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.

An integrated MINLP model for multi-party coordination in downstream oil supply chain

Cooperation among enterprises can bring overall and individual performance improvement,and a smooth coordination method is indispensable.However,due to the lack of customized coordination methods,cooperation in the downstream oil supply chain cannot be carried out smoothly.This paper intends to propose a multi-party coordination method to promote cooperation between oil shippers and pipeline operator by optimizing oil transportation,oil substitution and pipeline pricing schemes.An integrated game-theoretic modeling and analysis approach is developed to characterize the operation behaviors of all stakeholders in the downstream oil supply chain.The proposed mixed integer nonlinear programming model constrains supply and demand capacity,transportation routes,oil substitution rules and pipeline freight levels.Logarithm transformation and price discretization are introduced for model linear approximation.Simulation experiments are carried out in the oil distribution system in South China.The results show that compared to the business-as-usual scheme,the new scheme saves transportation cost by 3.48%,increases pipeline turnover by 5.7%,and reduces energy consumption and emissions by 7.66%and 6.77%.It is proved that the proposed method improves the revenue of the whole system,achieves fair revenue distribution,and also improves the energy and environmental benefits of the oil supply chain.

Noncooperative Model Predictive Game With Markov Jump Graph

In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the reality,the state and input constraints have been considered along with the external disturbances.An iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed manner.Sufficient conditions are established to guarantee the convergence of the proposed algorithm.In addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying MPSs.Finally,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.

Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment

The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment.It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players,as well as the impact of participants’manipulative behaviors on the state changes of the players.A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario.Subsequently,the strategy selection interaction relationship,strategy evolution stability,and dynamic decision-making process of the game players are investigated and verified by simulation experiments.The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent’s strategies.Especially in a highly uncertain environment,even small information asymmetry or miscalculation may have a significant impact on decision-making.This also confirms the feasibility and effectiveness of the method proposed in the paper,which can better explain the behavioral decision-making process of the agent in the interaction process.This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model.

Parental Psychological Control and Internet Gaming Disorder Tendency:A Moderated Mediation Model of Core Self-Evaluation and Intentional Self-Regulation

Internet gaming disorder(IGD)among junior high school students is an increasingly prominent mental health concern.It is important to look for influences behind internet gaming disorder tendency(IGDT)in the junior high school student population.The present study aimed to reveal the explanatory mechanisms underlying the association between parental psychological control(PPC)and internet gaming disorder tendency among junior high school students by testing the mediating role of core self-evaluation(CSE)and the moderating role of intentional self-regulation(ISR).Participants in present study were 735 Chinese junior high school students who completed offline self-report questionnaires on parental psychological control,core self-evaluation,intentional self-regulation,and Internet gaming disorder tendency.Analyses were conducted via mediation and moderated mediation.The results showed that:(1)Parental psychological control was positively related to junior high school students’Internet gaming disorder tendency.Core self-evaluation,and intentional self-regulation were negatively related to junior high school students’Internet gaming disorder tendency,respectively.(2)Core self-evaluation partially mediated the relationship between parental psychological control and junior high school students’Internet gaming disorder tendency.(3)Intentional self-regulation moderated the association between parental psychological control and Internet gaming disorder tendency,as well as the relationships between parental psychological control and core self-evaluation and core self-evaluation and Internet gaming disorder tendency in the mediated model.Based on these findings,we believe that there is a need to weaken parental psychological control,strengthen junior high school students’core self-evaluation and intentional self-regulation,and to recognize the important role of parents as well as their children’s personal positive traits in the healthy development of junior high school students.

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.

Chaos game representation walk model for the protein sequences

A new chaos game representation of protein sequences based on the detailed hydrophobic-hydrophilic （HP） model has been proposed by Yu et al （Physica A 337（2004） 171）. A CGR-walk model is proposed based on the new CGR coordinates for the protein sequences from complete genomes in the present paper. The new CCR coordinates based on the detailed HP model are converted into a time series, and a long-memory ARFIMA（p, d, q） model is introduced into the protein sequence analysis. This model is applied to simulating real CCR-walk sequence data of twelve protein sequences. Remarkably long-range correlations are uncovered in the data and the results obtained from these models are reasonably consistent with those available from the ARFIMA（p, d, q） model.

Strategic games on a hierarchical network model

Among complex network models,the hierarchical network model is the one most close to such real networks as world trade web,metabolic network,WWW,actor network,and so on.It has not only the property of power-law degree distribution,but also the scaling clustering coefficient property which Barabási-Albert(BA)model does not have.BA model is a model of network growth based on growth and preferential attachment,showing the scale-free degree distribution property.In this paper,we study the evolution of cooperation on a hierarchical network model,adopting the prisoner's dilemma(PD)game and snowdrift game(SG)as metaphors of the interplay between connected nodes.BA model provides a unifying framework for the emergence of cooperation.But interestingly,we found that on hierarchical model,there is no sign of cooperation for PD game,while the fre-quency of cooperation decreases as the common benefit decreases for SG.By comparing the scaling clustering coefficient prop-erties of the hierarchical network model with that of BA model,we found that the former amplifies the effect of hubs.Considering different performances of PD game and SG on complex network,we also found that common benefit leads to cooperation in the evolution.Thus our study may shed light on the emergence of cooperation in both natural and social environments.

Multi-Modal Data Analysis Based Game Player Experience Modeling Using LSTM-DNN

Game player modeling is a paradigm of computational models to exploit players’behavior and experience using game and player analytics.Player modeling refers to descriptions of players based on frameworks of data derived from the interaction of a player’s behavior within the game as well as the player’s experience with the game.Player behavior focuses on dynamic and static information gathered at the time of gameplay.Player experience concerns the association of the human player during gameplay,which is based on cognitive and affective physiological measurements collected from sensors mounted on the player’s body or in the player’s surroundings.In this paper,player experience modeling is studied based on the board puzzle game“Candy Crush Saga”using cognitive data of players accessed by physiological and peripheral devices.Long Short-Term Memory-based Deep Neural Network(LSTM-DNN)is used to predict players’effective states in terms of valence,arousal,dominance,and liking by employing the concept of transfer learning.Transfer learning focuses on gaining knowledge while solving one problem and using the same knowledge to solve different but related problems.The homogeneous transfer learning approach has not been implemented in the game domain before,and this novel study opens a new research area for the game industry where the main challenge is predicting the significance of innovative games for entertainment and players’engagement.Relevant not only from a player’s point of view,it is also a benchmark study for game developers who have been facing problems of“cold start”for innovative games that strengthen the game industrial economy.

Case Study on the Forestry Cooperation Model from Game Structure Perspective

Take Chinese yew cooperative organization for example,different game structures of forestry cooperation model were analyzed,the elative merit and applicable occasion was discussed combined with empirical investigation,and some suggestions were given also.The results showed that depending entirely on normal forest farmers cooperate spontaneously is difficult.Policies should be designed from the perspective of promoted village cadres and influential family salons to cooperation.When market factors become the main obstacle,it is necessary to introduce companies,relax constraints of forest management and build the right market atmosphere.According to unequal status of company and forest farmers,develop the cooperation model of " company + cooperation organization + farmers".In certain circumstances,especially there are several companies vicious competition,the intervention of association can play a coordinating role.

Reverse Engineering, Some Board Games as a Key to the Development of Artificial Intelligence and Construction of Economic Models

Reverse engineering, also called back engineering, is the process of extracting knowledge or designing information from anything： mechanical device electronic components, computer programs, or biological, chemical matters, and--subsequently--analyzing its components. Reverse engineering can be applied for the sake of creating artificial intelligence, e.g. when the used methods are based on very old games, such as Go and chess. Many generations of computers are able to play at the same level as human grandmasters. A computers＇ arrival at that level is due to imitation of human Go or chess play. A particular emphasis shall be placed upon the Go game, known for 5,500 years. Invented in China, it may be classified as the oldest board game, having its ardent enthusiasts until present times. Old physical issues can be easily projected upon the modeling of new economic phenomena and quantum games. The aim of this paper is to discuss the applications of reverse engineering, traditional social games and other domains, such as quantum physics, to the analysis of utterly new social as well as economic phenomena.

Research on Financing Game Model of Small and Medium-sized Enterprises based on Different Risk Categories

With the development of market economy and the deepening of economic system reform, some of the Small and medium-sized（SME） enterprises have become the most dynamic economic growth point in the national economy. Nevertheless, SMEs are facing a lot of problems in the market competition, such as technical backwardness, information lag, lack of talents, etc.. The healthy development of SMEs is very important, whereas, SMEs’ financing is a worldwide problem, and the result of financing game between banks and enterprises depends on a variety of decision-making factors. In this paper, from the point of view of bank, we analyze the diffi culties of external financing of SMEs, and establish a financing game model based on different risk categories, in order to better solve the problems that remain in the process of financing and promote the healthy and sustainable development of SMEs.

System dynamics of behaviour-evolutionary mix-game models

In real financial markets there are two kinds of traders： one is fundamentalist, and the other is a trend-follower. The mix-game model is proposed to mimic such phenomena. In a mix-game model there are two groups of agents： Group 1 plays the majority game and Group 2 plays the minority game. In this paper, we investigate such a case that some traders in real financial markets could change their investment behaviours by assigning the evolutionary abilities to agents： if the winning rates of agents are smaller than a threshold, they will join the other group; and agents will repeat such an evolution at certain time intervals. Through the simulations, we obtain the following findings： （i） the volatilities of systems increase with the increase of the number of agents in Group 1 and the times of behavioural changes of all agents; （ii） the performances of agents in both groups and the stabilities of systems become better if all agents take more time to observe their new investment behaviours; （iii） there are two-phase zones of market and non-market and two-phase zones of evolution and non-evolution; （iv） parameter configurations located within the cross areas between the zones of markets and the zones of evolution are suited for simulating the financial markets.

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.

Hysteresis behavior and nonequilibrium phase transition in a one-dimensional evolutionary game model

We investigate a simple evolutionary game model in one dimension. It is found that the system exhibits a discontinuous phase transition from a defection state to a cooperation state when the b payoff of a defector exploiting a cooperator is small. Furthermore, if b is large enough, then the system exhibits two continuous phase transitions between two absorbing states and a coexistence state of cooperation and defection, respectively. The tri-critical point is roughly estimated. Moreover, it is found that the critical behavior of the continuous phase transition with an absorbing state is in the directed percolation universality class.

A CONNECTION ADMISSION CONTROL SCHEME BASED ON GAME THEORETICAL MODEL IN ATM NETWORKS

In this paper, the main schemes of connection admission control (CAC) in ATM networks are briefly discussed especially the principle of dynamic bandwidth allocation. Then the fair share of the bandwidth among different traffic sources is analyzed based on cooperative game model. A CAC scheme is proposed using the genetic algorithm (GA) to optimize the bandwidth-delay-product formed utilization function that ensures the fair share and accuracy of accepting/rejecting the incoming calls. Simulation results show that the proposed scheme ensures fairness of the shared bandwidth to different traffic sources.

Certainty of patient survival with reference to game information dynamic model

This paper is concerned with Hepato-Cellular Carcinoma (HCC) patients treated naturopathic agents. Patients treated with ≥4 agents survived significantly longer than patients treated with ≤3 agents. The great effect is seen in patients treated with at least 4 agents that include Cordyceps sinensis. This greater certainty of patient survival without toxic side effects is significant benefit comparing with the conventional therapy. Treatment of HCC with a regimen of ≥4 agents prepared from natural products is associated with greater certainty of patient survival in a substantial portion of patients. The information dynamic model for certainty of patient survival is derived based on fluid mechanics, where a series of approximate solutions of the flow between two parallel flat walls, one of which is at rest, the other is suddenly accelerated from the rest to a constant velocity are used. The kinetic energy of certainty of patient survival decreases with increasing time, while the potential energy increases with increasing time. Total mechanical energy of patients treated with 4 or more agents is smaller than that treated with 3 or fewer agents. The kinetic energy (potential energy) of patients treated with 4 or more agents decreases (increases) more slower than the kinetic energy (potential energy) of patients treated with 3 or fewer agents.

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.

A Three-Stage Stochastic Dynamic Pricing Game Model Affected by New Products into the Market

In real-life marketing, a common phenomenon is that the prices of current product will have been cut down even the new product has not gone into market yet. Thus, it is very important for merchant to set the strategy which can make the excepted revenue maximum. So, this paper constructs a three-stage stochastic dynamic pricing game model for analyzing the influence of the uncertainty of entry timing of the new products on pricing of products being sold. By analyzing of the pricing strategy, there are big differences in the predictions of new product going into market between merchant and customers;the merchant will adopt cutting price for promotion strategy to reduce negative influence of the new products on the demand of the products sold now. Otherwise, the merchant will adopt the strategy of maximizing current period’s profit.

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 intousluced. 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.