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Table of Content

    07 February 2023, Volume 42 Issue 12
    Distributed Iterative Learning Control for Multi-Agent Systems with Dead Zone Input
    YANG Nana, LI Suoping, ZHOU Yongqiang
    2022, 42(12):  3149-3162.  DOI: 10.12341/jssms21056
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    For a class of multi-agent systems with unknown dead-zone input, under the framework of iterative learning control, a time-varying gain with differential adaptive learning law is designed by using adaptive control; a differential parameter adaptive learning law is used to estimate the slope of the unknown dead zone input function, and an auxiliary control is constructed based on the hyperbolic tangent function to compensate for the remaining terms, which avoids the occurrence of chatter. By constructing an appropriate composite energy function, it is analyzed and proved that the followers can accurately track the leader on a finite time interval [0,T] , and all the signals of the closed-loop system are bounded.
    Filtering Algorithm with Bounded-Power Disturbance and White Gaussian Noise
    SUN Hongda, FENG Yu
    2022, 42(12):  3163-3172.  DOI: 10.12341/jssms22144
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    Traditional filtering algorithms, like Kalman filtering, are highly model dependent, and are able to achieve acceptable estimation performance under precise model. However, unknown environments and modeling mismatch always occur in real applications, which unavoidably leads to poor estimation performance. Therefore, a new linear time invariant robust optimal filter design method is proposed to solve the problem that discrete systems are affected by both bounded-power disturbance and white Gaussian noise. This method is capable of ensuring the robustness and the optimal mean square estimation, simultaneously. In order to ensure robust optimal filtering, this is based on system level synthesis method, and conducts the upper bound of estimation performance according to the system response of error dynamics and the parameters of disturbance and noise. On this basis, a computationally tractable algorithm is proposed for filter’s gain design. Finally, a velocity estimation example is used to verify the effectiveness of the current results, and it is shown that the current method outperforms some existing filtering algorithms, and achieves better estimate.
    L2-Well-Posedness and Regularity of 1-d Euler-Bernoulli Beams on a Three-Edge-Tree Shaped Network
    QI Qi, LIU Dongyi, XU Genqi
    2022, 42(12):  3173-3188.  DOI: 10.12341/jssms22211
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    The 1-d network system consisting of three Euler-Bernoulli beams is considered. By constructing appropriate multiplies we show that the open-loop network system is L2-well-posed. In light of an asymptotic estimation of the input-output transfer function of system, it is verified that the open-loop system is regular. In the end, we further discuss other boundary conditions.
    Optimal Control of Dual-Motor Servo System with Backlash Nonlinearity
    DANG Jiali, WANG Shubo
    2022, 42(12):  3189-3200.  DOI: 10.12341/jssms22220
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    This paper proposes an optimal control strategy based on backstepping method for the dual-motor servo system with backlash nonlinearity, realizing load tracking and motors synchronization. Firstly, the state equation is established after introducing an approximate dead zone function to describe the backlash model. Then, the optimal tracking controller is designed by combing backstepping control technology and second-order filter; the optimal synchronization controller is designed according to the position difference and velocity difference of the two motors; the control input of the two motors is obtained respectively combing the two controllers. Lyapunov theorem is used to prove the stability of the system. Lastly, it is proved that the proposed control method in the paper has better control effect on dual-motor servo system by comparing with the simulation results of PI control and dynamic surface control.
    Managing Multi-Mode Commuting Based on Transit Pricing Strategy in the Era of Autonomous Vehicles
    TANG Zheyi, TIAN Lijun
    2022, 42(12):  3201-3212.  DOI: 10.12341/jssms21504
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    Optimal management on the multi-mode traffic system is the classic problem in transportation field. Combining the background of the autonomous era, this paper formulates a multi-modal competitive transportation model consisting of the regular vehicles (RVs) and shared autonomous vehicles (SAVs) on a bottleneck-constrained highway and a separate transit line, then investigates the impact of diverse strategies of transit pricing (e.g., marginal cost pricing, average cost pricing, optimal total social cost pricing, and subsidized marginal cost pricing from road tolling) on the penetration rate for SAVs, the modal split pattern, and the total social costs. The results show that: the number of commuters for RVs is not affected, while the number of commuters for SAVs and transit is not unique with the change of different transit pricing; when some condition is satisfied, optimal total social cost pricing has the best effect in guiding commuters to choose the transit mode, alleviating road congestion, and reducing individual travel cost and total social cost; however, with the marginal cost further improved, the subsidized marginal cost pricing from road tolling will achieve the minimal total social cost. This paper provides reference for the government to formulate multi-objective and flexible traffic policies from different perspectives.
    Closed-Loop Supply Chain Recycling and Pricing Decisions Considering Cost Sharing Under Fairness Concerns
    CAO Xiaogang, QI Xiudi, WEN Hui, ZHANG Cuiwei
    2022, 42(12):  3213-3233.  DOI: 10.12341/jssms21560
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    This paper analyzes a closed-loop supply chain system consisting of a manufacturer engaged in production activities for new and remanufactured products and a retailer engaged in both sales and recovery activities. The impact of the retailer's fairness concern and the manufacturer's cost sharing on the supply chain system decisions is analyzed by applying the backward induction method and Stackelberg game. The results show that when the retailer is fair and neutral, the manufacturer's cost sharing is positively related to the retailer's recovery rate, and the manufacturer's cost sharing can increase the recovery rate and reduce the unit transfer price that the manufacturer pays to the retailer; when the manufacturer does not participate in the recovery cost sharing, the retailer's fairness concerns is positively related to the retailer's profit, negatively related to the recovery rate and the manufacturer's profit, and does not affect the total profit of the supply chain system; when the fairness concerns behavior and cost sharing behavior exist at the same time, the influence of cost sharing behavior on supply chain decision is much smaller than that of fairness concerns behavior on supply chain decision. Finally, the above conclusions are verified by example analysis.
    Research on the Theme and Evolution of Government Governance in Major Public Health Emergencies: A Textual Analysis Based on the Press Conference of Epidemic Prevention and Control
    WEI Zikai, TANG Xijin
    2022, 42(12):  3234-3252.  DOI: 10.12341/jssms21591
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    By analyzing the contents of the press conference on epidemic prevention and control, this study summarizes the various measures taken by the Chinese government along the entire process of epidemic prevention and control. It helps to describe how the government effectively responds in different stages of fighting against the COVID-19, so as to better understand the ideas and modes of public governance. This study proposes a policy text analysis framework by combining semantic information co-occurrence network and community discovery algorithm. This study discusses the characteristics of governance in public health emergencies, the evolution of governance themes, and the interacting logic among government functional departments. The results show that government governance topics cover a wide range and some key points are emphasized. Medical care, agriculture and transportation are the core directions of government governance; various functional departments cooperate closely, and under each governance theme corresponds to multiple departments to participate, showing a working situation of joint prevention and control; the governance theme shows strong continuity, and the focus of government governance has been adjusted accordingly in response to the different stages of the development of the epidemic. This study provides experience and reference for effective response to public health emergencies and policy formulation.
    A Multi-Server Priority Agent Service Queueing System with Balking, Reneging and Negative Customers
    CHEN Yanting, CHEN Jiaying
    2022, 42(12):  3253-3272.  DOI: 10.12341/jssms21694
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    Nowadays, chatting-based intelligent customer service has largely replaced the traditional call centers. However, due to the simple replies from the most intelligent customer service, customers tend to transfer to an agent for problem consultation. When conducting agent service consultation, quite often, there are many customers in the system together with network interruption. Based on this system, we study a multi-server priority queueing system with balking, reneging, and negative customers. Firstly, taking the agent service as an example, we develop a queueing model which includes the balking and reneging behaviors under the classic preemptive priority rule, and model the network interruption as negative customers. Secondly, we derive the steady-state distribution of two types of customers through the matrix analytical method and compute the corresponding performance measures. Furthermore, the numerical examples show that the comprehensive impacts of balking, reneging, and negative customers on the system performance are profound. Finally, we analyze the individual and system utilities, and provide suggestions for system optimal control.
    Investment Decision of Value-Added Services of Logistics Platform Under Incomplete User Information
    GUI Yunmiao, ZHAI Huihui, GONG Bengang
    2022, 42(12):  3273-3287.  DOI: 10.12341/jssms22110
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    In order to improve the competitive performance of the logistics platform, considering the impact of negative expectations on users' utility and platform profits in the state of incomplete information of users, a value-added service investment decision model of the logistics platform based on Hotelling is established, and the equilibrium solution of the platform value-added service investment decision under the master-slave game sequence and different user attribution structures is analyzed. The research shows that when the investment cost of value-added services is greater than a certain threshold and users have incomplete information, the investment volume of the follower platform in the market should be higher than that of the leader platform. When car owners settle on multiple platforms, the optimal investment of the leading logistics platform decreases with the increase of the user's network externality strength. However, the optimal investment amount of the follow-up logistics platform increases with the increase of the user's network externality strength. When the cargo owner settles on multiple platforms and the users on both sides have incomplete information, the leading platform and the follower logistics platform should reduce the amount of investment. When both the vehicle owner and the cargo owner are on multiple platforms and the cargo owner has incomplete information, the leading logistics platform and the follower logistics platform should increase the investment.
    Research on Coordinated Development of Xinjiang Energy-Food-Water Nexus Based on ISM-AHP Method
    GAO Jing, WANG Xiaolin, SUN Xuguang, XIA Yan, XU Jian
    2022, 42(12):  3288-3305.  DOI: 10.12341/jssms22127
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    The coupling relationship between energy, food and water is related to the social stability and sustainable development of a region. Xinjiang has always paid attention to the coordinated development level of energy, food and water. This paper established an evaluation index system for the coordinated development of the energyfood-water nexus. Based on the ISM-AHP method, it quantitatively evaluated the level of regional coordinated development and the degree of coupling between subsystems across Xinjiang, Northern Xinjiang, Southern Xinjiang, and Eastern Xinjiang from 2005 to 2019. The results show that: 1) The coordinated development levels of the energy-food-water nexus in various regions of Xinjiang are on the rise, but there are differences in the level and structure of development among regions. 2) The development of the energy industry and the efficiency of energy and water synergy are vital to the coordinated development of the region. The energy development gap in various regions in Xinjiang has grown bigger, and there is a huge difference in the efficiency of energy and water synergy. 3) The amount of hydropower generation, the efficiency of agricultural diesel use, the efficiency of fertilizer use, the total retail sales of consumer goods and the total import & export volume will significantly affect the coordinated development of Xinjiang’s energy-food-water nexus. On the whole, the energy-food-water nexus of Xinjiang Uygur Autonomous Region is showing a positive development trend. However, Southern Xinjiang is affected by energy development and the relationship between energy and water, which limits the development potential of resource endowments. Therefore, in addition to the overall consideration of the relationship between the resource endowments and industrial layout of various regions in Xinjiang at the strategic level, it is also necessary to focus on narrowing the development gap between Southern Xinjiang and other regions of Xinjiang. Southern Xinjiang should use the dividends of the development of low-carbon energy transformation such as hydropower and photovoltaics to drive the high-quality development of Xinjiang’s economy, which gives full play to the strategic role of Xinjiang’s key industries as a critical node in the Belt and Road Initiative.
    The Evolutionary Game Model of Petition Conflict Under the Influence of Social Learning Psychology and Government-Enterprise Collaboration
    LI Xuehong, ZHANG Xueyun, ZHOU Jiaqi, ZHANG Guoxing
    2022, 42(12):  3306-3320.  DOI: 10.12341/jssms22128
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    Complaint reporting is a social governance system innovation with Chinese characteristics, and rapid economic and social development has put forward new requirements and challenges to the petition system. The current research around the petition system and petition conflict is dominated by theoretical analysis and case studies, and few research focuses on the micro-action mechanism of petition conflict. In this paper, we analyze the evolutionary process of behavioral strategies of different subjects from two perspectives:the social learning psychology of petitioner groups and the collaboration between government departments and enterprises, and discuss and reveal the internal influence mechanism of petition conflicts. The results show that:The social learning psychology within the petitioners' group has an important influence on their behavior, and the learning efficiency comes from the trade-off and comparison of the costs and benefits of petitions, which in turn affects the dynamic game process between enterprises and petitioners; the petitioners expect to draw the attention of the government and the public through their irrational petition behavior, reveal the irregularities of enterprises and obtain corresponding compensation benefits; the involvement of government departments in the petition conflict issue can guide the behavior of enterprises and petitioners to a benign interaction of "enterprises operating in compliance and petitioners petitioning rationally". At the same time, the problem of petition conflict also reflects the inadequacy of the internal petition system. Therefore, exploring a multi-body petition conflict management mechanism with government participation is an important measure to alleviate petition conflicts and improve the effectiveness of petition management.
    Forecasting of Port Container Throughput Based on TEI@I Methodology
    JIA Peng, LU Shenglan, WU Tong, WANG Shouyang
    2022, 42(12):  3321-3338.  DOI: 10.12341/jssms22216
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    Based on the TEI@I (Text mining+Econometrics+Intelligent algorithms @ Integration) methodology, this paper proposes a port container throughput forecasting framework that can adapt to external contingencies. Firstly, the original sequence of port container throughput is decomposed by CEEMD (Complementary Ensemble Empirical Modal Decomposition) to obtain subseries of different time scales, and each subseries is analyzed for complexity, smoothness and correlation (with the original sequence), on which the new subseries are classified and reconstructed; then adapted forecasting models are constructed and selected according to the different characteristics of each subseries; For the part of huge shocks caused by external contingencies, an improved standard event analysis method is introduced to quantify the impact direction, impact degree and impact duration of irregular large events; finally, the prediction results of each part are integrated and combined with the "expert system" to optimize the final prediction results. The empirical studies of Shanghai and Qingdao ports show that the method is able to guarantee its prediction accuracy, prediction direction and model stability in the presence of major irregularities, and the results are better than other benchmark models.
    Analysis of Green Building Supply Under Compound Environmental Regulation by Evolutionary Game
    CAI Binqing, HUANG Yujing, HUANG Xinhuan
    2022, 42(12):  3339-3354.  DOI: 10.12341/jssms22225
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    In order to design reasonable environmental regulation policies to promote the supply and long-term development of green buildings, the evolutionary game model between the government and the building supplier and the numerical simulation are applied to compare the impacts of the compound environmental regulation policy on green building supply. The compound environmental regulation policy is consisted of static carbon tax, dynamic carbon tax, static carbon emission permits trading and dynamic carbon emission permits trading. We get the following conclusions: when the government implements the compound policy of static carbon tax and static carbon emission permits trading, the game system fluctuates periodically, and there is no evolutional stable strategy. When the compound policy of dynamic carbon tax and static carbon emission permits trading, or static carbon tax and dynamic carbon emission permits trading, or dynamic carbon tax and dynamic carbon emission permits trading are implemented, there are evolution stable strategies in the game system. The compound policy of static carbon tax and dynamic carbon emission permits trading is best among all compound policies for promoting the supply of green buildings. Under the best compound policy, the probability of supplying green buildings is positively correlated with the upper limit of carbon tax and carbon trading price, and negatively correlated with the cost of government supervision.
    Feeder Bus Schedule Optimization Considering Passenger Queuing Behavior
    DOU Xueping, DONG Ran, LI Tongfei, GONG Xiaolin
    2022, 42(12):  3355-3367.  DOI: 10.12341/jssms22368
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    Residents usually experience transfers when they take public transit services in long-distance commuting trips. During peak hours, passengers may have to wait in a queue for multiple bus trips, resulting in a sharp increase in their transfer costs. Given train schedules and transfer demand, joint optimization of feeder bus timetable and fleet size has been investigated, with consideration of passenger queuing behavior. According to an elaborate questionnaire survey, the trigger conditions and occurrence probability of passengers joining and leaving a waiting queue are determined. A feeder bus schedule optimization model is formulated to minimize the sum of passengers’ travel cost and bus operator’s cost. In the model, the fleet size is explicitly calculated and constrained for each feasible bus timetable based on the deficit function. A genetic algorithm incorporating an enumeration process is developed to solve the model, and numerical experiments are conducted under different scenarios. The results indicate that the optimized feeder bus schedule can greatly reduce passenger travel cost without observably increasing bus operation cost, but the different queuing behavior of heterogeneous passengers has a significant impact on bus schedule optimization solutions. This research can provide theoretical guidance and decision support for the coordinated operation of an integrated public transit system.
    Fisher Information in Different Types of Ranked Set Sampling from Skew-Normal Distribution
    ZHANG Jianfen, CHEN Wangxue, WANG Shuo, ZHOU Yawen
    2022, 42(12):  3368-3379.  DOI: 10.12341/jssms21174
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    Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this article, Fisher information in the corresponding samples about the skewness parameter from skewnormal distribution under simple random sampling, ranked set sampling (RSS), extreme RSS (ERSS) and median RSS (MRSS) will be respectively studied. The numerical results show that different types of perfect ranked set sample carry more information than a simple random sample of equivalent size. The numerical results also show all information will decrease as rank error.
    Marginalization of the Markov Property for Bayesian Networks
    SUN Tingran, SUN Yi
    2022, 42(12):  3380-3396.  DOI: 10.12341/jssms21327
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    As a product of the combination of probability theory and graph theory, Bayesian networks have irreplaceable applications in modeling uncertain complex systems and reducing the computational complexity of probabilistic inference. When we perform probabilistic inference and data analysis on large-scale Bayesian networks, we often need to care about only a small set of variables, which requires one to consider the structural information of the marginal model. Considering that the marginalization operation of Bayesian networks is not closed, we focus on the problem of finding minimal I-maps for marginal models of Bayesian networks. Based on the variable elimination method in undirected graphical models and the definition of t-removable vertices in directed graphical models, we propose the method of variable elimination theory of directed acyclic graphs and prove that the graph obtained after variable elimination is exactly a minimal I-map for a maginal model of a Bayesian network when marginalizing over variable set.
    Quantile Penalized Integrative Method and Its Application in the Systemic Risk of Commercial Banks
    CAI Chao, DONG Haotian, LI Li
    2022, 42(12):  3397-3411.  DOI: 10.12341/jssms22237
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    Big data usually combines data from different sources, and has high dimensional characteristic. It is a problem that how to mining the heterogeneity and correlations of different datasets and achieves dimension reduction. Hence, this paper proposes quantile penalized integrative method. A set of modeling methodology, includes mathematics expression, parameter estimation, is studied in detail. It can not only simultaneously build up models and select variables using data from different sources, but also considering the heterogeneity and correlations of data from different sources. The numerical simulation results show that the quantile penalized integrative method has a significant advantage in both model prediction and variable selection. Finally, the quantile penalized integrative method is applied to the measurement of the systemic risk of commercial Banks. The results show that the quantile penalized integrative method has a good performance in practical application.
    Bayesian Ψq-Optimal Designs for Multi-Factor Nonlinear Models Based on the Second-Order Least Squares Estimator
    LENG Wei, YIN Juliang
    2022, 42(12):  3412-3424.  DOI: 10.12341/jssms22313
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    As the error in a regression model obeys an asymmetric distribution, it has been shown that the second-order least squares estimator is more efficient than the ordinary least squares estimator. This paper considers Bayesian Ψq-optimal designs for multi-factor nonlinear models under the second-order least squares estimation. For such a multi-factor nonlinear model with a constant term, its Bayesian Ψq-optimal design via the second-order least squares estimator is the same as that derived from the ordinary least squares estimator. For the multi-factor nonlinear model without a constant term, if orthogonal assumptions are satisfied for Bayesian Ψq-optimal designs on marginal models, then Bayesian Ψq-optimal design for multi-factor nonlinear model can be obtained from the product design of Bayesian Ψq-optimal designs on marginal models. Several examples are presented to illustrate the effectiveness of theoretical results.
    Sparse Exploratory Factor Analysis Based on Prenet Penalty
    XUE Jiao, FU Deyin, HUANG Hengjun, HAN Haibo
    2022, 42(12):  3425-3448.  DOI: 10.12341/jssms21629
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    As an important statistical dimensionality reduction technique, factor analysis aims to reveal the quantitative relationship between explicit variables and latent variables by exploring the covariance structure among variables. The sparse estimation of factor loading matrix is an important part of determining the effect and interpretation of factor analysis, and there are two strategies: The two-step method based on rotation and the one-step method based on penalty. In order to obtain an easy-to-interpret sparse structure, this paper proposes a sparse factor model based on prenet penalty. Specifically, factor loading Λ is decomposed into the product of an orthogonal matrix Q and a diagonal matrix D. A prenet penalty is imposed on Q, an estimation method for solving the sparse factor loading matrix is proposed, and a solving algorithm for generalized expectation maximization is given. The simulation experiment results show that compared with the existing estimation method, the estimation results of the method based on the prenet penalty is relatively stable, and it is easy to obtain sparse factor loadings. The example data analysis shows that the method has obvious advantages in the sparse processing of factor analysis.