检索结果-内蒙古大学图书馆

Size-efficient sparse population for strictly structured quantum genetic algorithm

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2022年 135卷 159-171页

作者： Kim, Jun Suk Ahn, Chang Wook Gwangju Insti Ute Sci & Technol Gwangju South Korea

quantum genetic algorithm is a field of research to discover a potential structure to realize an effective heuristic, evolutionary optimization technique powered by quantum computation. Apart from contemporary efforts to look for a novel quantum evolutionary design, some studies suggest the idea of strictly structured quantum genetic algorithm, which rigorously imitates the classical practice via a sparse population to sample a few individuals from the given problem's domain, as opposed to the conventional quantum practice that transforms the entire domain into a population itself. Albeit having its own advantages, the algorithm requires to periodically measure and reinitialize the quantum system over generations. It therefore leads to several computational inefficiency issues including the wasteful population initialization, during which individuals that rather marginally contribute to the overall optimization are iteratively generated. This paper proposes that the algorithmic inefficiency from the mentioned problem can be alleviated by preemptively eliminating a large portion of undesirable individuals and still maintain the tasked optimization result to an acceptable degree. The main idea is to deliberately reduce the amount of randomness among the quantum population, thereby discarding individuals that do not contain any fitted genes. A number of tests were conducted on continuous optimization problems to validate the theory of the proposed method, resulting that it can effectively reduce the size of the involved population while minimizing the loss in the original algorithm's performance. (c) 2022 Elsevier B.V. All rights reserved.

关键词： quantum genetic algorithm Evolutionary computation Optimization Metaheuristics Grover's algorithm Population setup

来源：评论

学校读者我要写书评

暂无评论

Autonomous detection of myocarditis based on the fusion of improved quantum genetic algorithm and adaptive differential evolution optimization back propagation neural network

引用

HEALTH INFORMATION SCIENCE AND SYSTEMS 2023年第1期11卷 1-23页

作者： Wu, Lei Guo, Shuli Han, Lina Song, Xiaowei Zhao, Zhilei Cekderi, Anil Baris Beijing Inst Technol Sch Automat Natl Key Lab Autonomous Intelligent Unmanned Syst Beijing Peoples R China Chinese Peoples Liberat Army Gen Hosp Med Ctr 2 Natl Clin Res Ctr Geriatr Dis Dept Cardiol Beijing Peoples R China

Myocarditis is cardiac damage caused by a viral infection. Its result often leads to a variety of arrhythmias. However, rapid and reliable identification of myocarditis has a great impact on early diagnosis, expedited treatment, and improved patient survival rates. Therefore, a novel strategy for the autonomous detection of myocarditis is suggested in this work. First, the improved quantum genetic algorithm (IQGA) is proposed to extract the optimal features of ECG beat and heart rate variability (HRV) from raw ECG signals. Second, the backpropagation neural network (BPNN) is optimized using the adaptive differential evolution (ADE) algorithm to classify various ECG signal types with high accuracy. This study examines analogies among five different ECG signal types: normal, abnormal, myocarditis, myocardial infarction (MI), and prior myocardial infarction (PMI). Additionally, the study uses binary and multiclass classification to group myocarditis with other cardiovascular disorders in order to assess how well the algorithm performs in categorization. The experimental results demonstrate that the combination of IQGA and ADE-BPNN can effectively increase the precision and accuracy of myocarditis autonomous diagnosis. In addition, HRV assesses the method's robustness, and the classification tool can detect viruses in myocarditis patients one week before symptoms worsen. The model can be utilized in intensive care units or wearable monitoring devices and has strong performance in the detection of myocarditis.

关键词： Electrocardiogram quantum genetic algorithm Feature classification Back propagation neural network Myocarditis detection

来源：评论

学校读者我要写书评

暂无评论

Can quantum genetic algorithm really improve quantum backpropagation neural network?

引用

quantum INFORMATION PROCESSING 2023年第3期22卷 1-18页

作者： Choe, Il-Hyang Kim, Gwang-Jin Kim, Nam-Chol Ko, Myong-Chol Ryom, Ju-Song Han, Ryong-Min Han, Tae-Gyong Han, Il Kim Il Sung Univ Fac Phys Pyongyang North Korea Kim Il Sung Univ Inst Informat Technol Pyongyang North Korea

The key point of introducing quantum genetic algorithm to a quantum backpropagation neural network model is to overcome local stagnation problem which used to be Achilles' heel. In this paper, we propose a new quantum backpropagation (QBP) model based on the quantum genetic algorithm (QGA) and make simulations with this model to see whether QGA can really upgrade QBP and, in addition, to ensure that both quantum neural networks are better than classical backpropagation (CBP) neural networks from many points of view. Numerical experiments have been built to illustrate the efficiency of the new QBP algorithm over CBP and the original QBP algorithm. However, the proposed model has shown superior results to the rest of models in terms of correction rate and training time. That is to say quantum genetic algorithm-based quantum backpropagation neural network converges earlier than the other two models and that's why we can reduce the time needed to train.

关键词： quantum neural network quantum genetic algorithm quantum backpropagation neural network Local stagnation Global search

来源：评论

学校读者我要写书评

暂无评论

Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2018年第9期77卷 10539-10551页

作者： Deng, Lizhen Zhu, Hu Zhou, Quan Li, Yansheng Nanjing Univ Posts & Telecommun Coll Telecommun & Informat Engn Nanjing 210003 Jiangsu Peoples R China Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Hubei Peoples R China

With the development of infrared technology, infrared small targets detection has attracted great interest of researchers. Top-hat filter is one of widely used methods for detecting infrared small target, and the structure elements have great influence on the performance of detection. The structure elements are desired to be adjusted adaptively. To this end, an adaptive structure elements optimization method based on quantum genetic algorithm (QGA) is introduced, and the convergence of QGA reveals the effectiveness of QGA. Experimental results show that the proposed adaptive top-hat filter based on QGA can achieve more stable infrared small target detection performance compared with the traditional top-hat filter.

关键词： Infrared small target detection Top-hat filter quantum genetic algorithm Convergence analysis

来源：评论

学校读者我要写书评

暂无评论

QGA-QGCNN: a model of quantum gate circuit neural network optimized by quantum genetic algorithm

引用

JOURNAL OF SUPERCOMPUTING 2023年第12期79卷 13421-13441页

作者： Gong, Changqing Zhu, Hongsheng Gani, Abdullah Qi, Han Shenyang Aerosp Univ Sch Comp Sci Shenyang 110000 Peoples R China Univ Malaysia Sabah Fac Comp & Informat Labuan Int Campus Labuan 87000 Malaysia

Using a global optimization algorithm to optimize the initial weights and thresholds of traditional neural network models can effectively address the problems of premature convergence and lower accuracy. However, the shortcomings such as slow convergence speed and poor local search ability still exist. In order to solve these problems, a neural network model QGA-QGCNN using a quantum genetic algorithm (QGA) to optimize quantum Gate Circuit Neural Network (QGCNN) is proposed in this paper. In QGA-QGCNN, the initial parameters of QGCNN are optimized for the strong global optimization ability and faster convergence speed by using a QGA. When dealing with more complex problems, the QGCNN model based on quantum computing has specific parallel computing capabilities and can give full play to its ability to blur uncertain problems, thereby improving detection performance. We use the authoritative 10% KDD CUP99 data set in the field of network intrusion detection to conduct simulation experiments on the proposed QGA-QGCNN model. Experimental results show that the proposed intrusion detection model has a lower false alarm rate and significant accuracy compared to conventional attack detection models. And QGCNN optimized by QGA improves the convergence performance of the model.

关键词： quantum genetic algorithm quantum gate circuit quantum neural network quantum rotation gate quantum controlled-NOT gate

来源：评论

学校读者我要写书评

暂无评论

Adaptive impedance matching using quantum genetic algorithm

引用

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

来源：评论

学校读者我要写书评

暂无评论

Comprehensive dispatch model of agricultural water resources based on multi-objective quantum genetic algorithm

引用

DESALINATION AND WATER TREATMENT 2021年 239卷 192-201页

作者： Yan, Yaning Xian Peihua Univ Sch Intelligent Sci & Informat Engn Xian 710125 Peoples R China

In order to solve the problems of slow convergence speed, poor optimization effect, the large deviation between irrigation area and yield, and low water resource utilization rate, the integrated scheduling model of agricultural water resources based on a multi-objective quantum genetic algorithm is proposed. Taking the largest fully irrigated area and the largest crop yield as the optimization goals, construct a comprehensive scheduling model of agricultural water resources. On the basis of quantum genetic algorithm and multi-objective optimization algorithm, multi-objective quantum genetic algorithm is adopted, combined with real number coding of qubits, and quantum state interference characteristics are used to carry out probability crossover. According to the non-dominant sorting group classification mechanism and the non-inferior solution level sorting population classification, multi-objective optimization strategies such as elite retention and hierarchical clustering are used to solve the comprehensive scheduling model of agricultural water resources and realize the comprehensive scheduling of agricultural water resources. The experimental results show that the deviation of irrigation area proportion and irrigation yield of the proposed algorithm is small, and the optimization effect is good, which can effectively improve the utilization rate of water resources and accelerate the

关键词： Multi-objective quantum genetic algorithm quantum genetic algorithm Multi-objective optimization algorithm quantum bit coding

来源：评论

学校读者我要写书评

暂无评论

Comprehensive evaluation of integrative drip-irrigation and fertilization using a projection pursuit model based on the improved double chains quantum genetic algorithm

引用

DESALINATION AND WATER TREATMENT 2017年 66卷 229-234页

作者： Wang, Bai Li, Yanfeng Meng, Yan Liu, Xiao Heilongjiang Water Conservancy Inst Harbin 150080 Peoples R China Inst Food Sci & Engn State Key Lab Simulat & Regulat Water Cycle River Hangzhou Zhejiang Peoples R China Inst Water Resources & Hydropower Res Beijing 100048 Peoples R China

Finding the optimal solution in a single-treatment drip-irrigation and fertilizer scheme is nontrivial because of the inherent difficulty in evaluating the overall benefit of such a scheme. To address this problem, we have developed the project pursuit model based on the improved double chains quantum genetic algorithm, and applied it to integrative drip-irrigation and fertilization. The double chains quantum genetic algorithm was introduced to optimize the projection index function and seek the optimum projection vector. This algorithm was improved by introducing an immunity operator, a simulated annealing operator, and gradually optimizing and compressing the quantum chromosome search space during the evolution process. The improved projection pursuit model was applied to maize cultivation. The results show that the optimization efficiency and global search capability improved substantially. Increased nitrogen splits promoted dry matter above ground and nitrogen uptake in the maize, and also improved the yield and the plumping of seeds. A management practice of 150-200 kg/hm(2) of nitrogen applied at three splits produced the highest production in integrative drip-irrigation and fertilizer schemes for the black soil in Northeast China.

关键词： Real coding quantum computing quantum genetic algorithm Integrative drip-irrigation Fertilizer

来源：评论

学校读者我要写书评

暂无评论

Calculation of electronic structure of a spherical quantum dot using a combination of quantum genetic algorithm and Hartree-Fock-Roothaan method

引用

INTERNATIONAL JOURNAL OF MODERN PHYSICS C 2008年第4期19卷 599-609页

作者： Cakir, Bekir Ozmen, Ayhan Atav, Ulfet Yuksel, Huseyin Yakar, Yusuf Selcuk Univ Dept Phys Fac Arts & Sci TR-42031 Konya Turkey Aksaray Univ Dept Phys Fac Arts & Sci TR-68100 Aksaray Turkey

The electronic structure of quantum Dot (QD), GaAs/AlxGa1-xAs, has been investigated by using a combination of quantum genetic algorithm (QGA) and Hartree-Fock-Roothaan (HFR) method. One-electron system with an on-center impurity is considered by assuming a spherically symmetric confining potential of finite depth. The ground and excited state energies of one-electron QD were calculated depending on the dot radius and stoichiometric ratio. Expectation values of energy were determined by using the HFR method along with Slater-Type Orbitals (STOs) and QGA was used for the wave-functions optimization. In addition, the effect of the size of the basis set on the energy of QD was investigated. We also calculated the binding energy for a dot with finite confining potential. We found that the impurity binding energy increases for the finite potential well when the dot radius decreases. For the finite potential well, the binding energy reaches a peak value and then diminishes to a limiting value corresponding to the radius for which there are no bound states in the well. Whereas in previous study, in Ref. 40, for the infinite potential well, we found that the impurity binding energy increases as the dot radius decreases.

关键词： electronic structure of spherical quantum dot quantum genetic algorithm hydrogenlike impurity Hartree-Fock Roothaan method slater-type orbital

来源：评论

学校读者我要写书评

暂无评论

Application of a quantum genetic algorithm and QTAIM analysis in the study of structural and electronic properties of neutral bimetallic clusters NaxLiy (4 ≤ x plus y ≤ 10)

引用

JOURNAL OF MOLECULAR MODELING 2020年第11期26卷 1-16页

作者： Silva, Frederico Teixeira Rocha-Santos, Acassio Firme, Caio L. De Souza, Leonardo A. Anjos, Italo C. Belchior, Jadson C. Univ Fed Pernambuco Fundamental Chem Dept Ave Prof Moraes Rego 1235Cidade Univ Recife PE Brazil Univ Fed Paraiba Dept Chem Jardim Univ S-N BR-5805190 Joao Pessoa Paraiba Brazil Univ Fed Rio Grande do Norte Inst Chem Ave Senador Salgado Filho 3000 BR-59072970 Natal RN Brazil Univ Fed Minas Gerais Dept Chem Ave Antonio Carlos 6627 BR-31270901 Belo Horizonte MG Brazil Univ Fed Mato Grosso Dept Chem Ave Fernando Correa da Costa 2367 BR-78068600 Cuiaba MG Brazil

Alloy clusters of NaxLiy (4 <= x + y <= 10) are studied by exploring the potential energy surface in the ab initio MP2 level with the support of a quantum genetic algorithm (QGA). In some cases, the structures have been also refined with DFT and coupled-cluster methods. The general trends of sodium-lithium structures are in line with previous studies. The ionization potentials and polarizabilities to all structures were calculated with MP2 method and the average error between these two properties compared with experimental data was 6% and 13%, respectively. The topological analysis based on quantum theory of atoms in molecules (QTAIM) showed that by increasing the cluster size of the diatomic system there was a decrease of atomic interaction energies. The degree of degeneracy from D3BIA aromaticity index and the analysis of the atomic charges showed the influence (by charge transfer) of the chemical element in lower quantity in the cluster with respect to the other atoms. Our achievements of comparing our theoretical results with available experimental data have demonstrated that our approach can also predict satisfactorily quantum atomic and alloy clusters properties, at least, for low nuclearities.

关键词： Metal clusters quantum genetic algorithm MP2 Coupled-cluster QTAIM D3BIA

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：