Reliability assessment of power converters is extremely important due to the degradation of the converter performance under the thermal and electrical stresses. The normal or abnormal operation of a converter is determined based on the quality of the manufacturing process and the environmental and operating conditions. The failure indices are based on the previous failures data which are calculated using the history of the main parameter of the converter which are strongly affected by the aging process. In this article, a new real-time indicator is introduced using the monitoring of the main parameters of the converter. Each indicator is modeled using Replicator Neural Network (RNN) and the network reconstruction coefficient or reconstruction error will be considered as the reliability index or the coefficient of anomaly of the converter. In fact, the reliability assessment is based on the comparison between a reference model of the converter in normal conditions and the estimation of abnormal operation of the converter in the future. In the proposed method, a normal distribution function on the reconstructed error signal, their fit and percentage distance are introduced as the abnormality risk coefficient. The advantages of this method include taking into account all the uncertainties in the process of Manufacturing the power switch and its working conditions, not needing the aging test process in preparing the failure data and taking into account all the failures

connecting to rule-makers in order to set favorable rules (lobbying) or paying government executives to bend the current rule (bribing) are the two main strategies for influencing government. This study in an evolutionary game model explain why bribing may become widespread while other states like compliance and cooperative lobbying are Pareto superior. The theoretical model is used to study the effect of social parameters on firm’ s choice between lobbying and bribing. The results indicate that social disapproval of bribery has a negative impact on corruption. The effect, however, depends on the history of countries. Countries with a long history of corruption have much more difficult task in fight with corruption. Cooperation was the second social factor to be investigated. The effect of cooperation on lobbying is indirect through alleviating the difficulty and costs of linking to the government. Whenever and wherever linking is difficult, firms by cooperation, can make it less impeding.

In this paper, using Evolutionary Game Theory, we study the evolution of currency as an important and influential problem in the world economy by presenting three new models. In examining the evolution of two different currencies, we prove that if the parties chose either of the two currencies with a fixed probability, it will not have an impact on the evolutionary process of these currencies. Considering a new action based on either the possibility of using any two currencies or a preference between the two currencies, we illustrate their impact on the evolutionary process of currencies. In fact, we examine the impact of different actions and strategies on the evolutionary process between the two types of currencies.

Due to the stochastic nature of wind energy, allocating an appropriate investment incentive for wind generation technology (WGT) is a complicated issue. We propose an improvement on the traditional incentive, known as capacity payment mechanism (CPM), to reward the wind generators based on their performance exogenously affected by the wind energy potential of the location where the turbines are installed, and therefore, lead the investments towards locations with more generation potential. In CPM, a part of investment cost of each generator is recovered through fixed payments. However, in our proposal, wind generators are rewarded according to dynamic forecasts of the wind energy potential of the wind farm where they are located. We use an auto-regressive moving average (ARMA) model to forecast the wind speed fluctuations in long-term while capturing the auto-correlation of wind velocity variation in consecutive time intervals. Using the system dynamics (SD) modelling approach a competitive electricity market is designed to examine the efficiency of the proposed incentive. Performing a simulation analysis, we conclude that while a fixed CPM for wind generation can decrease the loss of load durations and average prices in long-term, the proposed improvement can provide quite similar results more efficiently.

Trust, as a multi-disciplinary research domain, is of high importance in the area of network security and it has increasingly become an important mechanism to solve the issues of distributed network security. Trust is also an effective mechanism to simplify complex society, and is the source to promote personal or social cooperation.From the perspective of network ecological evolution, we propose the model of the P2P Social Ecological Network. Based on game theory, we also put forward network trust dynamics and network eco-evolution by analysis of network trust and the development of the dynamics model. In this article, we further analyze the dynamic equation, and the evolutionary trend of the trust relationship between nodes using the Replicator dynamics principle. Finally, we reveal the law of trust evolution dynamics, and the simulation results clearly describe that the dynamics of trust can be effective in promoting the stability and evolution of networks.

Background: Immunotherapy is a recently developed method of cancer therapy, aiming to strengthen a patient’ s immune system in different ways to fight cancer. One of these ways is to add stem cells into the patient’ s body. Methods: The study was conducted in Kermanshah, western Iran, 2016-2017. We first modeled the interaction between cancerous and healthy cells using the concept of evolutionary game theory. System dynamics were analyzed employing Replicator equations and control theory notions. We categorized the system into separate cases based on the value of the parameters. For cases in which the system converged to undesired equilibrium points, “ stem-cell injection” was employed as a therapeutic suggestion. The effect of stem cells on the model was considered by reforming the Replicator equations as well as adding some new parameters to the system. Results: By adjusting stem cell-related parameters, the system converged to desired equilibrium points, i. e., points with no or a scanty level of cancerous cells. In addition to the theoretical analysis, our simulation results suggested solutions were effective in eliminating cancerous cells. Conclusion: This model could be applicable to different types of cancer, so we did not restrict it to a specific type of cancer. In fact, we were seeking a flexible mathematical framework that could cover different types of cancer by adjusting the system parameters.