检索结果-内蒙古大学图书馆

High Utility Itemset Mining over Uncertain Datasets Based on a quantum genetic algorithm

KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2018年第8期12卷 3606-3629页

作者： Wang, Ju Liu, Fuxian Jin, Chunjie Air Force Engn Univ Xian 710051 Shaanxi Peoples R China

The discovered high potential utility itemsets (HPUIs) have significant influence on a variety of areas, such as retail marketing, web click analysis, and biological gene analysis. Thus, in this paper, we propose an algorithm called HPUIM-QGA (Mining high potential utility itemsets based on a quantum genetic algorithm) to mine HPUIs over uncertain datasets based on a quantum genetic algorithm (QGA). The proposed algorithm not only can handle the problem of the non-downward closure property by developing an upper bound of the potential utility (UBPU) (which prunes the unpromising itemsets in the early stage) but can also handle the problem of combinatorial explosion by introducing a QGA, which finds optimal solutions quickly and needs to set only very few parameters. Furthermore, a pruning strategy has been designed to avoid the meaningless and redundant itemsets that are generated in the evolution process of the QGA. As proof of the HPUIM-QGA, a substantial number of experiments are performed on the runtime, memory usage, analysis of the discovered itemsets and the convergence on real-life and synthetic datasets. The results show that our proposed algorithm is reasonable and acceptable for mining meaningful HPUIs from uncertain datasets.

关键词： High utility itemsets uncertain datasets quantum genetic algorithm High potential utility itemsets HPUIM-QGA

来源：评论

学校读者我要写书评

暂无评论

HEURISTIC quantum genetic algorithm FOR AIR COMBAT DECISION MAKING ON COOPERATIVE MULTIPLE TARGET ATTACK

引用

International Journal of Modeling, Simulation, and Scientific Computing 2013年第4期4卷 44-61页

作者： HAIPENG KONG NI LI School of Automation Science and Electrical Engineering Beihang University 100191BeijingP.R.China

In order to achieve the optimal attack outcome in the air combat under the beyond visual range(BVR)condition,the decision-making(DM)problem which is to set a proper assignment for the friendly fighters on the hostile fighters is the most crucial task for cooperative multiple target attack(CMTA).In this paper,a heuristic quantum genetic algorithm(HQGA)is proposed to solve the DM *** originality of our work can be supported in the following aspects:(1)the HQGA assigns all hostile fighters to every missile rather than fighters so that the HQGA can encode chromosomes with quantum bits(Q-bits);(2)the relative successful sequence probability(RSSP)is defined,based on which the priority attack vector is constructed;(3)the HQGA can heuristically modify quantum chromosomes according to modification technique proposed in this paper;(4)last but not the least,in some special conditions,the HQGA gets rid of the constraint described by other algorithms that to obtain a better *** the end of this paper,two examples are illustrated to show that the HQGA has its own advantage over other algorithms when dealing with the DM problem in the context of CMTA.

关键词： Air combat decision making cooperative multiple target attack heuristic modification quantum genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Wideband signal DOA estimation based on modified quantum genetic algorithm

引用

IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2006年第3期E89A卷 648-653页

作者： Liu, F Li, SQ Liang, M Hu, LZ Natl EW Lab Chengdu 610036 Peoples R China Univ Elect Sci & Technol China Chengdu 610054 Peoples R China China Elect Technol Grp Corp 29 Res Inst Chengdu 610036 Peoples R China

A new wideband signal DOA estimation algorithm based on modified quantum genetic algorithm (MQGA) is proposed in the presence of the errors and the mutual coupling between array elements. In the algorithm, the narrowband signal subspace fitting method is generalized to wideband signal DOA finding according to the character of space spectrum of wideband signal, and so the rule function is constructed. Then, the solutions is encoded onto chromosomes as a string of binary sequence, the variable quantum rotation angle is defined according to the distribution of optimization solutions. Finally, we use the MQGA algorithm to solve the nonlinear global azimuths optimization problem, and get optimization azimuths by fitness values. The computer simulation results illustrated that the new algorithm have good estimation performance.

关键词： wideband signal direction of arrival quantum genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Delay optimization for ternary fixed polarity Reed-Muller circuits based on multilevel adaptive quantum genetic algorithm

引用

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2021年第10期36卷 5981-6006页

作者： He Zhenxue Wu Xiaoqian Wang Chao Huo Zhisheng Xiao Limin Wang Xiang Hebei Agr Univ Hebei Key Lab Agr Big Data Baoding 071001 Peoples R China Beihang Univ High Performance Comp Platform Beijing Peoples R China Beihang Univ Coll Software Beijing Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China

Delay optimization has now emerged as an important optimization goal in logic synthesis. The delay optimization for ternary fixed polarity Reed-Muller (FPRM) circuits aims to find a ternary FPRM circuit with a minimum delay. Because the delay optimization for ternary FPRM circuits is a combinatorial optimization problem, in this paper, we first propose a multilevel adaptive quantum genetic algorithm (MAQGA), which divides individuals into three-level populations: high-level population, intermediate-level population, and low-level population and uses the proposed ternary quantum rotation gate, proposed ternary quantum correction gate, and proposed multi-operator adaptive mutation mechanism to make the three-level populations evolve. Moreover, based on the proposed delay decomposition strategy, we propose a delay optimization approach (DOA) for ternary FPRM circuits under the unit delay model, which searches for a ternary FPRM circuit with a minimum delay using the MAQGA. Experimental results demonstrated the effectiveness and superiority of the DOA in optimizing the delay of ternary FPRM circuits.

关键词： combinatorial optimization problem delay optimization fixed polarity Reed-Muller genetic algorithm logic synthesis quantum genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Design optimization of office building envelope based on quantum genetic algorithm for energy conservation

引用

JOURNAL OF BUILDING ENGINEERING 2021年 35卷

作者： Wang, Yuxing Wei, Chunyu Hunan Univ Sch Architecture Changsha 410082 Hunan Peoples R China

Designing envelope configurations of building with the low construction cost and low energy consumption is of important significance to green building. At present, there are some mature professional software for building optimization design, however, these programs run for a long time and require detailed input of building parameters, which makes the design very inconvenient. It is relatively convenient to use some optimization algorithms to optimize the design of buildings. genetic algorithm is a common algorithm for building design optimization. However, genetic algorithm has the disadvantage of being easy to be trapped into local optimization. Based on this, in this paper, we propose a design optimal method of office building envelope based on quantum genetic algorithm. We optimize the office building envelope structure, such as walls, windows, glass curtain wall, numbers of windows, etc. to minimize the construction cost at the required energy conservation. Compared with the traditional genetic algorithm, in this paper, when using the quantum genetic algorithm makes the design optimization of office building envelope configuration at the required ENVLOAD (energy load of building envelope) value, the total window area are increased by 13.8%, which means that the natural ventilation is better;glass curtain wall ratio is increased by 14%, which means that indoor lighting is better;the cost fall by 0.7%, which means the cost is lower;the generation number to achieve convergence is reduced by 50%, which means the convergence is faster. And compared with original design, the total cost reduces by 35.3%. Compared with other literatures, the construction cost per unit area of envelope in this paper is lower and the building energy load per unit area of envelope is smaller.

关键词： Building envelope genetic algorithm quantum genetic algorithm Energy conservation Optimization

来源：评论

学校读者我要写书评

暂无评论

Multi-Adaptive Strategies-Based Higher-Order quantum genetic algorithm for Agile Remote Sensing Satellite Scheduling Problem

引用

SENSORS 2024年第15期24卷 4938页

作者： Sun, Xiaohan Ren, Yuan Yu, Linghui Space Engn Univ Dept Aerosp Engn & Technol Beijing 101416 Peoples R China DFH Satellite Co Ltd Beijing 100094 Peoples R China Space Engn Univ Dept Basic Course Beijing 101416 Peoples R China

The agile remote sensing satellite scheduling problem (ARSSSP) for large-scale tasks needs to simultaneously address the difficulties of complex constraints and a huge solution space. Taking inspiration from the quantum genetic algorithm (QGA), a multi-adaptive strategies-based higher-order quantum genetic algorithm (MAS-HOQGA) is proposed for solving the agile remote sensing satellites scheduling problem in this paper. In order to adapt to the requirements of engineering applications, this study combines the total task number and the total task priority as the optimization goal of the scheduling scheme. Firstly, we comprehensively considered the time-dependent characteristics of agile remote sensing satellites, attitude maneuverability, energy balance, and data storage constraints and established a satellite scheduling model that integrates multiple constraints. Then, quantum register operators, adaptive evolution operations, and adaptive mutation transfer operations were introduced to ensure global optimization while reducing time consumption. Finally, this paper demonstrated, through computational experiments, that the MAS-HOQGA exhibits high computational efficiency and excellent global optimization ability in the scheduling process of agile remote sensing satellites for large-scale tasks, while effectively avoiding the problem that the traditional QGA has, namely low solution efficiency and the tendency to easily fall into local optima. This method can be considered for application to the engineering practice of agile remote sensing satellite scheduling for large-scale tasks.

关键词： adaptive strategies agile remote sensing satellite scheduling global optimization large-scale tasks quantum genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

A new method for capillary pressure curve prediction based on NMR echo data using integral transform, the quantum genetic algorithm, and the artificial neural network in tight sandstone

引用

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年 217卷

作者： Jin, Guowen Xie, Ranhong China Univ Petr State Key Lab Petr Resources & Prospecting Beijing 102249 Peoples R China

The capillary pressure curve (CPC) is an important tool with which to investigate the petrophysical properties and pore structure of oil and gas reservoir rocks. However, the method of obtaining the CPC directly via labo-ratory measurements is usually time-consuming and costly, prone to the contamination or destruction of core samples, and can only be applied to limited cores. A new method adopting integral transform, the quantum genetic algorithm, and the artificial neural network (IT-QGA-ANN) based on nuclear magnetic resonance (NMR) echo data is proposed to improve CPC prediction accuracy in tight sandstone. First, 7 parameters that charac-terize rock properties are directly extracted from echo data using integral transform. This process does not require to obtain the transverse relaxation time (T-2) distribution by inversion of echo data, thereby avoiding the influence of inversion uncertainty. These characteristic parameters are then used as the input of the ANN, and the QGA method is utilized to optimize the weights and thresholds of ANN. Numerical simulation results prove the validity of integral transform to extract characteristic parameters. A total of 18 tight sandstones are used for mercury injection and NMR tests. The results indicate that, compared with the traditional nonlinear regression and ANN methods, the proposed IT-QGA-ANN method can more accurately predict the CPC. The proposed method achieves the direct and accurate transformation from echo data to the CPC, and provides important guidance for solving complex nonlinear problems in oil and gas reservoir evaluation based on NMR.

关键词： Capillary pressure curve Nuclear magnetic resonance Integral transform quantum genetic algorithm Artificial neural network

来源：评论

学校读者我要写书评

暂无评论

A quantum genetic algorithm for pickup and delivery problems with coalition formation

引用

Procedia Computer Science 2019年 159卷 261-270页

作者： Yara Rizk Mariette Awad Department of Electrical and Computer Engineering American University of Beirut Beirut Lebanon

With the “last mile” of the delivery process being the most expensive phase, autonomous package delivery systems are gaining traction as they aim for faster and cheaper delivery of goods to city, urban and rural destinations. This interest is further fueled by the emergence of e-commerce, where many applications can benefit from autonomous package delivery solutions. However, the environment stochasticity, variability and task complexity for autonomous operation make it difficult to deploy such systems in real-world applications without the incorporation of advanced machine learning and optimization algorithms. Moving away from designing a “one size fits all” agent to solve the outdoor package delivery problem and considering ad-hoc teams of agents trained within a data-driven framework could provide the answer. In this work, we propose a delivery scheduling algorithm for heterogeneous multi-agent systems using the pickup and delivery problem (PDP) formulation. Specifically, a 3-index mixed integer program-based PDP that allows coalition formation (PDP-CF) among agents is derived to allow multi-agent PDP schedules. We propose a quantum genetic algorithm to solve for the schedule since it is can better handle the large computational complexity of PDP-CF. Multiple PDP scenario simulations show the merits of the proposed approach.

关键词： Pickup delivery problems Coalition formation quantum genetic algorithm Cooperating agents

来源：评论

学校读者我要写书评

暂无评论

A Self-Adaptive quantum genetic algorithm for Network Flow Vehicle Scheduling Problem

引用

Journal of Computer and Communications 2021年第7期9卷 43-54页

作者： Aimei Xiao School of Computer Science and Technology Shandong University of Technology Zibo China

Bicycle sharing scheduling is a complex mathematical optimization problem, and it is challenging to design a general algorithm to solve it well due to the uncertainty of its influencing factors. This paper creatively establishes a new mathematical model to determine the appropriate number of vehicles to be placed at each placement point by calculating the traffic weights of the placement points and optimizes the hyperparameters in the algorithm by adaptive quantum genetic algorithm, and at the same time combines the network flow algorithm in graph theory to calculate the most suitable scheduling scheme for shared bicycles by establishing the minimum cost maximum flow network. Through experimental validation, the network flow-based algorithm proposed in this paper allows for a more convenient calculation of the daily bike-sharing scheduling scheme compared to previous algorithms. An adaptive quantum genetic algorithm optimizes the hyperparameters appearing in the algorithm. The experimental results show that the algorithm achieves good results as the transportation cost is only 1/15th of the GA algorithm and 1/9th of the QGA algorithm.

关键词： Network Coding quantum genetic algorithm Multicast Networks Optimization

来源：评论

学校读者我要写书评

暂无评论

Reliability optimization of linear consecutive k-out-of-n: F systems with Birnbaum importance-based quantum genetic algorithm

引用

ADVANCES IN MECHANICAL ENGINEERING 2019年第4期11卷

作者： Zhang, Shuai Zhao, Jiang-bin Zhu, Wen-jin Du, Li Northwestern Polytech Univ Sch Mech Engn Dept Ind Engn Xian 710072 Shaanxi Peoples R China

Component assignment problem is a common challenge of reliability optimization, which is a non-deterministic polynomial hard problem widely used in the linear consecutive k-out-of-n systems. In consideration of the advantages of quantum computing and importance measure, this article proposed a novel algorithm, which is Birnbaum importance-based quantum genetic algorithm, to improve the efficiency and accuracy for solving component assignment problem. First, the model of reliability optimization for linear consecutive k-out-of-n systems is established. Second, the detailed procedure of Birnbaum importance-based quantum genetic algorithm is introduced to solve the component assignment problem. Moreover, the effectiveness and the convergence of the quantum genetic algorithm, Birnbaum importance-based genetic local search, and Birnbaum importance-based quantum genetic algorithm is discussed through two comparative experiments. Finally, the case of production monitor systems is introduced to illustrate the effectiveness of Birnbaum importance-based quantum genetic algorithm comparing with the Birnbaum importance-based two-stage approach.

关键词： Component assignment problem linear consecutive k-out-of-n F system quantum genetic algorithm Birnbaum importance reliability optimization

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：