Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Modelling of a Human Driver’s Interaction with Vehicle Automated Steering Using Cooperative Game Theory

The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.

Game theory approach to optimal capital cost allocation in pollution control

This paper tries to integrate game theory, a very useful tool to resolve conflict phenomena, with optimal capital cost allocation issue in total emission control. First the necessity of allocating optimal capital costs fairly and reasonably among polluters in total emission control was analyzed. Then the possibility of applying game theory to the issue of the optimal capital cost allocation was expounded. Next the cooperative N person game model of the optimal capital cost allocation and its solution ways including method based on Shapley value, least core method, weak least core methods, proportional least core method, CGA method, MCRS method and so on were delineated. Finally through application of these methods it was concluded that to apply game theory in the optimal capital cost allocation issue is helpful to implement the total emission control planning schemes successfully, to control pollution effectively, and to ensure sustainable development.

On Instructive Meaning of Game Theory in Business Negotiation

1944年《博弈论与经济行为》一书的出版,奠定了现代博弈论理论研究的基石。此后,越来越多的学者开始研究博弈论和商务谈判的关系。本文介绍了博弈论和商务谈判的一些知识,以红黑博弈模型为例分析了博弈论在商务谈判中的应用,得出商务谈判的核心是实现双赢的结论。

The Effect of Reputation to the Moral Hazard in C2C E-Market with Game Theory

It is well known that the reputation is the basis of a seller to survive and gain trust from customers in a competitive business environment. But as the existence of information asymmetry between buyer and seller, the moral hazard problem is the key obstacle that impedes the benefits of related shareholders and reduces the efficiency of total market. It is crucial to design a control mechanism to avoid the negative impact of moral hazard. This paper studies the principal and agent relationship between buyer and seller in C2C e-market;because of the influence of information asymmetry, many customers suffered from being cheated by sellers with defective products in practice. These frequent cases will deteriorate long term relationship between sellers and buyers. Here we focus on the analysis of the causes of moral risks and the effect of reputation on oral risk with repeated game theory. The purpose of this paper is to help both firms and customers effectively avoid morality risk and realize a win-win situation.

Pricing Game Model of Wasted Clothing Recycling and Remanufacturing Based on Government Subsidy

In the global environment of pursuing resource regeneration and green environmental protection, more and more wasted clothing need to be solved. In order to make full use of the wasted clothing and save land and soil resources, an idea of wasted clothing's recycling and remanufacturing is put forward. In the new idea a pricing game model is established basing on Stacklberg differential game theory between traditional and remanufactured clothing. In this model, the differences in consumers' willingness to pay and the government's subsidies are considered. Government's optimal subsidy are obtained which ensure not only the interests of manufacturers but also environmental reputation and maximum social benefits. The study is helpful to push the wasted clothing's recycling and remanufacturing plan. It makes some index more precise quantification as government's subsidy, manufacturers and the social benefits. Government and manufactures can make the detailed cooperation plan reference to it.

Improved algorithmic mechanism based on game theory in computational grids

Computational grids （CGs） aim to offer pervasive access to a diverse collection of geographically distributed resources owned by different serf-interested agents or organizations. These agents may manipulate the resource allocation algorithm in their own benefit, and their selfish behavior may lead to severe performance degradation and poor efficiency. In this paper, game theory is introduced to solve the problem of barging for resource collection in heterogeneous distributed systems. By using the Cournot model that is an important model in static and complete information games, the algorithm is optimized in order to maximize the benefit. It can be seen that the approach is more suitable to the real situation and has practical use. Validity of the solutions is shown.

The Game-Theoretical Model of Using Insecticide-Treated Bed-Nets to Fight Malaria

Malaria infection is a major problem in many countries. The use of the Insecticide-Treated Bed-Nets (ITNs) has been shown to significantly reduce the number of malaria infections;however, the effectiveness is often jeopardized by improper handling or human behavior such as inconsistent usage. In this paper, we present a game-theoretical model for ITN usage in communities with malaria infections. We show that it is in the individual’s self interest to use the ITNs as long as the malaria is present in the community. Such an optimal ITN usage will significantly decrease the malaria prevalence and under some conditions may even lead to complete eradication of the disease.

Exploring the dynamic evolutionary mechanism of game model on the protection of traditional villages

With the rapid improvement of urbanization and industrialization in countries around the world,how to effectively solve the rapid demise of traditional villages is a social dilemma faced by all countries,which is why a series of relevant protection regulations have been promulgated in different historical periods.However,the formulation of relevant policies is still not scientific,universal,and long-term.In this study,we constructed an evolutionary game model of local governments and residents based on the evolutionary game theory(EGT),which is used to explore the evolutionary stability strategy(ESS)and stability conditions of stakeholders under the premise of mutual influence and restriction.Besides,the study also included the analysis about the impacts of different influence factors on the evolution tendency of the game model.At the same time,numerical simulation examples were used to verify the theoretical results and three crucial conclusions have been drawn.Firstly,the strategic evolution of stakeholders is a dynamic process of continuous adjustment and optimization,and its results and speed show consistent interdependence.Secondly,the decision-making of stakeholders mainly depends on the basic cost,and the high cost of investment is not conducive to the protection of traditional villages.Thirdly,the dynamic evolutionary mechanism composed of different influence factors will have an impact on the direction and speed of decision-making of stakeholders,which provides the basis for them to effectively restrict the decision-making of each other.This study eliminates the weaknesses of existing research approaches and provides scientific and novel ideas for the protection of traditional villages,which can contribute to the formulation and improvement of the relevant laws and regulations.

Dynamical Systems Theory Compared to Game Theory: The Case of the Salamis’s Battle

In this paper, we present an innovative non–linear, discrete, dynamical system trying to model the historic battle of Salamis between Greeks and Persians. September 2020 marks the anniversary of the 2500 years that have passed since this famous naval battle which took place in late September 480 B.C. The suggested model describes very well the most effective strategic behavior between two participants during a battle (or in a war). Moreover, we compare the results of the Dynamical Systems analysis to Game Theory, considering this conflict as a “war game”.

Game Theory Application and Strategic Bidding in Electricity Supply Market

This paper introduced the application of game theory in electricity power market. Moreover, the electricity pool model and the merit order dispatch method was introduced. In pool mode, participants are trying to maximize their benefit via competition with each other. Hence the market can be regarded as a non-cooperative game, especially, the electrical supply competition. Players (generators) could use strategic bidding to occupy advantages in competition. The bidding strategies of generators in electricity pool model were researched via build a 3-generator competition model. Moreover, Nash Equilibrium idea was used to explore generator’s optimal bidding strategy. The results show when players are in Nash Equilibrium;thestrategy is their optimal bidding strategy.

A Novel Dynamic Decision Model in 2-player Symmetric Repeated Games

Considering the dynamic character of repeated games and Markov process, this paper presented a novel dynamic decision model for symmetric repeated games. In this model, players' actions were mapped to a Markov decision process with payoffs, and the Boltzmann distribution was introduced. Our dynamic model is different from others', we used this dynamic model to study the iterated prisoner's dilemma, and the results show that this decision model can successfully be used in symmetric repeated games and has an ability of adaptive learning.

Market Share Model of Price and Advertising Combined Game in Duopoly

The marketing share model of price and advertising in a duopoly market was studied in this paper. Market response curves of price and advertising were presented to calculate the reasonable range based on the market forecast results. The interaction effect of price and advertising was considered,and the game theory was applied to a two-stage price and advertising competition which involved the market share model. A marketing decision support system (MDSS) was developed and simulation data was provided to give the solutions. The operation results show that the leading enterprise makes higher price,spends more on advertising,and earns more profit,while the small-scale enterprise has to lower the price,spend less on advertising,and has slightly higher profit rate. The system is shown to be adaptable to a wide variety of realistic situations.

Excess Benefit Allocation in Shared Savings Based on Non-cooperative Game Theory

Energy saving income distribution mode is of great significance to the energy industry.With the continuous application of new technologies,the problem of excess energy saving income distribution has become one of the obstacles to the appreciation of energy performance.At present,the distribution of risk and income is mainly based on the contribution of risk and income,which has some limitations.The benefit distribution of energy saving negotiation between energy saving service companies and clients can be regarded as a bargaining process where an effective range satisfying both parties can be obtained.This provides a new perspective in solving the problem of excess energy saving income distribution in energy management contract projects.

基于组合赋权-云模型的智能建造应用成熟度的评价

为解决传统施工方式存在的问题,建筑施工企业向智能建造方式逐渐转型已是大势所趋。针对新时代、新基建对智能建造施工的要求并结合能力成熟度理论,提出一种基于组合赋权-云模型的智能建造应用成熟度评价模型。首先,从施工、智能、其他3个维度,构建包含勘测、设计规划、施工现场管理、资源要素、智能建造技术、数据驱动、企业顶层设计7个类别的智能建造应用成熟度评价体系。其次,采用G1法与熵权法确定各指标的主、客观权重,运用博弈论进行权重组合。最后,通过云模型展示施工企业智能建造应用成熟度等级,并依据评价结果进行展望。研究结果表明:施工企业智能建造应用成熟度评价等级为“集成共享级”,评价结果与该企业实际情况吻合,验证了本文方法的适用性与科学性,为施工企业智能建造应用的发展提供科学依据。

基于网格化和雷达图的建筑抗震设防最优烈度决策模型研究

目前的建筑抗震设防最优烈度研究主要是从经济性或安全性进行考虑,然而合理的建筑抗震设防最优烈度需要综合考虑经济和安全性指标。本文将研究区域进行网格化,结合其周围历史地震数据进行地震危险性分析,以经济性指标和安全性指标作为抗震设防最优烈度评价指标;运用博弈论组合赋权法确定各指标权重,建立基于网格化和雷达图的建筑抗震设防最优烈度决策模型,将该模型运用到四川省崇州市钢混结构和砖混结构的抗震设防研究中。通过对比分析该模型数据发现:钢混结构按8度设防时,相比于6度、7度和9度设防,其抗震设防综合效益分别提升57.2%、29.6%和3.9%;砖混结构按8度设防时,相比于未设防、6度、7度和9度设防的抗震设防综合效益分别提升60.6%、19.2%、2.4%和1.9%。因此,崇州市钢混结构和砖混结构按8度设防时,为最优抗震设防烈度,抗震设防综合效益最佳,验证了该模型的有效性。

基于组合赋权-VIKOR法的山区施工便道方案优选模型

为对山岭地区施工便道方案进行客观、全面、精准评价,结合行业设计规范和相关研究成果,构建山区施工便道方案指标评价体系,提出一种山区施工便道方案优选模型。该模型采用三标度层次分析法和熵权法分别计算评价指标的主、客观权重,基于博弈论思想对主、客观权重进行赋权确定综合权重,并运用VIKOR法(多准则妥协解排序法)对山区施工便道方案进行优选。以某高速公路山区施工便道方案比选为工程实例,针对4种施工便道方案进行综合比选,并将本文模型与加权TOPSIS法(优劣解距离法)、灰色加权关联分析法进行对比分析。研究结果表明:3种计算模型得出的最优方案一致,组合赋权的方法克服了单一赋权的缺陷,使指标评价更客观。相比于加权TOPSIS法和灰色加权关联分析法,本文模型能抵御外部因素的干扰,明显地辨别方案之间的差距,得到准确清晰的方案排序,且当评价方案众多时,本文模型能够提供更多方案选择,得到最优化方案。