فهرس المقالات Forward algorithm

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  1 - An Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set
  Omid SojodiShijani Nader Rezazadeh
  Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the أکثر

  Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the mean statistic for determining the values of Markov functions on unstable statistical data set has led to a significant reduction in the accuracy of Markov algorithms including Forward algorithm used in solving Evaluation problems. The model’s parameters such as the occurrence probability of observation symbol being produced by state, varies directly among the successive events. Since the probability value of the above-mentioned parameter plays an important role in the accurate Evaluation and assessment of the probability of observations’ occurrence in the Evaluation problem by Forward algorithm, the variations between events and observations generated by the States should be automatically extracted. In order to achieve this, the current paper proposes an adaptive parameter for event probability in order to match and adjust the variations in the parameter after each event during the lifetime of Forward algorithm. The results of the experiments on a real set of data indicates the superior performance of the proposed method compared to other conventional methods regarding their accuracy. تفاصيل المقالة
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  2 - Abnormality Detection in a Landing Operation Using Hidden Markov Model
  Hasan Keyghobadi Alireza Seyedin
  The air transport industry is seeking to manage risks in air travels. Its main objective is to detect abnormal behaviors in various flight conditions. The current methods have some limitations and are based on studying the risks and measuring the effective parameters. T أکثر

  The air transport industry is seeking to manage risks in air travels. Its main objective is to detect abnormal behaviors in various flight conditions. The current methods have some limitations and are based on studying the risks and measuring the effective parameters. These parameters do not remove the dependency of a flight process on the time and human decisions. In this paper, we used an HMM-based method which is among the main methods of situation assessment in data fusion. This method includes two clustering levels based on data and model. The experiments were conducted with B_777 flight data and the variables considered in the next generation of ADS_B. According to the results of this study, our method has high speed and sensitivity in detection of abnormal changes which are effective in the flight parameters when landing. With the dynamic modelling, there is no dependency on time and conditions. The adaptation of this method to other air traffic control systems makes its extension possible to cover all flight conditions. تفاصيل المقالة