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Association Journal of CSIAM
Supervised by Ministry of Education of PRC
Sponsored by Xi'an Jiaotong University
ISSN 1005-3085  CN 61-1269/O1

Table of Content

    15 October 2023, Volume 40 Issue 5 Previous Issue    Next Issue
    Power Equipment Low-quality X-ray Images Opening/Closing Recognition Based on CNN and DUL
    ZHOU Jingbo, HAO Kunkun, WU Anbo
    2023, 40 (5):  681-698.  doi: 10.3969/j.issn.1005-3085.2023.05.001
    Abstract ( 142 )   PDF (2062KB) ( 118 )   Save
    In the process of power equipment opening/closing X-ray images acquisition by power inspection robot system, there are often low-quality problems such as image distortion, blur and low resolution, which make it difficult to identify the opening/closing state of X-ray images. Therefore, this paper proposes a deep learning recognition method based on data uncertainty learning. Firstly, the recognition algorithm is designed with three convolutional neural networks BaseNet, ResNet18 and MobileNetV3. Then, by fusing the DUL module, the convolutional neural network maps the images space to an uncertain features space that obeys the Gaussian distribution to adaptively learn the noise in low-quality X-ray images. Finally, three groups of comparative experiments are presented to simulate the influence of different quality data on the recognition performance of the model under ideal environment, harsh environment, and normal environment. The experimental results show that the model based on data uncertainty learning performs better than the deterministic model, and the average recognition accuracy of X-ray image opening/closing is increased by 2.64\%. ResNet18+DUL performs best, with an accuracy of up to 100\%, suitable for online recognition. MobileNetV3+DUL is with an accuracy of up to 97.83\%, suitable for offline recognition.
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    Event-triggered Control for Trajectory Tracking of Quadrotor Unmanned Aerial Vehicle
    YE Peiyun, YU Yang, WANG Wei
    2023, 40 (5):  699-714.  doi: 10.3969/j.issn.1005-3085.2023.05.002
    Abstract ( 115 )   PDF (1053KB) ( 119 )   Save
    In this paper, an event-trigger based on adaptive fuzzy control algorithm is proposed for the trajectory tracking of quadrotor unmanned aerial vehicle (QUAV) with model nonlinearities and external disturbances. Dividing the QUAV system into position subsystem and attitude subsystem, fuzzy logic systems are used to identify the nonlinearities. Then, an adaptive fuzzy control law is designed based on backstepping technique, and an adaptive event-triggered mechanism is constructed simultaneously, which determines the event-triggered instants. Thus, the adaptive fuzzy control law and the fuzzy parameter adaptive law are updated in an aperiodic form. Based on Lyapunov stability theory, it is proved that all signals in the closed-loop system are ultimately uniformly bounded via the impulsive dynamical system tool, and the tracking error converges to a small neighborhood of the origin. Besides, it is proved that there is a positive lower bound between the inter-sample time to avoid Zeno behaviour. Finally, simulation results illustrate that the proposed control scheme can guarantee the trajectory tracking control of the QUAV system, while it is able to the update frequency of the controller and improve the resource utilization.
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    Scenario Analysis of Urban Pension Fund Management
    JI Bingbing, CHEN Zhiping
    2023, 40 (5):  715-737.  doi: 10.3969/j.issn.1005-3085.2023.05.003
    Abstract ( 149 )   PDF (729KB) ( 115 )   Save
    The Chinese urban public pension system is facing significant challenges due to a declining workforce and a rapidly ageing population. In 2015, to enhance its long-term sustainability and reduce the interventions of the central government required to improve its funding condition, the government removed several operational constraints and allowed investment in Chinese financial markets. Based on an investment decision optimization model that combines multi-stage stochastic programming and dynamic stochastic control, this paper systematically explores the impact of macroeconomic and demographic factors on the pension system from the perspective of Chinese pension policy makers. The results show that: a reduction in interest rate can effectively hedge the negative impact of a reduction in contribution rate on the pension system; an increase in inflation rate and a decrease in GDP growth rate will have a negative impact on the pension system; a decrease/increase in the growth rate of active/passive population will have a direct negative impact on the pension system, and the pension system is more sensitive to passive than to active population growth rate. Finally, this paper provides policy recommendations based on the evidence collected.
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    Partially Observed Nonzero-sum Differential Game of Backward Systems with Random Jumps and Applications
    CHEN Xiaolan, WANG Kaikai, ZHU Qingfeng
    2023, 40 (5):  738-750.  doi: 10.3969/j.issn.1005-3085.2023.05.004
    Abstract ( 68 )   PDF (207KB) ( 92 )   Save
    Differential game is a theory that studies the decision-making process in which two or more players exert their control effects on a moving system described by differential equations to achieve their respective optimal goals. It has been widely concerned because of its interesting mathematical properties and application value in the economic field. A class of partially observed nonzero-sum differential games for backward stochastic systems with random jumps is considered, in which the game system involves the random jumps and each player possesses different observed equation. For this type of partially observed stochastic differential game problem, under the condition that the control domain is convex, the convex variation and duality techniques are used to establish the maximum principle of Nash equilibrium point. Under the appropriate convexity assumption, it is proved that the necessity optimal condition is also the sufficiency optimal condition, which is the verification theorem of Nash equilibrium point. Using the above maximum principle, a partially observed linear quadratic (LQ) game for backward stochastic systems with jumps is studied, and the unique optimal control of the LQ game problem is obtained, where the state equation and the adjoint equation constitute a class of forward backward stochastic differential equations with jumps. Since the LQ model is often used to describe many financial and economic phenomena, it is expected that the partially observed LQ game results for backward stochastic systems with jumps can be widely used in these fields.
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    Research on Multi-period Portfolio Decision Based on Stochastic Programming
    XUAN Haiyan, YAO Cunliu, LI Hongjian, AN Rong, ZHONG Jiayi
    2023, 40 (5):  751-762.  doi: 10.3969/j.issn.1005-3085.2023.05.005
    Abstract ( 98 )   PDF (249KB) ( 93 )   Save
    Optimal investment decision is an investor's rational allocation of risky assets in a complex and volatile environment from a long-term perspective in order to obtain the maximum desired utility. In this paper, the investment decision-making problem with uncertain rate of return in multi-stage investment is studied. Firstly, the ARMA-GARCH model is established to forecast the future rate of return of assets based on historical data of risky assets, Monte Carlo simulation method is used to simulate the possible future situation of yield, and random sampling is applied to build scenario trees. Secondly, based on the scenario tree, the mean-variance model proposed by Markowitz is extended to multiple periods according to stochastic programming theory. Finally, the data of six stocks in the Chinese securities market is selected to empirically investigate the model. The results of the study find that scenario tree is effective in describing the uncertainty problem. The model is suitable for multi-period investment and can provide radical, stable and conservative investors with intuitional and clear investment decision guidance.
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    Grey ${\rm GM}(2,1)$ Model with Complex Solution and Its Applications
    CHENG Maolin
    2023, 40 (5):  763-778.  doi: 10.3969/j.issn.1005-3085.2023.05.006
    Abstract ( 65 )   PDF (422KB) ( 179 )   Save
    ${\rm GM}(2,1)$ model is an important model in grey system prediction, but sometimes the solution of its whitening equation is complex, resulting in the predicted value of time series is complex, then we can use the distance between its mode and the actual value to reflect the size of its error. In order to improve the modeling accuracy, an extended grey ${\rm GM}(2,1)$ model is proposed in this paper, and the prediction method of complex time response equation and parameter estimation method are given. According to the model and method proposed in this paper, an extended grey ${\rm GM}(2,1)$ model is established for China's per capita GDP and China's private car ownership respectively, and compared with conventional methods and relevant literature methods. The results show that the improved method in this paper has the highest accuracy. The method presented in this paper is helpful to the generalization and application of grey ${\rm GM}(N,1)$ model.
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    A Cartesian Grid Method for the Elliptic Equations on Irregular Domains with Application to the Navier-Stokes Equations
    SHI Weidong, XU Jianjun, YUE Xiaoqiang
    2023, 40 (5):  779-792.  doi: 10.3969/j.issn.1005-3085.2023.05.007
    Abstract ( 84 )   PDF (1575KB) ( 168 )   Save
    A Cartesian grid method is presented for solving elliptic equation on irregular domains with Robin boundary condition in this paper. The elliptic equation is reformulated into an elliptic interface problem on a larger regular domain, then solved by using the level-set immersed interface method (IIM) recently developed. In particular, the Robin boundary condition is discretized using one-sided cubic interpolation. The method is applied to solving the Navier-Stokes equations on irregular domains. The Navier-Stokes solver couples the ghost fluid method for the velocity equations and the IIM for the auxiliary variable equation. Numerical tests show that second-order accuracy is achieved in both solution and gradient for the elliptic solver, and with fast convergence. The Navier-Stokes solver produces second-order accurate velocity and one-order accurate pressure. The robustness of the Navier-Stokes solver is demonstrated through simulations of flow around a circular cylinder.
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    LDG Method with High Order Time Stepping Scheme for a Time Tempered Fractional Diffusion Equation
    LI Minmin, LI Can, ZHAO Lijing
    2023, 40 (5):  793-806.  doi: 10.3969/j.issn.1005-3085.2023.05.008
    Abstract ( 66 )   PDF (207KB) ( 125 )   Save
    In the present paper, we develop a local discontinuous Galerkin (LDG) method  with a high order time stepping scheme for a time tempered fractional diffusion equation. Instead of solving the present model directly, we first transform it into a diffusion equation with Caputo fractional derivative. Then, the full-discrete LDG is constructed by using the L1-2 time stepping scheme to approach the Caputo fractional derivative, and using the discontinuous Galerkin to approximate the space derivative. We prove that the full-discrete discontinuous Galerkin method is unconditionally stable with the optimal convergence rate. We present two numerical examples to illustrate the accuracy and the robustness of the numerical method proposed in this paper. Our experimental results show that the high order accuracy of the present numerical scheme are obtained in both time and space variables.
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    The Global Attractor and Asymptotic Smoothing Effect of the Solution for 2D $g$-Navier-Stokes System with Nonlinear Dampness
    WANG Xiaoxia, JIANG Jinping, HOU Yanren
    2023, 40 (5):  807-821.  doi: 10.3969/j.issn.1005-3085.2023.05.009
    Abstract ( 75 )   PDF (201KB) ( 127 )   Save
    As one of the basic equations in fluid dynamics research, Navier-Stokes equation describes the dynamic balance of the force acting on any given region of liquid, reflecting the basic mechanical law of viscous fluid flow and has very important significance in fluid mechanics. As the generalization of the Navier-Stokes equation, the research on $g$-Navier-Stokes equation is flourishing in recent years. The dynamic properties of a class of autonomous $g$-Navier-Stokes systems with nonlinear dampness are studied. The global asymptotic compactness is proved by the prior estimation of solutions and the energy equation method on ${\bf R}^2$. The existence of global attractors about solvable semigroups is obtained, and the asymptotic smooth effect of solutions is analyzed. Some of the classical research results in recent years are further extended and improved, and the relevant research theories of $g$-Navier-Stokes equations are enriched.
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    The Variable Limit Integral Method for Helmholtz Equation
    WANG Yanan, WANG Guixia, HU Xuejia
    2023, 40 (5):  822-832.  doi: 10.3969/j.issn.1005-3085.2023.05.010
    Abstract ( 85 )   PDF (884KB) ( 226 )   Save
    Helmholtz equation is a class of elliptic partial differential equations that describe electromagnetic waves, and are widely used in mechanics, acoustics, electromagnetism, and other fields. In order to eliminate the pollution effect of high wavenumbers, the traditional method for numerically solving Helmholtz equation is to refine the grid, which not only increases the time complexity, but also usually makes the discrete matrix ill conditioned. Therefore, it is necessary to find an efficient numerical method for any wavenumbers. Based on the finite volume method, variable limit factors are introduced to completely convert the differential equations into integral equations. A discrete scheme containing a tridiagonal matrix is constructed using the univariable three-point and bivariable nine-point Lagrange interpolation formulas to perform numerical solutions of one-dimensional and two-dimensional Helmholtz equations using the variable limit integration method, respectively. The proposed method is suitable for arbitrary wave numbers, and the physical meaning of the solution process is clear. For the one-dimensional Helmholtz equation, the influence of the variable limit factor on the error is studied. The error estimation of the numerical solution is performed using Taylor expansion and Lagrange interpolation residual formula, and it is proved that the truncation error of the discrete scheme reaches second order. Numerical examples show that when the variable limit factor and step size of the discrete scheme are equal, the error order is lower. For the two-dimensional Helmholtz equation, the influence of different wave numbers on the numerical solution is investigated. It is proved that the truncation error of the discrete scheme reaches third order. Numerical examples indicate that the numerical scheme has good accuracy for different wave numbers, and high wavenumbers do not cause the pollution effect.
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    R-linear Convergence of Importance Sampling Stochastic Gradient Decent Algorithm
    WANG Fusheng, ZHEN Na, LI Xiaotong
    2023, 40 (5):  833-842.  doi: 10.3969/j.issn.1005-3085.2023.05.011
    Abstract ( 90 )   PDF (413KB) ( 102 )   Save
    In this paper, we propose a new stochastic variance reduction gradient algorithm for minimizing the sum of a finite number of smooth convex functions in machine learning. The characteristic of the new algorithm is to combine the gradient algorithm of stochastic variance reduction and a method of spectral gradient BB step size, so that the advantages of the two methods can be fully utilized. In addition, the new algorithm uses the important sample sampling method, which can greatly reduce the computation workload. In the end, it is proved that the new algorithm has R-linear convergence rate under the usual assumptions, and the complexity analysis is given. Numerical experiments show that the new algorithm is feasible and effective.
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    Variational-like Inequalities Involving Generalized Second-order Invexities
    GAO Liu, YU Guolin, WANG Meimei
    2023, 40 (5):  843-850.  doi: 10.3969/j.issn.1005-3085.2023.05.012
    Abstract ( 84 )   PDF (147KB) ( 99 )   Save
    The existences of solutions to the generalized second-order invex vector variational-like inequality are investigated, and their relationships with those of multi-objective optimization problems are disclosed. Two classes of generalized second-order invex functions and a type of second-order monotone functions are introduced, some specific examples are presented to illustrate their existences. The relationships with respect to the solutions between vector variational-like inequalities and multi-objective optimization problems are established by using analytical method. Based on KKM theorem, the existence results of vector variational-like inequalities are obtained under the assumptions of the introduced second-order monotonicity. It is shown that the solutions of vector variational-like inequalities are existed and it exists the closely relationships with multi-objective optimization problems under the appropriate conditions.
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