Table of Content

15 December 2024, Volume 41 Issue 6 Previous Issue   

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Adaptive Level Set Evolution Model Combined with Local Entropy Gradient ZHU Weili, DENG Xiaohua, WANG Yan 2024, 41 (6):  991-1005.  doi: 10.3969/j.issn.1005-3085.2024.06.001 Abstract ( 22 )   Save To solve the problem that active contour model based on image edge information is sensitive to initial contour, a new adaptive level set evolution model combining local entropy gradient is proposed. The local entropy gradient and regularized image gradient are used to construct the area term weight coefficients to replace the original constant coefficient.  The novel weight coefficients can change the symbol adaptively with the image information so that the evolution function adaptively moves up and down according to the image information, allowing constant initialization. The proposed model solves the initial contour sensitivity problem and allows constant initialization of the level set. Experiments verify that the model has good segmentation effect on gray uneven image, noise image, partial multi-object image and subjective edge image. In addition, the proposed adaptive weight coefficients can be used in other segmentation models which involve  area energy terms. Related Articles | Metrics

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A Robust Evolutionary Clustering Algorithm Based on Local Structure Self-expression LI Chunzhong, JU Wenliang, JING Kaili, GUI Yang 2024, 41 (6):  1006-1020.  doi: 10.3969/j.issn.1005-3085.2024.06.002 Abstract ( 84 )   Save Clustering is an unsupervised learning method that measures the similarity and difference between data by analyzing sample features. It utilizes the characteristics of high intra cluster similarity and large inter cluster differences to automate the process of grouping data. It is widely used in fields such as computer vision, text mining, biological information and so on. There is still improvement room in clustering algorithms in terms of robustness, universality, and class number selection, and the effectiveness of the algorithms is largely influenced by the density and manifold of the dataset. This paper proposes a robust evolutionary clustering algorithm based on local structure self-expression. This algorithm uses radial basis functions and adds prior information to obtain local density difference features of the data, constructing a new similarity measure. In this process, the extraction mechanism of local structural features of data and the recognition mechanism of stable classes are integrated, making clustering more robust and universal. Dynamic evolutionary clustering has natural advantages in these two aspects, which can continuously optimize clustering results during the dynamic clustering process, resulting in significant improvements in clustering performance. The new algorithm integrates local and global features through self-expression of the structure information in the dataset, while monitoring the stability of the class during dynamic evolution, in order to obtain better final clustering results. The experimental results on both synthetic and real datasets demonstrate that the clustering performance of the new algorithm is superior. Related Articles | Metrics

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Regularization Tensor Completion Algorithm for Hyperspectral Image Data XIE Yajun 2024, 41 (6):  1021-1040.  doi: 10.3969/j.issn.1005-3085.2024.06.003 Abstract ( 29 )   Save The efficient digital image processing technology is widely used in the fields of big data and artificial intelligence, especially hyperspectral image processing, which has become a hot topic in academic research. Hyperspectral data are usually stored in the form of high-dimensional arrays. However, the matrixization method of high-dimensional arrays lacks generalization ability as its internal structure cannot be accurately interpreted. In this paper, a novel tensor completion algorithm is proposed to reconstruct hyperspectral image and analyze the corresponding data. Firstly, a tensor kernel norm optimization model with regularization is established for hyperspectral image processing. Secondly, a new multi-multiplier algorithm with variable parameter alternating-direction is proposed to solve the tensor optimization model, and the convergence theory is established. Finally, the feasibility and effectiveness of the algorithm are verified by multi-dimensional comparison and analysis with some current effective algorithms. Related Articles | Metrics

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Global $\mu$-stability Analysis of Quaternion-valued Cohen-Grossberg Neural Networks with Time-varying Delays YANG Yanping, CHEN Zhanheng 2024, 41 (6):  1041-1052.  doi: 10.3969/j.issn.1005-3085.2024.06.004 Abstract ( 27 )   Save This research investigates the global $\mu$-stability of a quaternion-valued Cohen-Grossberg neural network with time-varying delays. The study first introduces the concept of time-varying delays into the neural network model, thereby constructing a more precise model that reflects the dynamic characteristics of neurons. Subsequently, by applying the theorem of homeomorphism, the uniqueness of equilibrium points is discussed, and the sufficient conditions for the existence of a unique equilibrium point in the system are determined. In view of the non-commutativity property of quaternion multiplication, the quaternion-valued neural network system is decomposed into four equivalent real-valued neural network systems. On this basis, by constructing an appropriate Lyapunov function, the sufficient conditions for the global $\mu$-stability of the system are obtained. Finally, through numerical simulation experiments, the global $\mu$-stability of the system is verified, thereby confirming the effectiveness and accuracy of the theoretical conclusions. Related Articles | Metrics

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Passivity of Memristive Bidirectional Associative Memory Neural Networks with Multi-proportional Delays WANG Fen 2024, 41 (6):  1053-1073.  doi: 10.3969/j.issn.1005-3085.2024.06.005 Abstract ( 32 )   Save Under the framework of Filippov solutions, passivity analysis of memristive BAM neural networks with multi-proportional delays can be guaranteed by constructing suitable Lyapunov-Krasovskii functional, Jensen's inequality, Lemma of Schur Complement, the theory of set-valued maps and functional differential equations with discontinuous right-hand sides. Moreover, the terms of multi-proportional delays are deformed by nonlinear transformation in this paper. We have successfully established sufficient conditions for the passivity of BAM memristive neural networks with multiple proportional delays. These conditions not only reveal the relationship between system parameters and passivity, but also provide theoretical basis and guidance for designing stable, reliable, and well passive BAM memristive neural networks. Finally, two numerical examples are exploited to show the effectiveness of the derived LMI-based passivity conditions. The work presented in this article not only deepens the understanding of the dynamic behavior of BAM memristive neural networks, but also provides a new perspective for the design and optimization of this type of network in practical applications. Related Articles | Metrics

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Dynamics of a Degenerate Reaction-diffusion Cholera Model with Seasonality CHU Huijie 2024, 41 (6):  1074-1086.  doi: 10.3969/j.issn.1005-3085.2024.06.006 Abstract ( 31 )   Save There are two transmission routes for cholera: the direct (human-to-human) and indirect (human-to-environment) transmission. Considering these two transmission mechanisms, a partially degenerate reaction-diffusion equation model is constructed to study the effects of seasonality and human activity on the spreading of cholera. First, we obtain the existence, un-iqueness and non-negativity of the solution and prove that the solution is ultimately uniformly bounded. Second, the basic reproduction number is identified, and it is shown that the disease will extinct when the basic reproduction number is less than 1. When the basic reproduction number is greater than 1, the global attractivity of the unique positive periodic solution is established using monotonic iteration method, which indicates that the disease will persist. Finally, we numerically explore the influences of key model parameters on the basic reproduction number. The results show that the spatial heterogeneity may reduce the risk of disease transmission, while the seasonal factors do not always contribute to the spread of cholera. Related Articles | Metrics

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Application of Infectious Disease Dynamics in Prevention and Control of COVID-19 in Heilongjiang Province WANG Jingnan, XIA Xiaofeng, ZHANG Hongpeng 2024, 41 (6):  1087-1097.  doi: 10.3969/j.issn.1005-3085.2024.06.007 Abstract ( 42 )   Save In this paper, a dynamic model of new coronary infectious disease is established by using differential equations. The existence and stability of equilibria are proved. Based on the epidemic data published by the Health Commission of Heilongjiang Province, the model parameters are estimated by the least-squares algorithm. In addition, the estimated parameters are substituted into the model for fitting comparison. The development of the third COVID-19 epidemic in Heilongjiang province is predicted. The effective strategies for prevention and control of the recurrence of COVID-19 are proposed. Related Articles | Metrics

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Modeling and Analysis of Continuous and State Impulsive Releases of Sterile Mosquitoes GAN Jingwen, SONG Ge 2024, 41 (6):  1098-1108.  doi: 10.3969/j.issn.1005-3085.2024.06.008 Abstract ( 40 )   Save Considering the impact of sterile mosquitoes on disease transmission, we established  two mathematical models of different releasing methods. Firstly, a mathematical model for continuously releasing sterile mosquitoes was established, and the stability of each equilibrium of the system were proved by the theory of continuous dynamic system. Secondly, in order to consider more rigorous and realistic situations, a model with state impulsive releasing sterile mosquitoes was presented by using the geometric theory and successor functions of semi-continuous dynamical systems. In the meantime, the existences of order one periodic solution of the model and its orbital asymptotic stability are investigated. The results showed that the spread of the disease can be effectively controlled by releasing a certain amount of sterile mosquitoes in proportion to the total number of wild mosquitoes and sterile mosquitoes. Related Articles | Metrics

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Local Discontinuous Petrov-Galerkin Method for Simulating Solitary Waves of the Coupled Nonlinear Schr\"{o}dinger Equations ZHAO Guozhong, YU Xijun 2024, 41 (6):  1109-1132.  doi: 10.3969/j.issn.1005-3085.2024.06.009 Abstract ( 56 )   Save The coupled nonlinear Schr\"{o}dinger equations have important applications in many areas of physics, such as quantum physics, nonlinear optics, crystal physics, Bose-Einstein condensates, water wave dynamics and so on. In this paper, a local discontinuous Petrov-Galerkin method is developed. The coupled nonlinear Schr\"{o}dinger equations are firstly rewritten as a first order differential system. The spacial discretization is accomplished by the discontinuous Petrov-Galerkin method. The third order total variation diminishing Runge-Kutta method is used to finish the temporal discretization. The numerical experiments shown that the algori-thm can reach its optimal convergence order for both linear and quadratic elements. The mass, momentum and energy conservation quantities are evaluated by some numerical examples. The algorithm can simulate the single soliton propagation, double soliton collision and three soliton collision phenomena very well. In addition, the algorithm can simulate the complex wave interaction or propagation in a long time interval. Furthermore, the scheme can simulate the soliton transmission and soliton creation phenomena. Related Articles | Metrics

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Research on Tourist Flow Prediction Based on IMPA-RELM ZHAN Yichang, QIN Xiwen, CHEN Dongxue, DONG Xiaogang, XU Dingxin 2024, 41 (6):  1133-1143.  doi: 10.3969/j.issn.1005-3085.2024.06.010 Abstract ( 31 )   Save Tourist flow forecasting is an important research problem in the field of tourism management, which is related to the formulation of tourism policy and the management of tourist attractions. In this paper, a method for predicting the tourist flow of tourist attrac-tions based on the improved marine predator algorithm (MPA) optimization regularized extreme learning machine is proposed. First, in order to adaptively balance the exploration and exploitation status, this paper proposes a MPA based on population diversity and population aggregation, which gives full play to the exploration and exploitation performance of MPA algorithm. The IMPA optimizes the weight and bias of the regularized extreme learning machine (IMPA-RELM), and uses the normalized root mean square error as the fitness function to determine the optimal weight and bias parameters. Finally, the built IMPA-RELM model is applied to the prediction of daily tourist flow in Jiuzhaigou and Chagan Lake scenic spots. The experimental results show that the proposed IMPA-RELM model not only significantly improves the performance of the RELM model, but also has more superior prediction performance and generalization ability compared with the baseline models such as LS-SVM, BPNN and LSTM. Thus, the novel method can provide important reference for the operation and management of scenic spots and the formulation of tourism policies. Related Articles | Metrics

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Bootstrap Inference of Exposure Level with Skew-normal One-way Classification Random Effect Model YE Rendao, YANG Jianan 2024, 41 (6):  1144-1154.  doi: 10.3969/j.issn.1005-3085.2024.06.011 Abstract ( 33 )   Save To assess exposure level in a work environment, we consider the interval estimation and hypothesis testing problems of exposure level based on the skew-normal one-way classification random effect model. Firstly, the EM algorithm is used to give the maximum likelihood estimation of unknown parameters. Secondly, based on the Bootstrap approach, three types of Bootstrap confidence intervals for the individual average exposure level are constructed. The Monte Carlo simulation results indicate that the improved percentile Bootstrap confidence interval performs best in the sense of coverage probability, and the Bootstrap standard confidence interval performs best in the sense of upper confidence limit. Finally, the above approaches are applied to the real data example of styrene exposures to verify the reasonableness and effectiveness of the proposed approaches. Related Articles | Metrics

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Transient and Steady State Analysis of M/G/1 Queueing System with Randomized Overhaul $\langle p,Y \rangle $-policy LI Zhanyu, TANG Yinghui 2024, 41 (6):  1155-1169.  doi: 10.3969/j.issn.1005-3085.2024.06.012 Abstract ( 33 )   Save This paper considers the M/G/1 queueing system with randomized overhaul $\langle p,Y \rangle $-policy, in which when the system becomes empty, the system is overhauled with probability $p ( 0\le p\le 1 )$ and the length of overhauling time is a random variable with general distribution. Firstly, we analyze the embedded Markov chain of queue length, and obtain the probability generating function of its steady-state distribution. Secondly, the transient distribution of the queue size at any time $t$ is discussed, and the expressions of the Laplace transform of the transient queue length distribution with respect to time $t$ are presented. Meanwhile, based on the transient analysis of the queue length, the recursive formulas of the steady-state distribution of the queue length are obtained by employing L'Hospital rule. Furthermore, the stochastic decomposition structure of the steady-state queue size is presented. Finally, numerical examples are provided to determine the optimal overhaul policy for economizing the system cost under a given cost structure. Related Articles | Metrics

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Research on Location Decision and Optimization of 5G Base Station Based on Particle Swarm Optimization Algorithm WANG Yirong, CHEN Changlong, YU Zhou 2024, 41 (6):  1170-1178.  doi: 10.3969/j.issn.1005-3085.2024.06.013 Abstract ( 131 )   Save With the advent of the 5G communication era, the communication demand between different regions has risen significantly, so the importance of base station construction has been increasing. Current communication facilities can not meet the growing needs of remote communication, it is necessary to build high-quality 5G base stations to meet the requirements of 5G technology. In the process of 5G base station construction, 5G base station location decision and optimization are of great significance. Therefore, this paper proposes a 5G base station location decision and optimization method based on the particle swarm optimization algorithm. In view of the difficulty of implementing meta-heuristic calculation due to the huge amount of factor transmission in the construction of 5G base stations, as well as the situation of 5G associated transmission, the optimization model of 5G base station location decision is built with comprehensive consideration of coverage objectives and communication quality objectives. By initializing particle swarm, evaluating fitness, updating individual optimal and group optimal solutions, adjusting speed and position, and iterative optimization, the particle swarm optimization algorithm obtains the optimization result of 5G base station location decision. The experimental results show that this method can effectively optimize the location decision of 5G base stations, and can be widely used in the field of 5G base station location decision, so as to promote the further development of modern communication technology. Related Articles | Metrics

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An Eco-epidemiological Model with Saturation Incidence WANG Lingshu, LI Mengyuan, WANG Yan 2024, 41 (6):  1179-1188.  doi: 10.3969/j.issn.1005-3085.2024.06.014 Abstract ( 86 )   Save In this paper, the stability of an eco-epidemiological predator-prey model with saturation incidence. Using the theory of time-delay differential equations, the local stability of feasible equilibria is studied, and sufficient conditions for the occurrence of Hope branches at coexisting equilib are obtained. By constructing appropriate Lyapunov functional and applying the LaSalle invariance principle, the global asymptotic stability of feasible equilibria is discussed, and sufficient conditions are obtained for the elimination and spread of diseases to ultimately form endemic diseases. Related Articles | Metrics