿山用能的经济性和碳减排为目标,考虑主网实时碳计量水平,调节采煤时间、煤流速度、运输流量与设备用能,生成煤流运输和矿山电网低碳调度的优化方案。以山西某矿山供电系统为实例,验证所提模型与方法的有效性。仿真结果表明,所提模型与方法能够有效降低矿山生产的吨煤电耗、用能成本及碳排放量,实现了煤流-潮流协同的矿山低碳化经济运行。

关键词：矿山供电系统煤流潮流分时碳计量低碳运行

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

全清洁能源下的高品质矿区能源系统配置优化方法

引用

煤炭学报 2024年第3期49卷 1669-1679页

作者：梁睿李嘉翔巩敦卫黄宏旭梁凯泽刘海龙李晓中国矿业大学电气工程学院江苏徐州221116 青岛科技大学信息科学技术学院山东青岛266061 中煤集团新疆能源有限公司新疆乌鲁木齐830000 宁夏红墩子煤业有限公司宁夏银川750002

面向“30·60”双碳目标,矿区能源利用方式的绿色、经济、高效转型成为我国能源革命的迫切需求。西部矿区拥有丰富的可再生能源资源禀赋,但仍面临着可再生能源就地消纳困难,电力设备投资成本高、利用率低以及外送输电通道有限的困难。... 详细信息

面向“30·60”双碳目标,矿区能源利用方式的绿色、经济、高效转型成为我国能源革命的迫切需求。西部矿区拥有丰富的可再生能源资源禀赋,但仍面临着可再生能源就地消纳困难,电力设备投资成本高、利用率低以及外送输电通道有限的困难。为提升矿区用能清洁化程度,提升矿区能源供给的稳定性与可靠性,增强矿区对外部电网的支撑能力,提出全清洁能源下的高品质矿区能源系统(High-quality Coal Mine Energy System,HCMES)及其配置优化方法。首先,考虑西部矿山综合能源系统的负荷特点与伴生能源利用,结合可再生能源发电与废弃矿井抽水蓄能,构建全清洁能源下的HCMES架构。其次,考虑到矿区生产全流程负荷的需求响应能力,考虑系统的能量平衡约束,提出全清洁能源下的高品质矿区能源系统优化配置模型。最后,以系统年平均综合成本最小化为目标,将原问题转化为混合整数线性规划模型,求解生成高品质矿区能源系统优化配置方案。以我国西部某年产煤量1200万t的矿区实际数据为实例,验证所提模型与方法的有效性,并分析可再生能源出力与生产负荷需求不确定性对系统优化配置结果的影响。算例仿真设置了4种矿区能源系统配置方式:不配置储能、配置抽水蓄能、配置电化学储能、配置抽水蓄能(不外购电能)。结果表明,所提出的HCMES相较于其他配置方式可减少电气一次设备投资11.11%,相较于方式3可降低年平均综合成本7.91%,且最多可减少矿区生产用能总二氧化碳排放量91.17%。

关键词：全清洁能源伴生能源利用废弃矿井抽水蓄能矿山综合能源配置优化

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

Developer Cooperation Relationship and Attribute Similarity Based Community Detection in Software Ecosystem

引用

Chinese Journal of Electronics 2023年第1期32卷 39-50页

作者： SHEN Xin DU Junwei gong dunwei YAO Xiangjuan School of Information and Control Engineering China University of Mining and Technology School of Information Science and Technology Qingdao University of Science and Technology School of Mathematics China University of Mining and Technology

A software ecosystem(SECO) can be described as a special complex network. Previous complex networks in an SECO have limitations in accurately reflecting the similarity between each pair of nodes. The community structure is critical towards understanding the network topology and function. Many scholars tend to adopt evolutionary optimization methods for community detection. The information adopted in previous optimization models for community detection is incomprehensive and cannot be directly applied to the problem of community detection in an SECO. Based on this, a complex network in SECOs is first built. In the network, the cooperation intensity between developers is accurately calculated, and the attribute contained by each developer is considered. A multi-objective optimization model is formulated. A community detection algorithm based on NSGA-II is employed to solve the above model. Experimental results demonstrate that the proposed method of calculating the developer cooperation intensity and our model are advantageous.

关键词： Software ecosystem Complex network Cooperation intensity Attribute similarity Community detection

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

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

在线全文

在线全文

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

在线全文

在线全文

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：