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6th International Symposium on Computational Intelligence and Design (ISCID)

作者： Zhang, Jian Liu, Li Li, Huanzhou Tang, Zhangguo Sichuan Normal Univ Sch Phys & Elect Engn Chengdu Peoples R China

ISBN: (纸本)9780769550794

Parameters tuning is the key of the design of PID controller, for the PID parameters tuning, a PID parameters tuning method based on improved quantum genetic algorithm is proposed in this study. This study proposes an improved genetic algorithm (IQGA) which introduces a dynamic adjustment strategy of population and search intervals to improve the convergence speed, search ability and stability of quantum genetic algorithm-based PID parameters tuning method. Experimental results show that the proposed algorithm can obtain a good performance in PID parameters tuning problem.

关键词： quantum genetic algorithm PID parameters tuning

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Information Technology in An Improved quantum genetic algorithm based on Dynamic Adjustment of quantum Rotation Angle

Information Technology in An Improved Quantum Genetic Algori...

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2nd International Conference on Civil Engineering and Material Engineering (CEME 2013)

作者： Li, HuiXia Xue, YunCan Zhang, JianQiang Yang, QiWen Hohai Univ Coll Internet Things Engn Changzhou Peoples R China

ISBN: (纸本)9783037859797

To overcome the shortcomings of precocity and being easily trapped into local optimum of the standard quantum genetic algorithm (QGA), Information Technology in An Improved quantum genetic algorithm based on dynamic adjustment of the quantum rotation angle of quantum gate (DAAQGA) was proposed. Mutation operation using the quantum not-gate is also introduced to enhance the diversity of population. Chaos search are also introduced into the modified algorithm to improve the search accuracy. Simulation experiments have been carried and the results show that the improved algorithm has excellent performance both in the preventing premature ability and in the search accuracy.

关键词： information technology quantum genetic algorithm quantum rotation gate quantum mutation Chaos search

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A New Mutative Scale Chaos Optimization quantum genetic algorithm

A New Mutative Scale Chaos Optimization Quantum Genetic Algo...

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20th Chinese Control and Decision Conference

作者： Teng, Hao Yang, Bingru Zhao, Baohua Univ Sci & Technol Beijing Sch Informat Engn Beijing 100080 Peoples R China Univ Jinan Sch Informat Sci & Engn Jinan 250022 Peoples R China

ISBN: (纸本)9781424417339

Aiming at the trouble of easy getting into local minimum existed in quantum genetic algorithm, this paper presents a new chaos quantum genetic algorithm. This algorithm executes global search using the chaos movement's ergodicity and randomness, and searches the local space of current optimal solutions using the prior knowledge in the process of search and combining the idea of gradient descent, thereby can improve the convergence speed. Adopting the ameliorated mutative scale chaos optimization method, chaotic search for the optimization is implemented to the population that is processed one time with the quantum genetic algorithm, which can lead to the rapid evolution of the population. The test of typical function shows that the performance of this method is better than quantum genetic algorithm and genetic algorithm.

关键词： quantum genetic algorithm Chaos Optimization Gradient Descent Mutative Scale

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Variable observation duration scheduling problem for agile Earth observation satellite based on quantum genetic algorithm 40

Variable observation duration scheduling problem for agile E...

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40th Chinese Control Conference (CCC)

作者： Zhi, Hui Liang, Weikui Han, Peng Guo, Yanning Li, Chuanjiang Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China Aerosp Syst Engn Shanghai Shanghai 201109 Peoples R China

ISBN: (纸本)9789881563804

Compared to the conventional Earth observation satellites, the agile Earth observation satellites have stronger attitude adjustment capability along three axes which also make the scheduling problem more difficult. This paper proposes a new variable observation duration scheduling method based on the quantum genetic algorithm for agile Earth observation satellites at multiple observation tasks. First, we model the scheduling problem and take the observation profits as the performance function that combines the task priority and observation duration. Then, we propose a new coding method that includes the actual observation start time and the observation duration. Based on the good continuous space search ability of the quantum genetic algorithm, we design the corresponding quantum genetic algorithm which searches in both discrete domain and continuous domain. Finally, we give the simulation of multi-task multi-satellite scheduling problems and get the results of efficient observation planning which indicate the effectiveness of the algorithm.

关键词： quantum genetic algorithm scheduling agile Earth observation satellite

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Improved Kriging for Drilling Visualization Based on quantum genetic algorithm 37

Improved Kriging for Drilling Visualization Based on Quantum...

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37th Chinese Control Conference (CCC)

作者： Zhang, Zheng Lai, Xuzhi Wu, Min China Univ Geosci Sch Automat Wuhan 430074 Hubei Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9789881563958

To realize drilling visualization, an effective interpolation method is essential to construct three-dimensional model. Kriging is an effective interpolation method commonly used by geologists. How-ever, 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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Function optimization based on quantum genetic algorithm

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Research Journal of Applied Sciences, Engineering and Technology 2014年第1期7卷 144-149页

作者： Sun, Ying Xiong, Hegen College of Machinery and Automation Wuhan University of Science and Technology Wuhan 430081 B.O.X 242 China

Optimization method is important in engineering design and application. quantum genetic algorithm has the characteristics of good population diversity, rapid convergence and good global search capability and so on. It combines quantum algorithm with genetic algorithm. A novel quantum genetic algorithm is proposed, which is called Variable-boundary-coded quantum genetic algorithm (vbQGA) in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded chromosomes. Therefore much shorter chromosome strings can be gained. The method of encoding and decoding of chromosome is first described before a new adaptive selection scheme for angle parameters used for rotation gate is put forward based on the core ideas and principles of quantum computation. Eight typical functions are selected to optimize to evaluate the effectiveness and performance of vbQGA against standard genetic algorithm (sGA) and genetic quantum algorithm (GQA). The simulation results show that vbQGA is significantly superior to sGA in all aspects and outperforms GQA in robustness and solving velocity, especially for multidimensional and complicated functions. © Maxwell Scientific Organization, 2014.

关键词： Function optimization Optimization algorithm quantum genetic algorithm Variable-boundary coding

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Dynamic Reactive Power Allocation Strategy for AC/DC System Based on quantum genetic algorithm

Dynamic Reactive Power Allocation Strategy for AC/DC System ...

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Chinese Automation Congress (CAC)

作者： Li, Yanchun Bai, Enming Xu, Jianyuan Liu, Jicheng Liu, Shaowu Ren, Puchun Yuan, Peng State Grid Corp China Northeast Branch Shenyang Peoples R China Shenyang Univ Technol Shenyang Peoples R China State Grid Liaoning Elect Power Co Ltd Elect Power Res Inst Shenyang Peoples R China

ISBN: (纸本)9781728176871

With the fast increasing of new energy, the voltage stability control ability of the AC/DC hybrid grid is seriously insufficient and the voltage stability margin of the network is greatly reduced. The dynamic reactive power allocation strategy for AC/DC grid with a lot of new energy is studied in this paper. Firstly, the sensitivity analysis method of AC/DC hybrid system is presented. Then a dynamic reactive power allocation evaluation index considering both steady and transient characteristics is determined. And an optimization model for AC/DC grid with new energy considering both steady and transient processes is established. Finally, a dynamic reactive power allocation strategy based on quantum genetic algorithm is proposed. The proposed strategy is applied to the actual power grid, and the calculation and comparative study prove the effectiveness and practicability of the strategy.

关键词： vokage stability AC/DC system dynamic reactive power allocation quantum genetic algorithm

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Research on Network Congestion Control Based on quantum genetic algorithm

Research on Network Congestion Control Based on Quantum Gene...

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International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Lei, Gang Yin, Xia Shi, Wei Zhongzhou Univ Coll Engn Technol Zhengzhou Peoples R China

ISBN: (纸本)9783038350125

An optimization mathematical model of QoS routing, which with the objectives of network congestion control, is presented in this paper. Combining quantum computation and genetic algorithm, an algorithm for network congestion control based on quantum genetic algorithm (QGA) is proposed. quantum bit and quantum rotation gate operation are used to update the chromosomes. The simulation results manifest that this algorithm is of fast speed and high efficiency and easily escape from local optimal solution. It can improve network performance and arrive at the purpose of congestion control.

关键词： Network Congestion QoS Routing quantum genetic algorithm Optimization

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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

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Matching with quantum genetic algorithm and Shape Contexts 11

Matching with Quantum Genetic Algorithm and Shape Contexts

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11th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

作者： Mezghiche, Khalil M. Melkemi, Kamal E. Foufou, Sebti Univ Biskra Dept Comp Sci Biskra Algeria Qatar Univ CENG Dept Comp Sci & Engn Doha Qatar

ISBN: (纸本)9781479971008

In this paper, we propose to combine the shape context (SC) descriptor with quantum genetic algorithms (QGA) to define a new shape matching and retrieval method. The SC matching method is based on finding the best correspondence between two point sets. The proposed method uses the QGA to find the best configuration of sample points in order to achieve the best possible matching between the two shapes. This combination of SC and QGA leads to a better retrieval results based on our tests. The SC is a very powerful discriminative descriptor which is translation and scale invariant, but weak against rotation and flipping. In our proposed quantum shape context algorithm (QSC), we use the QGA to estimate the best orientation of the target shape to ensure the best matching for rotated and flipped shapes. The experimental results showed that our proposed QSC matching method is much powerful than the classic SC method for the retrieval of shapes with orientation changes.

关键词： shape matching shape retrieval shape context quantum genetic algorithm

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