中国科学院数学与系统科学研究院期刊网

25 November 2024, Volume 44 Issue 11
    

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  • YIN Zhichao, GUO Rundong
    Systems Engineering - Theory & Practice. 2024, 44(11): 3467-3480. https://doi.org/10.12011/SETP2023-1076
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    Insufficient aggregate demand is the prominent contradiction facing the current economic operation, we must restore and expand consumption in a priority position. This paper empirically investigates the impact of the housing provident fund system on household consumption using data from three editions of the China Household Finance Survey in 2015, 2017, and 2019. The empirical results show that household contributions and withdrawals to the housing provident fund significantly increase household consumption levels and improve household consumption structure. Robustness tests show that the above conclusions remain robust after replacing the way the core variables are defined, replacing the instrumental variables, and relaxing the exclusivity constraints on the instrumental variables. The Heterogeneity analysis shows that the housing provident fund system has a greater impact on the consumption of housed, low-income, as well as young and middle-aged households. Further research finds that contributing to the housing fund reduces households' precautionary saving incentives, withdrawing from the housing fund increases households' disposable income and eases liquidity constraints, thereby boosting household consumption. This paper provides micro-level evidence that housing funds promote household consumption and improve household consumption structure, which can provide important references for relevant policy formulation.
  • ZHANG Kequn, JIANG Yukun
    Systems Engineering - Theory & Practice. 2024, 44(11): 3481-3500. https://doi.org/10.12011/SETP2023-0824
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    Promoting enterprises to accelerate digital transformation is of great significance to enhance the core competitiveness of enterprises, empower the upgrading of traditional industries, generate new forms of business, as well as drive China's digital economy to become better and stronger. From the perspective of enterprises, this paper analyzes the antecedents of enterprises' digital transformation, constructs related indexes based on the text analysis method, proposes a two-factor theoretical model of manager characteristics and dynamic capabilities, and uses the structural equation model based on partial least squares estimation (PLS-SEM). The empirical results show that manager characteristics such as entrepreneurship, digital evangelist and coordinator, as well as corporate dynamic capabilities such as sensing, learning, integrating and coordinating, have a significantly positive role in promoting the tendency and output of digital transformation of enterprises. In addition, manager characteristics can significantly improve the level of enterprises' dynamic capabilities, and the effect of manager characteristics on enterprises' dynamic capabilities and digital transformation is moderated by managers' perception of policy uncertainty. In addition, the above effects are heterogeneous between state-owned and private enterprises, enterprises in the eastern, central and western regions, as well as enterprises in provincial and non-provincial capitals. This paper fills the research gap on the antecedents of digital transformation, and provide a feasible practical path for enterprises to cultivate managers in the digital era and improve their dynamic capabilities.
  • LI Hongzhou, HE Lifei, LI Shu
    Systems Engineering - Theory & Practice. 2024, 44(11): 3501-3519. https://doi.org/10.12011/SETP2023-1726
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    The “Triple Reform” policy is a significant initiative aimed at addressing the challenges of renewable energy consumption and promoting the high-quality development of new energy in the context of increasing renewable energy penetration. This study focuses on Shandong Province, which has a strong reliance on traditional coal-fired power, and employs a static Computable General Equilibrium (CGE) model to link renewable energy with the “Triple Reform” policy. The study simulates the impact on the economic and environmental aspects of Shandong Province under different shares of renewable energy electricity consumption, coupled with the simultaneous implementation of the “Triple Reform” policy. The research investigates the underlying reasons for the slow progress in the implementation of the “Triple Reform” policy for coal-fired power units and, based on this, transforms the compensation issue into a cost problem. Cost estimation for the implementation of the “Triple Reform” policy in Shandong Province is carried out. The results indicate that the implementation of the “Triple Reform” plan will have certain negative impacts on the regional economy but can also bring significant environmental benefits. In the scenario with 60% coal-fired power and 40% renewable energy electricity (F60C40), the cost of implementing the “Triple Reform” policy in Shandong Province is estimated to be 4 billion yuan. The policy recommendations of this study emphasize the need for vigorous development of renewable energy in China, urging coal-fired power units to actively implement the “Triple Reform” policy. It also suggests timely introduction of reasonable policy support or economic incentives to leverage the stabilizing role of coal-fired power.
  • ZHAI Pengxiang, LEI Lei, FAN Ying, GUO Kun, ZHANG Dayong, JI Qiang
    Systems Engineering - Theory & Practice. 2024, 44(11): 3520-3536. https://doi.org/10.12011/SETP2023-1910
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    Identifying and addressing various financial risks on the way toward low-carbon transition is crucial for China to achieve its dual carbon goal. By performing textual analysis of newspaper articles, this paper constructs a novel index of climate policy uncertainty for China to examine the impact of the climate policy shock on the corporate bond cost as well as the mechanism behind the relationship. From a climate policy-cash flow sensitive perspective, this paper develops a theoretical model of financing decision-making under climate policy uncertainty and empirically verifies the hypothesis with a dataset of Chinese-listed companies from 2009--2020. The results show that bond spreads of climate policy-sensitive firms are significantly higher than that of climate policy-insensitive firms, which indicates that climate policy uncertainty significantly deteriorates corporate bond costs in China. Moreover, this effect increases with the maturity of the corporate bond and the level of climate policy uncertainty and is more profound in firms with a negative sensitivity to changes in climate policies. The results also prove that internal environmental governance and external regulatory enforcement intensity are two key channels by which the climate policy shock can impact the cost of corporate bonds in China. This paper contributes to the research of climate finance by providing a theoretical framework and empirical evidence on the relationship between climate policy shock and corporate bond cost and thus is crucial for policymakers to understand micro-level financing and investment risk in China under the dual carbon goal.
  • ZHOU Zhongqiang, ZHOU Daqing, XIONG Xiong
    Systems Engineering - Theory & Practice. 2024, 44(11): 3537-3549. https://doi.org/10.12011/SETP2023-1982
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    Since the 2015 stock market crash, the trading activities of the “National Team” funds have drawn significant attention from investors. This paper uses A-share listed company stock trading data from the third quarter of 2015 to the fourth quarter of 2021 to examine the impact of “National Team” fund holdings on institutional investor herding behavior. Employing a fixed effects model for regression analysis, the findings indicate that “National Team” fund holdings exacerbate institutional investor herding behavior. Further analysis reveals a negative correlation between institutional herd behavior and stock price synchronicity, suggesting that this behavior is not merely blind following of “National Team” fund holdings but rather a pseudo-herd behavior influenced by shared market and private information. This effect is consistent across bull, bear, and volatile market conditions, though it is somewhat reduced during bear markets. The conclusions of this study enhance the understanding of the intervention effects of the “National Team” funds and provide valuable insights for their effective management.
  • YIN Haiyuan, YANG Qingsong
    Systems Engineering - Theory & Practice. 2024, 44(11): 3550-3570. https://doi.org/10.12011/SETP2023-1258
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    This paper builds a parallel CNN-LSTM deep learning model, excavates the interactive text between investors and the management of listed companies on the interaction platform of Shanghai and Shenzhen Stock Exchanges, quantifies the information interaction process between investors and the management from the text content and semantic characteristics, and analyzes its impact on the company's stock price foam by identifying the content of investors' inquiries and the quality of company responses. The study found that investors' questioning and attention to different contents had significantly different effects on the stock price foam. Among them, questioning and attention to the company's stock and financial information could inhibit the frequency and intensity of the stock price foam, while questioning and attention to the company's research, development, production and sales information increased the frequency and intensity of the stock price foam; The higher the clarity of the management's response to investors' questions, the more significantly it can reduce the frequency of stock price foam, but it has no significant impact on the strength of stock price foam. Further, the worse the external information environment is and the lower the shareholding ratio of institutional investors is, the more obvious the impact of information interaction on the foam of the company's share price is. The transparency of company information plays a part of the intermediary effect in this impact. The research findings contribute to a micro perspective understanding of the impact mechanism of information exchange behavior on the operation of the stock market in China's investor interaction platforms.
  • WANG Tao, CHEN Zhuo, YAN Bo
    Systems Engineering - Theory & Practice. 2024, 44(11): 3571-3585. https://doi.org/10.12011/SETP2023-1915
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    In order to alleviate traffic pressure, multiple cities in China have introduced various policies restricting the fuel vehicles, which to some extent has affected the competition between the new energy vehicles and the fuel vehicles. Based on the above reality, this paper constructs an automobile market competition decision-making model composed of a fuel vehicle automaker and a new energy vehicle automaker in consideration of consumers' anxiety about the new energy vehicles' range or energy replenishment. This paper analyzes the optimal decision-making of the two types of automakers under the government's three policy scenarios (license plate policy, license plate lottery, and the combination of the above two policies), and compares the equilibrium results of the various policies scenarios to explore the threshold conditions for the dominant policy choice of these two automakers in terms of demand and profit. The results show that these two automakers can always realize the optimal profits under the license plate policy, while they can realize the optimal profits under the license plate lottery and the combination of these two policies only when the degree of anxiety of consumers about the fuel vehicles caused by the license plate lottery is lower than that of the new energy vehicles. In addition, the license plate lottery and the license plate policy will not change the prices of these two types of vehicles. Finally, from the perspective of demand and profit, the combination of the license plate policy and the license plate lottery cannot be an optimal choice for the fuel vehicle automaker, while the license plate lottery cannot be an optimal choice for the new energy vehicle automaker. When consumers are highly anxious about the fuel vehicles and the new energy vehicles, the license plate policy can be an optimal choice for these two types of vehicle automakers. However, as the government imposes stricter restrictions on the lottery of the fuel vehicles, the likelihood that the license plate policy becomes a predominant choice for these two automakers will gradually decrease.
  • DAI Yeming, LI Yongheng, QI Yao
    Systems Engineering - Theory & Practice. 2024, 44(11): 3586-3597. https://doi.org/10.12011/SETP2023-1059
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    In order to guide electricity retailer and consumers to adjust the peak electricity demand reasonably and ensure a reliable power supply, a peak-regulating mechanism based on incentive-based demand response and considering consumer behavior factors is proposed. This mechanism takes into account both peak and off-peak power load periods, encourages consumers to transfer part of electricity demand during the peak period by guiding the retailer to formulate compensation standards, and then establishes a two-level programming model between the retailer and consumers considering the influence of consumer behavior on their own utilities. Among them, the upper retailer aims to maximize his own profit, and the lower consumers aim to maximize their total utilities. Finally, the optimal pricing strategies, compensation standard of retailer and the optimal power consumption of consumers are obtained. The numerical results show that adopting the peak-regulating mechanism adopted by electricity retailer is beneficial for improving retailer's profit and consumers' total utility, and the electricity retailer can improve his profit by appropriately increasing the baseline and compensation rate. The optimal electricity consumption of consumers is not related to their jealousy coefficient and guilt coefficient, but is related to the product of their dissatisfaction coefficient. In addition, the proposed peak-regulating mechanism can effectively reduce the load of power system during peak periods of electricity consumption, guide consumers to adjust their electricity habits and staggered electricity consumption, thereby ensure the stability of power system.
  • HUANG Junwei, MEI Shu'e, ZHONG Weijun
    Systems Engineering - Theory & Practice. 2024, 44(11): 3598-3611. https://doi.org/10.12011/SETP2023-0793
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    Nowadays many e-commerce platforms cooperate with third-party cashback websites or establish official cashback websites to make cashback promotions to boost sales. This paper constructs a game-theoretic model to investigate the optimal cashback mode selection of the e-commerce platform and the optimal participation strategy of the merchant under different cashback payment rules. The research reveals: At first, under the payment rule that the cashback provided by the merchant for the cashback website is fixed, when the fixed cashback payment is low, the e-commerce platform should establish an official cashback website and the merchant will participate in the platform's cashback promotion. Second, under the payment rule that the cashback provided by the merchant for the cashback website is decided by itself, only when the commission rate is high and the cashback channel utility discount factor is low while the proportion of customers who know the cashback website and are sensitive to the cashback that they can obtain from the cashback website is high, the platform should cooperate with a third-party cashback website, otherwise it should establish an official cashback website, and the merchant is always willing to participate in the platform's cashback promotion under this payment rule. Third, regardless of the payment rules, it is feasible for the e-commerce platform to operate the official cashback website at a loss under certain conditions. In the extension, this paper considers that two cashback modes coexist under different cashback payment rules.
  • JIANG Xiaolan, TIAN Lijun
    Systems Engineering - Theory & Practice. 2024, 44(11): 3612-3625. https://doi.org/10.12011/SETP2023-1248
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    How to stimulate right number of drivers to serve customers at the right time is the core of operations for ride-sourcing platforms. Based on the time expanded network, considering the labor supply heterogeneity of drivers with different behavioral characteristics, this paper assumes that drivers' utility consists of consumption utility and reference utility. A unified framework reconciling two behavioral theories is established to depict drivers' labor supply behaviors for working and corresponding equilibrium solution algorithm is proposed to analyze the schedule choices of drivers with different behavioral characteristics in an equilibrium market. Furthermore, two kinds of incentive modes, namely the commission-based one and the threshold-based one, are proposed, and corresponding models are developed to study the responses of drivers with different behavioral characteristics to different incentives. The optimal incentive strategies for the platform are explored. The results show that drivers driven by neoclassical behavior are more likely to work or supply more labor in response to an extra incentive than drivers driven by income-target behavior. Threshold-based incentive is more effective for full-time drivers who prefer to work long hours, while part-time drivers prefer to the commission-based incentive and threshold-based incentive with low threshold. This paper provides a theoretical reference and practical basis for platform to understand drivers' labor supply behaviors and further manage and stimulate labors.
  • GUO Mingxue, ZHAO Tingting, GAO Ziyou
    Systems Engineering - Theory & Practice. 2024, 44(11): 3626-3638. https://doi.org/10.12011/SETP2023-0592
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    Disruptive events, such as natural disasters and manmade attacks, could lead to multi-site structural damages and functional failures with various severities for road transportation systems. These events result in degraded system level of service and even disconnectivity between some origins and destinations. To enhance the resilience of road transportation system, various protection/restoration countermeasures can be taken for system components before/after the occurrence of disruptive events. These countermeasures help the system to resist to, to response to, and to recovery from disruptive events with better accumulated system performance over the time span. This paper briefly reviews the definition of transportation system resilience and the state of art for transportation system resilience assessment methods. Then, research efforts regarding the strategies' optimization for transportation system components' protection and restoration to enhance system resilience is highlighted. Last but not least, the outlook for future research directions in this field is discussed for the reference of audience.
  • TANG Kun, XU Tian, GUO Tangyi, SHAO Fei
    Systems Engineering - Theory & Practice. 2024, 44(11): 3639-3649. https://doi.org/10.12011/SETP2023-0877
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    As a representative of the transportation systems in China, high-speed railway (HSR) network plays an extremely important role at many levels of economy and strategy. This paper focuses on the topological structure and resilience of China's HSR transportation network from a hyper-network perspective. Initially, we construct a hyper-network representation of China's HSR system. We visualize this network, revealing instances where specific HSR lines detach from the main network. Subsequently, we choose metrics tailored to the characteristics of HSR transportation for topological analysis. Finally, we employ natural connectivity as an indicator to quantify network resilience. Dynamic assessments using both random and intentional strategies are conducted to evaluate the network's ability to withstand disruptions. Our results highlight the pivotal role of a few key nodes within the HSR hyper-network, such as Zhengzhou East Station and Nanjing South Station, which hold significant value. Experimental findings underscore that prioritizing attacks on these nodes has the most significant impact on the network's natural connectivity. This paper integrates hypergraph theory with the HSR network, taking into account geographical relevance and operational considerations. This integration enhances the precision of our study on the topological characteristics and resilience of the HSR transportation network. The outcomes of our research offer valuable scientific insights for the planning, construction, and operation of HSR networks. They hold substantial practical significance in advancing China's railway transportation sector.
  • TIAN Tian, LIU Yuxue, TANG Jiafu
    Systems Engineering - Theory & Practice. 2024, 44(11): 3650-3665. https://doi.org/10.12011/SETP2023-1528
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    This article proposes the operator-based vehicle relocation problem in free-return car-sharing systems. With the objective of minimizing total cost, considering factors such as differences in employee capabilities, network demand and capacity and whether vehicles must be relocated, we build a parking-lot based mixed integer programming and design a Constructive population algorithm based on probabilistic elite set (CPAPES). CPAPES uses virtual employee combinations to control the quality and diversity of individuals in the population, uses virtual cost vectors as genetic information, adopts an elite-set based probability construction method to generate individuals and multiple neighborhood search operators and variable neighborhood search techniques to improve individuals. Based on the characteristics of real data, we generate 832 instances in different scales under 16 scenarios to conduct numerical experiments. The experimental results validate the effectiveness of CPAPES and reveal the impact of employee capabilities, the proportion of vehicles that must be relocated, the spatial distribution of vehicles and the number and capacity of parking lots on the total cost of relocating vehicles. This article not only enriches the research on vehicle relocation problem, but also provides scientific decision support for car-sharing operators to reduce costs and improve efficiency.
  • TIAN Yu, WANG Daoping, HAO Mei
    Systems Engineering - Theory & Practice. 2024, 44(11): 3666-3680. https://doi.org/10.12011/SETP2023-1555
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    A supply chain consisting of suppliers, producers and consumers, and the suppliers and producers decide the carbon information disclosure degree and product premium according to the market situation. Parameters such as consumer information trust, consumer information sensitivity and information sharing benefit coefficient were introduced to construct a supply chain carbon information disclosure model under information asymmetry and a supply chain carbon information sharing model based on blockchain technology, and the optimal decision of different decision models was compared and analyzed. The results show that: 1) With the increase of the cost coefficient of carbon information disclosure, the decision-making of the supply chain is divided into three stages: Full disclosure of carbon information of suppliers and producers, full disclosure of carbon information of producers and partial disclosure of carbon information of suppliers and producers, and the optimal decision-making of the decision-making body shows a downward trend. 2) Except for the interval of the cost coefficient of a certain carbon information chain, the optimal carbon information disclosure degree of the manufacturer is always no lower than that of the supplier; when the initial price of the product is less than a certain threshold, the premium of the manufacturer's optimal product is higher. And the manufacturer's optimal decision is more sensitive to the change of related parameters. 3) When the cost coefficient of carbon information on-chain is less than the cost coefficient of traditional carbon information disclosure, the profit of the decision-making subject under the “blockchain + carbon information” sharing mechanism is much higher than the profit under information asymmetry.
  • CAO Mukun, CHEN Zequan, WANG Yao
    Systems Engineering - Theory & Practice. 2024, 44(11): 3681-3699. https://doi.org/10.12011/SETP2023-0218
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    The rapid development of the supply chain has driven the demand for the electronic and digital procurement of the supply chain. The leading supply chain node enterprises have begun to seek more efficient negotiation measures to cope with the high frequency of procurement demand. In contrast, the existing automatic negotiation models cannot fully support the increased complexity of real-time negotiation scenarios. This paper explores the automated negotiation model for multilateral procurement in the supply chain. First, the multi-issue one-to-many automated negotiation model is divided into modules. Based on the pretreated opponent information, the Bayesian method of continuous variables estimates the negotiators' preferences and promotes the multilateral multi-attribute negotiation to reach a win-win situation. Secondly, in the strategy generation part, twin delayed deep deterministic policy gradient algorithm (TD3) is introduced to realize the agent's perception of the negotiation process and the judgment of the negotiator's strategic behavior. Then, the enhanced Lagrange algorithm is introduced to output the counter-proposal that can maximize the joint benefits of both parties. Finally, this paper verifies the feasibility and effectiveness of the negotiation strategy model through human-computer experiments in various scenarios.
  • LIU Ye, WANG Yanan, HOU Wenhui, LIU Hui, WANG Jianqiang
    Systems Engineering - Theory & Practice. 2024, 44(11): 3700-3715. https://doi.org/10.12011/SETP2023-1899
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    Aiming at the problem of high similarity and low degree of discrimination between fraudulent samples and normal samples and the confusion of marginal normal samples in medical insurance fraud identification, this paper proposes a medical insurance fraud identification algorithm based on isolation loss and deep autoencoder (ISDAE). Aiming at the easy isolation of marginal fraud samples and sparse fraud samples, the algorithm proposes a sample isolation measure to quantitatively analyze the differences between the two types of samples from the perspective of feature distribution. On the basis, using DAE's ability to mine linear and nonlinear features of medical insurance and considering the interference of margin normal samples on model training, an isolation loss is defined in the latent space to achieve the aggregation of center normal samples and the separation of edge normal samples, thereby increasing the difference between fraudulent samples and normal samples. To further improve the fraud detection performance of the model, the fraud degree of samples is evaluated by integrating the isolation value and the reconstruction error. Finally, the performance of the proposed algorithm is verified on the Tianchi medical insurance dataset. The results show that the overall fraud identification performance of the proposed ISDAE algorithm is better than the comparative methods, and its performance is more stable.
  • TANG Zhipeng, CUI Ting, XIONG Shifeng
    Systems Engineering - Theory & Practice. 2024, 44(11): 3716-3728. https://doi.org/10.12011/SETP2023-1928
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    Bandwidth is the key to the estimation of the independent variable coefficients of geographically weighted regression models. The local independent variables with spatial correlation show various potential spatial heterogeneity by determining the most suitable bandwidth. Traditional geographically weighted regression models, including GWR, SGWR and MGWR, all adopt isotropic bandwidth for their independent variable coefficients. In this study, the constraint assumption about isotropic bandwidth is relaxed, an anisotropic bandwidth geographically weighted regression (AGWR) model is proposed, and the coefficient estimation process and the conditions of anisotropic bandwidth discrimination are given. Taking the fitting process of the influence factors of housing price in South Jiangsu and North Jiangsu of China as an example, the AGWR model is compared with other isotropic bandwidth models. The AGWR model shows good fitting ability. In Monte Carlo simulation, the AGWR model still maintains this advantage compared with other isotropic bandwidth models. The proposed AGWR model provides a basis for the quantitative study of anisotropy spatial difference problem to set up a suitable model form.
  • YU Jing, ZHANG Feiyu
    Systems Engineering - Theory & Practice. 2024, 44(11): 3729-3737. https://doi.org/10.12011/SETP2023-1616
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    Cost is an important consideration for decision makers when making decisions. A graph model for conflict resolution based on decision cost is established to describe the impact of cost on decision makers in conflict. The model is integrated with military science to form a graph model for military game based on cost. Firstly, a series of modeling elements of graph model are defined based on cost theory, and the definition of relative cost preference matrix and cost improvement reachable set are given. Secondly, the graph model based on decision cost is integrated with military science, and the concepts of killing cost and transfer cost are introduced into the model to form a graph model for military game based on cost. Finally, the graph model for military game is applied to a military conflict case to solve the possible choices of decision makers and the stable solution of the conflict. The results show that the model can effectively simulate the behavior of decision makers in military conflicts, and has certain guiding significance for actual combat.
  • BAI Yang, FAN Chengli, Fu Qiang, Zhao Haizhou, YU Dengxiu
    Systems Engineering - Theory & Practice. 2024, 44(11): 3738-3747. https://doi.org/10.12011/SETP2023-1600
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    Aiming at the fact that the traditional battle intent prediction model cannot meet the requirements of prediction accuracy and reliability for air defense operations under system confrontation, an intelligent battle intent prediction method for air defense targets based on BiLSTM-Attention (bi-directional long short-term memory-attention) and dynamic Bayesian network is proposed. Considering target state information and target tactical information comprehensively, the combat intent feature set of the air defense target is designed; making full use of the collected historical moment data and predicted future moment data, the two-way loop and attention mechanism is introduced to simulate the reasoning process of the decision maker on the combat posture, highlighting the key information that affects the type of ballistic trajectory, and increasing the accuracy of the ballistic trajectory prediction of the air defense target. On this basis, a dynamic Bayesian network is constructed by combining the target trajectory, type, altitude and velocity to realize the accurate prediction of air defense target intent. The simulation experiments consider the effect of radar switch on target trajectory, and verify the feasibility and superiority of the proposed method under game confrontation conditions by comparing it with the traditional target intent prediction method.
  • QIAO Yidan, CHEN Dengkai, SUN Yiwei, LIAO Wenyi
    Systems Engineering - Theory & Practice. 2024, 44(11): 3748-3764. https://doi.org/10.12011/SETP2023-0491
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    Compared with other complex operation systems, manned deep submergence operation has the characteristics of closed and narrow extreme environment, as well as the nature of long-endurance and high-load tasks. Once the manned deep submerging accident occurs, it is likely to cause major consequences. Therefore, it is urgent to develop a dynamic probability assessment method that can quantitatively assess the cognitive behavior performance and operational risk of oceanauts. The method for modeling the cognitive behavior of oceanauts based on knowledge and experience is proposed, which integrates more performance influencing factors into the IDAC human reliability analysis method, and develops the cognitive environment simulation program for probabilistic assessment of operational risk through system dynamics method to simulate the dynamic HEP of oceanauts. Taking a manned deep submerging mission as an example, the feasibility of the proposed method is verified. The research results would help to accurately identify key risk tasks, and guide technicians to overcome relevant technical problems, so as to improve the overall work efficiency of the human-machine-environment system in the cabin.