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Adaptive impedance matching using quantum genetic algorithm

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Journal of Central South University 2013年第4期20卷 977-981页

作者：谭阳红陈赛华张根苗熊智挺 College of Electrical and Information Engineering Hunan University

An adaptive technique adopting quantum genetic algorithm （QGA） for antenna impedance tuning is presented. Three examples are given with different types of antenna impedance. The frequency range of the dual standards is from 1.7 to 2.2 GHz. Simulation results show that the proposed tuning technique can achieve good accuracy of impedance matching and load power. The reflection coefficient and VSWR obtained are also very close to their ideal values. Comparison of the proposed QGA tuning method with conventional genetic algorithm based tuning method is Moreover, the proposed method can be useful for software wireless bands. also given, which shows that the QGA tuning algorithm is much faster. defined radio systems using a single antenna for multiple mobile and

关键词： impedance matching conventional genetic algorithm quantum genetic algorithm

Directional Modulation Based on a quantum genetic algorithm for a Multiple-Reflection Model

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Computers, Materials & Continua 2020年第9期64卷 1771-1783页

作者： Yuwei Huang Xiubo Chen Kaiguo Yuan Jianyi Zhang Biao Liu Information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Beijing Electronic Science and Technology Institute Beijing100070China Sate Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China School of Computing and Informatics The University of Louisiana at LafayetteLafayetteLA 70503USA.

Directional modulation is one of the hot topics in data security *** fulfill the requirements of communication security in wireless environment with multiple paths,this study takes into account the factors of reflections and antenna radiation pattern for directional *** other previous works,a novel multiple-reflection model,which is more realistic and complex than simplified two-ray reflection models,is proposed based on two *** focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna *** quantum approach has strengths in convergence speed and the globe searching ability for the complicated model with the large-size antenna array and multiple *** this,a phased directional modulation transmission system can be optimized as regards communication safety and improve performance based on the constraint of the pattern of the antenna *** work can spur applications of the quantum evolutionary algorithm in directional modulation technology,which is also studied.

关键词： Directional modulation quantum genetic algorithm phased antenna array multiple reflection

Novel quantum genetic algorithm and Its Applications

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Frontiers of Electrical and Electronic Engineering in China 2006年第1期1卷 31-36页

作者： ZHANG Ge-xiang LI Na JIN Wei-dong HU Lai-zhao School of Electrical Engineering Southwest Jiaotong UniversityChengdu 610031China National EW Laboratory Chengdu 610036China

By introducing strong parallelism of quantum computing into evolutionary algorithm,a novel quantum genetic algorithm(NQGA)is *** NQGA,a novel approach for updating the rotation angles of quantum logic gates and a strategy for enhancing search capability and avoiding premature convergence are *** typical complex continuous functions are chosen to test the performance of ***,NQGA is applied in selecting the best feature subset from a large number of features in radar emitter signal *** testing and experimental results of feature selection show that NQGA presents good search capability,rapid convergence,short computing time,and ability to avoid premature convergence effectively.

关键词： genetic algorithm quantum genetic algorithm feature selection recognition

Topology control based on quantum genetic algorithm in sensor networks

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Frontiers of Electrical and Electronic Engineering in China 2007年第3期2卷 326-329页

作者： SUN Lijuan GUO Jian LU Kai WANG Ruchuan College of Computer Nanjing University of Posts and TelecommunicationsNanjing 210003China

Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service(QoS)are *** terms of the goal of low energy consumption and high connectivity,the control on topology is *** algorithm of topology control based on quantum genetic algorithm in sensor networks is *** advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation *** goals of high connectivity and low consumption of energy are reached.

关键词： sensor network topology control power control genetic algorithm quantum genetic algorithm

Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a quantum genetic algorithm

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Journal of Systems Science and Information 2018年第5期9卷 399-420页

作者： Ye ZHANG Xiaoxuan HU Waiming ZHU Peng JIN School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling *** on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the *** results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

关键词： Earth observation satellite integrated scheduling quantum genetic algorithm

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

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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

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

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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

Improved Kriging for Drilling Visualization Based on quantum genetic algorithm

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Improved Kriging for Drilling Visualization Based on Quantum...

Multi-task Allocation of Multi-UAV Coalition Based on Improved quantum genetic algorithm

第37届中国控制会议

作者： Zheng Zhang Xuzhi Lai Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To realize drilling visualization, an effective interpolation method is essential to construct three-dimensional *** is an effective interpolation method commonly used by geologists. However, the variogram model parameters in traditional Kriging have a certain subjectivity, which will influence the accuracy of interpolation. quantum genetic algorithm（QGA）is introduced to optimize the variogram model parameters selection in this paper. Elevation values of boreholes are used as data sets for simulation. The results show that the proposed improved Kriging has a better prediction accuracy.

关键词： Kriging quantum genetic algorithm Optimization Interpolation

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Multi-task Allocation of Multi-UAV Coalition Based on Improv...