The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high a...The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high accuracy in modelling the reflection coefficients.However,amplitude inversion based on it is highly nonlinear,thus,requires nonlinear inversion techniques like the genetic algorithm(GA)which has been widely applied in seismology.The quantum genetic algorithm(QGA)is a variant of the GA that enjoys the advantages of quantum computing,such as qubits and superposition of states.It,however,suffers from limitations in the areas of convergence rate and escaping local minima.To address these shortcomings,in this study,we propose a hybrid quantum genetic algorithm(HQGA)that combines a self-adaptive rotating strategy,and operations of quantum mutation and catastrophe.While the selfadaptive rotating strategy improves the flexibility and efficiency of a quantum rotating gate,the operations of quantum mutation and catastrophe enhance the local and global search abilities,respectively.Using the exact Zoeppritz equation,the HQGA was applied to both synthetic and field seismic data inversion and the results were compared to those of the GA and QGA.A number of the synthetic tests show that the HQGA requires fewer searches to converge to the global solution and the inversion results have generally higher accuracy.The application to field data reveals a good agreement between the inverted parameters and real logs.展开更多
Directional modulation is one of the hot topics in data security researches.To fulfill the requirements of communication security in wireless environment with multiple paths,this study takes into account the factors o...Directional modulation is one of the hot topics in data security researches.To 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 modulation.Unlike 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 reflectors.Another focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna array.The quantum approach has strengths in convergence speed and the globe searching ability for the complicated model with the large-size antenna array and multiple paths.From 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 array.Our work can spur applications of the quantum evolutionary algorithm in directional modulation technology,which is also studied.展开更多
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 ...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.展开更多
Despite the critical role that middleboxes play in introducing new network functionality,management and innovation of them are still severe challenges for network operators,since traditional middleboxes based on hardw...Despite the critical role that middleboxes play in introducing new network functionality,management and innovation of them are still severe challenges for network operators,since traditional middleboxes based on hardware lack service flexibility and scalability.Recently,though new networking technologies,such as network function virtualization(NFV) and softwaredefined networking(SDN),are considered as very promising drivers to design cost-efficient middlebox service architectures,how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic.Therefore,we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN.First,a framework is designed for service placement decision,and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay.Then a heuristic solution is designed based on the improved quantum genetic algorithm.Experimental results show that our proposed method can calculate automatically the optimal placement schemes.Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.展开更多
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...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 problem.Based 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 population.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.展开更多
Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service(QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on...Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service(QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.展开更多
By introducing strong parallelism of quantum computing into evolutionary algorithm,a novel quantum genetic algorithm(NQGA)is proposed.In NQGA,a novel approach for updating the rotation angles of quantum logic gates an...By introducing strong parallelism of quantum computing into evolutionary algorithm,a novel quantum genetic algorithm(NQGA)is proposed.In 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 adopted.Several typical complex continuous functions are chosen to test the performance of NQGA.Also,NQGA is applied in selecting the best feature subset from a large number of features in radar emitter signal recognition.The 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.展开更多
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 ...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 problem.The 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 result.In 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.展开更多
The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered.Background of the model is a new model of quantum inference based on ...The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered.Background of the model is a new model of quantum inference based on quantum genetic algorithm.Quantum genetic algorithm applied on line for the quantum correlation’s type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing.Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures(as new design laws)discussed in Part I.The smart control design with guaranteed achievement of these trade-off interrelations is main goal for quantum self-organization algorithm of imperfect KB.Sophisticated synergetic quantum information effect in Part I(autonomous robot in unpredicted control situations)and II(swarm robots with imperfect KB exchanging between“master-slaves”)introduced:a new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation.Within the toolkit of classical intelligent control,the achievement of the similar synergetic information effect is impossible.Benchmarks of intelligent cognitive robotic control applications considered.展开更多
Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to ca...Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to calculate localization of the acoustic emission source.However,in back propagation(BP) neural network,the BP algorithm is a stochastic gradient algorithm virtually,the network may get into local minimum and the result of network training is dissatisfactory.It is a kind of genetic algorithms with the form of quantum chromosomes,the random observation which simulates the quantum collapse can bring diverse individuals,and the evolutionary operators characterized by a quantum mechanism are introduced to speed up convergence and avoid prematurity.Simulation results show that the modeling of neural network based on quantum genetic algorithm has fast convergent and higher localization accuracy,so it has a good application prospect and is worth researching further more.展开更多
A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR...A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By ~using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are ~achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.展开更多
Quantitative stock selection has become a research hotspot in the field of investment decision. As the data mining technology becomes mature, quantitative stock selection has made great progress. From the perspective ...Quantitative stock selection has become a research hotspot in the field of investment decision. As the data mining technology becomes mature, quantitative stock selection has made great progress. From the perspective of value investment, this paper selects top 200 stocks of A share in terms of market value. With the random forest (RF), financial characteristic variables with significant impact on SVR are screened out. At the same time with quantum genetic algorithm (QGA) superior to the traditional genetic algorithm (GA), SVR parameters are deeply and dynamically sought for, so as to build the RF-QGA-SVR model for year-to-year stock ranking. The quantitative stock selection model is built, and the empirical analysis of its stock selection performance is conducted. The conclusion is as follows: 1) Optimizing SVR with QGA has higher precision than the traditional genetic algorithm, and is more excellent than the traditional GA optimization;2) SVR after RF optimization of characteristic variables more significantly improves the accuracy of stock ranking and prediction;3) In the stock ranking obtained from the RF-QGA-SVR model, the yields of top stock portfolios are much higher than the market benchmark yield. At the same time, the yields of the top 10 stock portfolios are the highest, and the top 30 stock portfolios are the most stable. This study has positive reference significance on quantitative stock selection in the field of quantitative investment.展开更多
An engineering microburst model to generate the microburst wind field for virtual flight simulation has been presented. The model is built as a finite viscosity vortex core model based on the vortex ring theory consid...An engineering microburst model to generate the microburst wind field for virtual flight simulation has been presented. The model is built as a finite viscosity vortex core model based on the vortex ring theory considering the air viscosity,and it can solve the problem of induced velocity discontinuity at the inner region near the vortex core. Moreover,the central axis velocity is obtained by turbulence free jet theory so as to avoid the singularity.The parameters in multiple-vortex-ring microburst model are determined by improved quantum genetic algorithm( QGA) based on immune and mutation operator,and the parameters optimization of the model under condition of different maximum vertical velocity are investigated. The results show that the microburst model is effective and accurate. The simulation results fit the preset value very well,and the error is controlled within 10^(- 7).展开更多
Low-voltage electrical apparatuses(LVEAs)have many workpieces and intricate geometric structures,and the assembly process is rigid and labor-intensive,and has little balance.The assembly process cannot readily adapt t...Low-voltage electrical apparatuses(LVEAs)have many workpieces and intricate geometric structures,and the assembly process is rigid and labor-intensive,and has little balance.The assembly process cannot readily adapt to changes in assembly situations.To address these issues,a collaborative assembly is proposed.Based on the requirements of collaborative assembly,a colored Petri net(CPN)model is proposed to analyze the performance of the interaction and self-government of robots in collaborative assembly.Also,an artificial potential field based planning algorithm(AFPA)is presented to realize the assembly planning and dynamic interaction of robots in the collaborative assembly of LVEAs.Then an adaptive quantum genetic algorithm(AQGA)is developed to optimize the assembly process.Lastly,taking a two-pole circuit-breaker controller with leakage protection(TPCLP)as an assembly instance,comparative results show that the collaborative assembly is cost-effective and flexible in LVEA assembly.The distribution of resources can also be optimized in the assembly.The assembly robots can interact dynamically with each other to accommodate changes that may occur in the LVEA assembly.展开更多
To improve user experience of composite Web services, a user-aware quality of service (QoS) based Web services composition model is proposed. Under such model, a Web services selection method based on quantum geneti...To improve user experience of composite Web services, a user-aware quality of service (QoS) based Web services composition model is proposed. Under such model, a Web services selection method based on quantum genetic algorithm is proposed. This algorithm uses quantum bit encoding, dynamic step-length quantum gate angle adjustment, neighborhood service search and dynamic punishment strategy to expand search scope and speed up convergence. Simulation experiment shows that this algorithm is more efficient than other existing algorithms in Web services selection.展开更多
This article studies multi-constraints least-cost multicast routing problem in internet protocol over dense wavelength division multiplexing (IP/DWDM) networks. To address this problem, an individual-difference-base...This article studies multi-constraints least-cost multicast routing problem in internet protocol over dense wavelength division multiplexing (IP/DWDM) networks. To address this problem, an individual-difference-based quantum genetic algorithm (IDQGA) is proposed. This algorithm considers individual differences among chromosomes by introducing an adaptive rotation angle step determination scheme and a grouping-based quantum mutation operation. Simulations are conducted over network topologies. The results indicate that compared with other heuristic algorithms, IDQGA has better optimal performance on solving quality of service (QoS) multicast routing problem in IP/DWDM networks and is characterized by strong robustness, high success ratio and excellent capability on global searching.展开更多
基金supported by the National Natural Science Foundation of China(U19B6003,42122029)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX 202003)partially supported by SEG/WesternGeco Scholarship,SEG Foundation/Chevron Scholarship,and SEG/Norman and Shirley Domenico Scholarship
文摘The amplitude versus offset/angle(AVO/AVA)inversion which recovers elastic properties of subsurface media is an essential tool in oil and gas exploration.In general,the exact Zoeppritz equation has a relatively high accuracy in modelling the reflection coefficients.However,amplitude inversion based on it is highly nonlinear,thus,requires nonlinear inversion techniques like the genetic algorithm(GA)which has been widely applied in seismology.The quantum genetic algorithm(QGA)is a variant of the GA that enjoys the advantages of quantum computing,such as qubits and superposition of states.It,however,suffers from limitations in the areas of convergence rate and escaping local minima.To address these shortcomings,in this study,we propose a hybrid quantum genetic algorithm(HQGA)that combines a self-adaptive rotating strategy,and operations of quantum mutation and catastrophe.While the selfadaptive rotating strategy improves the flexibility and efficiency of a quantum rotating gate,the operations of quantum mutation and catastrophe enhance the local and global search abilities,respectively.Using the exact Zoeppritz equation,the HQGA was applied to both synthetic and field seismic data inversion and the results were compared to those of the GA and QGA.A number of the synthetic tests show that the HQGA requires fewer searches to converge to the global solution and the inversion results have generally higher accuracy.The application to field data reveals a good agreement between the inverted parameters and real logs.
基金This work was supported by the NSFC(Grant Nos.61671087,61962009 and 61003287)the Fok Ying Tong Education Foundation(Grant No.131067)+3 种基金the Major Scientific and Technological Special Project of Guizhou Province(Grant No.20183001)the Foundation of State Key Laboratory of Public Big Data(Grant No.2018BDKFJJ018)the High-quality and Cutting-edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China)the Fundamental Research Funds for the Central Universities(Nos.2019XD-A02,328201915,328201917 and 328201916).
文摘Directional modulation is one of the hot topics in data security researches.To 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 modulation.Unlike 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 reflectors.Another focus is a quantum genetic algorithm applied to optimize antenna excitation in a phased directional modulation antenna array.The quantum approach has strengths in convergence speed and the globe searching ability for the complicated model with the large-size antenna array and multiple paths.From 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 array.Our work can spur applications of the quantum evolutionary algorithm in directional modulation technology,which is also studied.
文摘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.
基金supported by the National Basic Research Program(973)of China(Nos.2012CB315901 and 2013CB329104)the National Natural Science Foundation of China(Nos.61309019,61372121,61572519,and 61502530)the National High-Tech R&D Program(863)of China(Nos.2015AA016102 and 2013AA013505)
文摘Despite the critical role that middleboxes play in introducing new network functionality,management and innovation of them are still severe challenges for network operators,since traditional middleboxes based on hardware lack service flexibility and scalability.Recently,though new networking technologies,such as network function virtualization(NFV) and softwaredefined networking(SDN),are considered as very promising drivers to design cost-efficient middlebox service architectures,how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic.Therefore,we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN.First,a framework is designed for service placement decision,and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay.Then a heuristic solution is designed based on the improved quantum genetic algorithm.Experimental results show that our proposed method can calculate automatically the optimal placement schemes.Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.
基金Supported by the National Natural Science Foundation of China(71671059,71401048,71472058,71521001)
文摘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 problem.Based 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 population.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.
基金supported by the National Natural Science Foundation of China (Grant No.60573141 and 70271050)the Natural Science Foundation of Jiangsu Province (No.BK2005146)+4 种基金the High Technology Research Program of Jiangsu Province (No.BG2004004 and BG2005038,BG2006001)the Hi-Technology Research and Development Program of China (No.2006AA01Z219)Foundation of National Laboratory for Modern Communications (No.9140C1101010603)the High Technology Research Programme of Nanjing (No.2006RZ105)the Foundation of Jiangsu Key Laboratory of Computer Information Processing Technology (No.kjs050001 and kjs0606).
文摘Nowadays,two trends appear in the application of sensor networks in which both multi-service and quality of service(QoS)are supported.In terms of the goal of low energy consumption and high connectivity,the control on topology is crucial.The algorithm of topology control based on quantum genetic algorithm in sensor networks is proposed.An advantage of the quantum genetic algorithm over the conventional genetic algorithm is demonstrated in simulation experiments.The goals of high connectivity and low consumption of energy are reached.
基金supported by the National Nat-ural Science Foundation of China (No.60572143)by the National EW Lab Pre-research Foundation (No.NEWL51435QT220401).
文摘By introducing strong parallelism of quantum computing into evolutionary algorithm,a novel quantum genetic algorithm(NQGA)is proposed.In 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 adopted.Several typical complex continuous functions are chosen to test the performance of NQGA.Also,NQGA is applied in selecting the best feature subset from a large number of features in radar emitter signal recognition.The 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.
基金supported by National Nature Science Foundation of China,and the supporting project is“Study on parallel intelligent optimization simulation with combination of qualitative and quantitative method”(61004089)supported by the Graduate Student Innovation Practice Foundation of Beihang University in China(YCSJ-01-201205),which is“Research of an efficient and intelligent optimization method and application in aircraft shape design”.
文摘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 problem.The 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 result.In 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.
文摘The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered.Background of the model is a new model of quantum inference based on quantum genetic algorithm.Quantum genetic algorithm applied on line for the quantum correlation’s type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing.Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures(as new design laws)discussed in Part I.The smart control design with guaranteed achievement of these trade-off interrelations is main goal for quantum self-organization algorithm of imperfect KB.Sophisticated synergetic quantum information effect in Part I(autonomous robot in unpredicted control situations)and II(swarm robots with imperfect KB exchanging between“master-slaves”)introduced:a new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation.Within the toolkit of classical intelligent control,the achievement of the similar synergetic information effect is impossible.Benchmarks of intelligent cognitive robotic control applications considered.
基金supported by the National Natural Science Foundation of China (51075068)the Southeast University Science Foundation Funded Program (KJ2009348)
文摘Due to defects of time-difference of arrival localization,which influences by speed differences of various model waveforms and waveform distortion in transmitting process,a neural network technique is introduced to calculate localization of the acoustic emission source.However,in back propagation(BP) neural network,the BP algorithm is a stochastic gradient algorithm virtually,the network may get into local minimum and the result of network training is dissatisfactory.It is a kind of genetic algorithms with the form of quantum chromosomes,the random observation which simulates the quantum collapse can bring diverse individuals,and the evolutionary operators characterized by a quantum mechanism are introduced to speed up convergence and avoid prematurity.Simulation results show that the modeling of neural network based on quantum genetic algorithm has fast convergent and higher localization accuracy,so it has a good application prospect and is worth researching further more.
文摘A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By ~using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are ~achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.
文摘Quantitative stock selection has become a research hotspot in the field of investment decision. As the data mining technology becomes mature, quantitative stock selection has made great progress. From the perspective of value investment, this paper selects top 200 stocks of A share in terms of market value. With the random forest (RF), financial characteristic variables with significant impact on SVR are screened out. At the same time with quantum genetic algorithm (QGA) superior to the traditional genetic algorithm (GA), SVR parameters are deeply and dynamically sought for, so as to build the RF-QGA-SVR model for year-to-year stock ranking. The quantitative stock selection model is built, and the empirical analysis of its stock selection performance is conducted. The conclusion is as follows: 1) Optimizing SVR with QGA has higher precision than the traditional genetic algorithm, and is more excellent than the traditional GA optimization;2) SVR after RF optimization of characteristic variables more significantly improves the accuracy of stock ranking and prediction;3) In the stock ranking obtained from the RF-QGA-SVR model, the yields of top stock portfolios are much higher than the market benchmark yield. At the same time, the yields of the top 10 stock portfolios are the highest, and the top 30 stock portfolios are the most stable. This study has positive reference significance on quantitative stock selection in the field of quantitative investment.
基金National Natural Science Foundation of China(No.61032001)
文摘An engineering microburst model to generate the microburst wind field for virtual flight simulation has been presented. The model is built as a finite viscosity vortex core model based on the vortex ring theory considering the air viscosity,and it can solve the problem of induced velocity discontinuity at the inner region near the vortex core. Moreover,the central axis velocity is obtained by turbulence free jet theory so as to avoid the singularity.The parameters in multiple-vortex-ring microburst model are determined by improved quantum genetic algorithm( QGA) based on immune and mutation operator,and the parameters optimization of the model under condition of different maximum vertical velocity are investigated. The results show that the microburst model is effective and accurate. The simulation results fit the preset value very well,and the error is controlled within 10^(- 7).
基金supported by the National Natural Science Foundation of China(No.52175124)the Zhejiang Provincial Natural Science Foundation of China(No.LZ21E050003)the Fundamental Research Funds for Zhejiang Universities,China(No.RF-C2020004)。
文摘Low-voltage electrical apparatuses(LVEAs)have many workpieces and intricate geometric structures,and the assembly process is rigid and labor-intensive,and has little balance.The assembly process cannot readily adapt to changes in assembly situations.To address these issues,a collaborative assembly is proposed.Based on the requirements of collaborative assembly,a colored Petri net(CPN)model is proposed to analyze the performance of the interaction and self-government of robots in collaborative assembly.Also,an artificial potential field based planning algorithm(AFPA)is presented to realize the assembly planning and dynamic interaction of robots in the collaborative assembly of LVEAs.Then an adaptive quantum genetic algorithm(AQGA)is developed to optimize the assembly process.Lastly,taking a two-pole circuit-breaker controller with leakage protection(TPCLP)as an assembly instance,comparative results show that the collaborative assembly is cost-effective and flexible in LVEA assembly.The distribution of resources can also be optimized in the assembly.The assembly robots can interact dynamically with each other to accommodate changes that may occur in the LVEA assembly.
基金supported by the National Science and Technology Pillar Program (2008BAH37B04)
文摘To improve user experience of composite Web services, a user-aware quality of service (QoS) based Web services composition model is proposed. Under such model, a Web services selection method based on quantum genetic algorithm is proposed. This algorithm uses quantum bit encoding, dynamic step-length quantum gate angle adjustment, neighborhood service search and dynamic punishment strategy to expand search scope and speed up convergence. Simulation experiment shows that this algorithm is more efficient than other existing algorithms in Web services selection.
基金the National Natural Science Foundation of China (60572021, 90704006)the National Basic Research Program of China (2007CB310705)+3 种基金the Hi-Tech Research and Development Program of China (2007AA01Z247)PCSIRT (IRT0609)111 Project (B07005)ISTCP (2006DFA11040)
文摘This article studies multi-constraints least-cost multicast routing problem in internet protocol over dense wavelength division multiplexing (IP/DWDM) networks. To address this problem, an individual-difference-based quantum genetic algorithm (IDQGA) is proposed. This algorithm considers individual differences among chromosomes by introducing an adaptive rotation angle step determination scheme and a grouping-based quantum mutation operation. Simulations are conducted over network topologies. The results indicate that compared with other heuristic algorithms, IDQGA has better optimal performance on solving quality of service (QoS) multicast routing problem in IP/DWDM networks and is characterized by strong robustness, high success ratio and excellent capability on global searching.