中国科学院数学与系统科学研究院期刊网

25 March 2024, Volume 44 Issue 3
    

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  • HUANG Yanwei, YAN Jinghui
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 595-609. https://doi.org/10.12341/jssms22580
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    The hydrodynamic characteristics of USV are highly nonlinear and time-varying. In order to facilitate the control of the yaw, a nonlinear parameter-varying (NPV) model based on the surge velocity is proposed. Firstly, a nonlinear mechanism model with three degrees of freedom is established by introducing Ross damping model from the hydrodynamic mechanism. Secondly, on the basis of the mechanism model, the nonlinear term is implied in the linear structure to make the model form a linear structure. Then, the sway damping term with small value is ignored, and the surge velocity is taken as the variable parameter to establish the NPV model based on the surge velocity. The NPV model has a simple structure with nonlinear and variable parameter terms, which is an extended form of the Norrbin nonlinear model and linear parameter-varying (LPV) model. Finally, simulations and experiments show that the NPV model can well describe the nonlinear and time-varying characteristics of the yaw motion of the USV.
  • HE Defeng, HUANG Yuanchi, MU Jianbin
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 610-621. https://doi.org/10.12341/jssms22606
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    In this paper, an event-triggered interpolation model predictive control method is proposed for constrained linear parameter varying (LPV) systems with uncertain bounded disturbances. By the interpolation method, optimization problem solution will show the current moment system default parameterized form of feedback control law, to reduce the number of optimization problem solving variables and reduce the burden of the system. Superimposing the multiplicative perturbations of system scheduling parameters and the additive perturbations of each time point, a finite step compact constraint set is constructed to realize the robust constraints. And the deviation of the nominal system and the actual system that exceeds the tight constraint set is used as the trigger condition. Trigger thresholds associated with interpolation coefficients and robust constraint sets are calculated online. We show that the proposed algorithm is recursively feasible and the closed-loop system is input-to-state stable in the attraction region. Finally, an example is given to verify the proposed method.
  • WANG Rui, YU Fusheng, ZHAO Liyun
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 622-633. https://doi.org/10.12341/jssms23320
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    This paper presents an adaptive direct novel alleviating adjusted parameters fuzzy tracking control algorithm for a class of uncertain saturation switched nonlinear systems under arbitrary switchings in non-strict feedback form. Combined with common Lyapunov function (CLF) method, an auxiliary constructed system is introduced to compensate the input saturation problem. FLSs are designed to model the uncertain nonlinear functions of non-strict feedback systems, by estimating the boundness of the optimal approximation vector and approximation error of the FLSs, the adjusted parameters would be greatly alleviated. Based on Lyapunov theories analysis, it is shown that with the proposed scheme, all the signals in the closed-loop systems are uniformly ultimately bounded, and the system output converges to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.
  • WANG Liu, HU Aihua, JIANG Zhengxian
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 634-647. https://doi.org/10.12341/jssms23291
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    This paper studies the mean-square bounded cluster consensus for nonlinear multi-agent networks under deception attacks. Firstly, all network nodes are divided into different clusters. Considering that the control signal may be replaced by an error signal after being subjected to deception attacks, a Bernoulli random variable is introduced to represent the success of the deception attack. Secondly, a distributed impulsive controller employing pinning strategy is designed to ensure mean-square bounded cluster consensus in the presence of deception attacks. Furthermore, using the graph theory, linear matrix inequality and Lyapunov function method, sufficient conditions for realizing the mean-square bounded cluster consensus of multi-agent networks under deception attacks are given. Finally, a simulation example is supplied to verify the feasibility and effectiveness of the theoretical results.
  • FANG Cheng, WU Peng, HE Zerong
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 648-664. https://doi.org/10.12341/jssms23624
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    In this paper, a reaction-diffusion Syphilis model with a fixed latent period and spatial heterogeneity is formulated to study the transmission dynamics of syphilis among population. Firstly, the authors discuss the global existence and attractor of the solution for the system. Secondly, based on the definition the next generation operator for the disease compartment model, as the threshold of the dynamics, the basic reproduction number $R_0$ is derived. Specifically, the authors show that the disease-free steady state is globally attractive when $R_0<1$ and the uniform persistence of the disease is proved by the persistence theory for dissipative system. Finally, in space homogeneous case, the explicit expression of the basic reproduction number $\tilde{R}_0$ is derived. Moreover, the authors prove the global stability of the disease-free and the endemic equilibria by Fluctuation lemma.
  • HE Zhilong, WU Yanxia
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 665-680. https://doi.org/10.12341/jssms23279
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    Under the constraint of actuator saturation, this paper considers the stability and synchronization of a class of financial systems under impulsive control. First, by introducing a dead zone nonlinear function to represent the saturation nonlinearity of the system at the impulsive time, the local exponential stability condition of the financial chaotic system under the saturated impulsive control is obtained. Secondly, by establishing a saturated impulsive controller, a sufficient condition for the chaotic synchronization of the driving response financial system is obtained. Finally, a numerical example is exploited to verify the efficiency of the obtained theoretical results.
  • MA Mengfan, GUO Shenghui
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 681-693. https://doi.org/10.12341/jssms22097
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    In this paper, a design method of a reduced-order observer for the cyber-physical system with unknown input signals and its application in sensor attack detection are investigated. Firstly, the Kronecker product is used to describe the original cyber-physical system as a dynamic model of the whole system. Then, a reduced-order observer with unknown input for cyber-physical system is presented, and the influence of unknown input on the system can be eliminated by increasing the constraint condition of the reduced-order observer gain matrix, and then judging whether there is a sensor attack signal through system output status. Finally, the capability of the proposed reduced-order observer to estimate the state of the system and detect the attack signal of the sensor is verified by numerical simulation. Also, the simulation results show that the performance of the proposed reduced-order observer is better than that of the full-order observer.
  • WANG Fang, YIN Xuewei, SHI Chunlai, YU Lean
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 694-710. https://doi.org/10.12341/jssms23150
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    To solve the dilemma of information-sensitive e-waste recycling under incomplete information, this paper constructed an evolutionary game model composed of government, consumers and recyclers based on prospect theory, and discussed the main factors affecting system game strategy. The results show that the government's increased supervision can promote the standardization of the recycling market. The negative credit evaluation of consumers is conductive to the informal recyclers. The high negative credit evaluation encourages the normalization of the informal recyclers, while the low negative credit evaluation promotes the informal recycling treatment of the recyclers. In the recycling process, if consumers suffer information leakage losses, they tend to distrust strategies, and the greater the information leakage loss, the deeper the degree of distrust. In addition, the loss factors in prospect theory have an impact on the strategies of consumers and recyclers, while the return factors have almost no effect, indicating policymakers pay more attention to loss aversion in the game.
  • CHEN Congli, YANG Hui, WANG Guoling, TANG Wei
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 711-722. https://doi.org/10.12341/jssms23003
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    In this paper, we study the existence and generic stability of equilibria for multiobjective games with uncertain parameters. We first use the vector valued Ky Fan inequality to prove the existence of weakly Pareto-NS equilibria for the games. Secondly, it is proven that the weakly Pareto-NS equilibria of most multiobjective games are essential under uncertain parameters by Fort theorem. Finally, these conclusions are verified by a specific example.
  • LIU Hualing, CHEN Ning, REN Qingqing, QIAN Kejia
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 723-740. https://doi.org/10.12341/jssms23111
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    The advent of the Internet era has accelerated the frequency of news updating and expanded the scope of news dissemination. It is difficult to mine and analyze the potential risk of news content only relying on manual work. Therefore, it is of great significance to build a model to predict the future popularity of news for a period of time to quickly control bad information and strengthen Internet information governance. In order to better predict the news popularity, this paper focuses on mining the relationship between news, and proposes a news popularity prediction method (that integrates the news jump relationship and user preference under the premise of moderately integrating user preference information). This method first combines the news content and the historical jump probability to generate the news jump relationship network, and uses the multi-task graph convolution matrix completion model MGCMC (multitask graph convolution matrix completion) proposed in this paper to predict the sparsely distributed and unbalanced jump probability matrix, so as to obtain the characteristics of the future news jump relationship network. When the news platform recommends a group of news in the state of dissemination to users, this method combines users' personalized preferences to predict their click behavior, and finally gains news popularity. The experimental results based on the real user-news interaction dataset Mind show that MGCMC performs better than the existing matrix completion and unbalanced prediction models, and the accuracy of user-news click prediction is higher, and the discovery of popular news is more accurate.
  • WANG Daiwen, WEI Cuiping
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 741-754. https://doi.org/10.12341/jssms22812
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    Decision-making trial and evaluation laboratory(DEMATEL) methods are used to analyze the relationship between interacting factors and identify key factors. In view of the incomplete judgment and the element of linguistic distribution assessment elements in the direct influence relation matrix, this paper proposes the improved DEMATEL method to deal with linguistic distribution assessments and linguistic term sets with different semantics. Firstly, this paper defines the similarity formula of linguistic distribution assessment under the numerical scale, and uses the weighted average operator of linguistic distribution assessment (DTWA) to complete the incomplete elements. Secondly, this paper uses the numerical scale of the linguistic term set to numeralize the expert's linguistic distribution assessments. The DEMATEL process is carried out by synthesizing the numerical decision information of all experts to obtain the weight of each factor and the influence relationship between the factors. The factors are divided into two groups: The cause group and the effect group. Finally, the proposed method is applied to a practical case of sustainable cycle partner selection.
  • HE Junyong, ZHANG Guosheng, QI Sijun
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 755-779. https://doi.org/10.12341/jssms22857
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    Market liquidity and stock pricing information efficiency reflect the quality of a security market. Based on the background the tier Select of NEEQ(National Equities Exchange and Quotations) launched on July 27, 2020, this paper adopts the staggered difference-in-difference to study the effects on the stock liquidity and pricing information efficiency. It is found that, stock liquidity and pricing information efficiency of firms listed on the tier Select are significantly improved. The establishment of the tier Select, the improvement of information disclosure mechanism, and a series of reforms have significantly promoted the stock pricing information efficiency through channels such as increasing market transactions and reducing information asymmetry. The further study demonstrates that the stock pricing information efficiencies of firms with lower information asymmetry and higher market capitalization have been significantly improved. While, for those firms with high degree of information asymmetry or lower market capitalization, their stock pricing efficiencies nearly have remained invariant. Stock price reflects more of the characteristics of market and industry, but absorbs less of its idiosyncratic information. There exhibits co-movement, and stock price synchronizes to rise and fall. Considering most of listed firms in the tier Select are small and medium-sized high-tech enterprises, and the market makers are professional market-making institutions, they have the ability to price the stocks of high-tech enterprises. Therefore, based on the continuous auction mechanism on the tier Select, implementing a hybrid market-making mechanism can further improve market liquidity and stock pricing information efficiency.
  • YUAN Ruiping, ZOU Shunjie, PAN Luke, LI Juntao, MA Xifeng
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 780-791. https://doi.org/10.12341/jssms23629
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    In order to improve the picking efficiency of robotic mobile fulfillment system (RMFS) and better meet the dynamic needs of customers and order deadlines, a dynamic shelf storage allocation strategy is proposed considering the frequency and urgency of future demand, as well as the system congestion factors. A dynamic storage allocation model is constructed to minimize the total distance of shelf transportation, and a heuristic algorithm is designed to solve the model. Firstly, considering the urgency of shelf demand, a greedy algorithm is designed to generate the initial solution; Then, based on the frequency of demand for shelves in subsequent batches of orders and the load capacity balance among aisles, dynamic shelf storage optimization is carried out using neighborhood search algorithm. Finally, the effectiveness of the proposed model and algorithm is verified by comparison with other static and dynamic storage allocation methods.
  • SUN Jingyun, MA Xiaowen
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 792-808. https://doi.org/10.12341/jssms23647
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    Taking the main components of the SSE 50 Index as the research object, this paper first constructs a comprehensive evaluation index of stock risk based on fractal and S-utility theory, which is the basis of selecting stocks for portfolio construction. Then, under the assumption that the return on financial assets obeys asymmetric Laplacian distribution, the CVaR value is adopted to measure the risk of portfolio, and then an M-CVaR optimal asset allocation model is constructed, which is transformed into a quadratic programming problem to solve. In the empirical analysis stage, the sliding window method is used to dynamically adjust the optimal allocation ratio of the best stock set with monthly, quarterly, semi-annual and one-year cycles respectively. The results show that some stock investment sets screened by fractal and S-type expected utility theory can obtain better investment returns than all stocks participating in the portfolio, and the asset allocation scheme with one-year adjustment cycle can obtain higher cumulative return and Sharpe ratio than other adjustment cycles.
  • WANG Luyao, ZHANG Xinyu, KUANG Xiong, ZHOU Jianhong
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 809-823. https://doi.org/10.12341/jssms23180
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    The optimization of revenue management is one of the effective ways to improve retailers' economic returns. Pricing is the engine and core technology of revenue management, which plays an important role in improving retailers' revenue. Considering the complexity of forecasting and optimization problems in the practical application of revenue management, the steps of forecasting product demand first and then optimizing revenue are usually adopted. When forecasting product demand, there are usually multiple candidate models, that is, facing the uncertainty of the model. At this time, the final model is generally determined by model selection. However, traditional model selection criteria, including Akaike information criterion(AIC) and Bayesian information criterion(BIC), usually only consider the impact of model selection on prediction accuracy, without considering how the prediction model will affect the next optimization decision objectives. This paper first proposes the focused information criterion(FIC) model selection criterion in the optimization of commodity income management, uses the FIC model selection criterion to select the product demand forecasting model, considers the structure of the optimization model, and selects the prediction model with the goal of minimizing the decision-making error rather than prediction error. The numerical simulation results show that, in most cases, compared with AIC and BIC model selection criteria, FIC model selection criteria considering decision objectives performs best. Meanwhile, the empirical research results also verify the superiority of the FIC model selection criteria considering decision objectives.
  • QIU Yue, XIE Tian
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 824-843. https://doi.org/10.12341/jssms23304
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    This paper presents a comprehensive comparison of various models for predicting cryptocurrency volatility. The findings highlight that the rough volatility model demonstrates robust and reliable performance in forecasting out-of-sample volatility across multiple periods. Conversely, the heterogeneous autoregressive(HAR) model shows relatively weaker results. However, the log-transformed HAR model exhibits superior predictive capabilities. Additionally, the study emphasizes the significance of selecting appropriate time zone divisions, considering the impact of different time zones on cryptocurrency market volatility. To address model uncertainty in volatility modeling, the paper introduces the method of model averaging using least squares. The results indicate that model averaging outperforms alternative approaches by effectively balancing the strengths and weaknesses of different models, ultimately enhancing the credibility and stability of predictions in the cryptocurrency market. The study underscores the importance of considering the unique characteristics and historical performance of cryptocurrency volatility when selecting suitable volatility models. Furthermore, it emphasizes the need for careful evaluation of model performance across diverse datasets and prediction targets to mitigate uncertainty arising from blind application.
  • KANG Ning, MO Luyao, JING Ke
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 844-861. https://doi.org/10.12341/jssms22446
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    Smooth transition autoregressive model (STAR) often sets the transition function as logistic function or exponential function, and obtains the estimation, test and forecasting results by mean regression. We propose a new semi-parametric smooth transition quantile autoregressive model. Its main advantages are as follows: First, the smooth transition function is constructed by the barycentric rational interpolation function, which has more flexible form and can better reduce the risk of mispecification. Second, in the framework of quantile regression, the genetic algorithm is applied to obtain the coefficient estimation of new model, which is more informative than the mean regression. Numerical simulation results show that the autoregressive coefficient estimators have good performance in unbiasedness, effectiveness and consistency. Finally, the new model is applied to reveal and forecast the dynamic trend of stock returns of the Shanghai Composite Index, and the empirical results indicate that there exist nonlinear and heterogeneous characteristics of the return series.
  • ZHONG Wen, LIU Liu
    Journal of System Science and Mathematical Science Chinese Series. 2024, 44(3): 862-878. https://doi.org/10.12341/jssms22875
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    With the gradual improvement of sensor technology and data acquisition system, a large number of complex high-dimensional data can be collected. Monitoring multi-variable and high-dimensional data streams are often a basic requirement of modern manufacturing and quality management departments. However, in the field of high dimensional data monitoring, most of the traditional multivariate control charts are no longer applicable due to the “curse of dimension” and the complicated and unknown distribution of variables. In response to this situation, some researchers have discussed various tests for the mean vector of complex high-dimensional data with unknown distribution. But these tests are rarely applicable to Phase II process monitoring. In this paper, we propose an EWMA-type nonparametric monitoring scheme based on high-dimensional empirical likelihood ratio test, which can be used to monitor the mean vector of multi-dimensional and highdimensional processes, and is suitable for subgroup data streams. The proposed control chart is not only easy to implement and interpret, but also the Monte Carlo numerical simulation results show that the proposed control chart can effectively detect the mean shift in symmetric, skewed and heavy-tailed distributions. Finally, the proposed control chart is applied to the semiconductor manufacturing process, and the results show that the proposed method has a good monitoring effect on the semiconductor that has not passed the test.