In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tig...In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method.展开更多
针对心肌梗死(myocardial infarction,MI)12导联高频心电信号(high frequency electrocardiogram,HFECG)全局特征聚类问题,提出了一种计算机自动聚类算法。收集MIT-BIH标准心电数据库中的健康心电信号、早期心肌梗死心电信号、急性期心...针对心肌梗死(myocardial infarction,MI)12导联高频心电信号(high frequency electrocardiogram,HFECG)全局特征聚类问题,提出了一种计算机自动聚类算法。收集MIT-BIH标准心电数据库中的健康心电信号、早期心肌梗死心电信号、急性期心肌梗死心电信号、近期心肌梗死心电信号进行处理。应用二维主分量判别法(two dimensional principal component analysis,2D-PCA)对12导联HF-ECG进行融合特征提取,并应用基于均方差属性加权的遗传模拟退火K-means改进聚类算法。与常规K-means聚类算法相比,特征值更加简单直观,所提算法平均分类精度有较大提高,能对12导联HF-ECG进行更有效的聚类。展开更多
针对径向基函数(Radial Basis Function,RBF)神经网络算法在无线网络室内定位中拓扑结构和网络参数难以确定,其定位效果不理想的问题,提出了一种用核主成分分析的模糊C均值聚类算法(Fuzzy C-Means clustering algorithm based on Kernel...针对径向基函数(Radial Basis Function,RBF)神经网络算法在无线网络室内定位中拓扑结构和网络参数难以确定,其定位效果不理想的问题,提出了一种用核主成分分析的模糊C均值聚类算法(Fuzzy C-Means clustering algorithm based on Kernel Principal Component Analysis,KPCA-FCM)和模拟退火自适应遗传算法(Simulated Annealing adaptive Genetic Algorithm,SAGA)优化RBF神经网络的无线室内定位算法。首先利用KPCA对原始训练数据样本进行数据预处理,再通过KPCA-FCM算法计算出最优聚类数目和聚类中心点;其次将聚类数目和聚类中心点作为隐含层神经元个数和中心值,创建RBF神经网络,并将其网络参数映射到SAGA算法中;再次由SAGA算法进行网络参数寻优,把最优的解映射回RBF神经网络;最后利用样本数据对RBF神经网络进行训练和测试,完成建立RBF神经网络算法模型。实验表明,在相同的环境中,所提算法比传统RBF神经网络定位精度提高了48.41%。展开更多
In this paper, we find the optimal precursors which can cause double-gyre regime transitions based on conditional nonlinear optimal perturbation (CNOP) method with Regional Ocean Modeling System (ROMS). Firstly, we si...In this paper, we find the optimal precursors which can cause double-gyre regime transitions based on conditional nonlinear optimal perturbation (CNOP) method with Regional Ocean Modeling System (ROMS). Firstly, we simulate the multiple-equilibria regimes of double-gyre circulation under different viscosity coefficient and obtain the bifurcation diagram, then choose two equilibrium states (called jet-up state and jet-down state) as reference states respectively, propose Principal Component Analysis-based Simulated Annealing (PCASA) algorithm to solve CNOP-type initial perturbations which can induce double-gyre regime transitions between jet-up state and jet-down state. PCASA algorithm is an adjoint-free method which searches optimal solution randomly in the whole solution space. In addition, we investigate CNOP-type initial perturbations how to evolve with time. The results show:(1) the CNOP-type perturbations present a two-cell structure, and gradually evolves into a three-cell structure at predictive time;(2) by superimposing CNOP-type perturbations on the jet-up state and integrating ROMS, double-gyre circulation transfers from jet-up state to jet-down state, and vice versa, and random initial perturbations don't cause the transitions, which means CNOP-type perturbations are the optimal precursors of double-gyre regime transitions;(3) by analyzing the transition process of double-gyre regime transitions, we find that CNOP-type initial perturbations obtain energy from the background state through both barotropic and baroclinic instabilities, and barotropic instability contributes more significantly to the fast-growth of the perturbations. The optimal precursors and the dynamic mechanism of double-gyre regime transitions revealed in this paper have an important significance to enhance the predictability of double-gyre circulation.展开更多
基金funded by the National Natural Science Foundation of China(42174131)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-03).
文摘In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method.
文摘针对心肌梗死(myocardial infarction,MI)12导联高频心电信号(high frequency electrocardiogram,HFECG)全局特征聚类问题,提出了一种计算机自动聚类算法。收集MIT-BIH标准心电数据库中的健康心电信号、早期心肌梗死心电信号、急性期心肌梗死心电信号、近期心肌梗死心电信号进行处理。应用二维主分量判别法(two dimensional principal component analysis,2D-PCA)对12导联HF-ECG进行融合特征提取,并应用基于均方差属性加权的遗传模拟退火K-means改进聚类算法。与常规K-means聚类算法相比,特征值更加简单直观,所提算法平均分类精度有较大提高,能对12导联HF-ECG进行更有效的聚类。
基金Supported by the National Natural Science Foundation of China(No.41405097)the Fundamental Research Funds for the Central Universities of China in 2017
文摘In this paper, we find the optimal precursors which can cause double-gyre regime transitions based on conditional nonlinear optimal perturbation (CNOP) method with Regional Ocean Modeling System (ROMS). Firstly, we simulate the multiple-equilibria regimes of double-gyre circulation under different viscosity coefficient and obtain the bifurcation diagram, then choose two equilibrium states (called jet-up state and jet-down state) as reference states respectively, propose Principal Component Analysis-based Simulated Annealing (PCASA) algorithm to solve CNOP-type initial perturbations which can induce double-gyre regime transitions between jet-up state and jet-down state. PCASA algorithm is an adjoint-free method which searches optimal solution randomly in the whole solution space. In addition, we investigate CNOP-type initial perturbations how to evolve with time. The results show:(1) the CNOP-type perturbations present a two-cell structure, and gradually evolves into a three-cell structure at predictive time;(2) by superimposing CNOP-type perturbations on the jet-up state and integrating ROMS, double-gyre circulation transfers from jet-up state to jet-down state, and vice versa, and random initial perturbations don't cause the transitions, which means CNOP-type perturbations are the optimal precursors of double-gyre regime transitions;(3) by analyzing the transition process of double-gyre regime transitions, we find that CNOP-type initial perturbations obtain energy from the background state through both barotropic and baroclinic instabilities, and barotropic instability contributes more significantly to the fast-growth of the perturbations. The optimal precursors and the dynamic mechanism of double-gyre regime transitions revealed in this paper have an important significance to enhance the predictability of double-gyre circulation.
