• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.825-838
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• 2014

The stationary Markov chain model has been widely used as a daily rainfall simulation model. A main assumption of the stationary Markov model is that statistical characteristics do not change over time and do not have any trends. In other words, the stationary Markov chain model for daily rainfall simulation essentially can not incorporate any changes in mean or variance into the model. Here we develop a Non-stationary hidden Markov chain model (NHMM) based stochastic downscaling scheme for simulating the daily rainfall sequences, using general circulation models (GCMs) as inputs. It has been acknowledged that GCMs perform well with respect to annual and seasonal variation at large spatial scale and they stand as one of the primary sources for obtaining forecasts. The proposed model is applied to daily rainfall series at three stations in Nakdong watershed. The model showed a better performance in reproducing most of the statistics associated with daily and seasonal rainfall. In particular, the proposed model provided a significant improvement in reproducing the extremes. It was confirmed that the proposed model could be used as a downscaling model for the purpose of generating plausible daily rainfall scenarios if elaborate GCM forecasts can used as a predictor. Also, the proposed NHMM model can be applied to climate change studies if GCM based climate change scenarios are used as inputs.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.61-69
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• 2021

The military pension deficit is increasing due to an increase in the average life expectancy and pension option rate, and a significant reason for this is estimated to be a continued increase in the number of military pension recipients. In terms of the soundness of military pension finances, this paper uses the Markov chain model to validate the stability of the military group, suggesting the direction of future military pension system in terms of the ratio of pension receipts to employees, and verifying the feasibility of the method applied through verification. Through this paper, we have confirmed that the initial 45,270 military personnel converge to 43,141 after a certain period of time and reach a stable state, which is expected to help us to estimate the long term size of military pension recipients to confirm the direction of national financial support. Military man who are eligible for pensions for more than 20 years have a relatively low rate of turnover or retirement compared to ordinary private groups, making it easier to define their status and simplify state transition probabilities. Therefore, it is expected that the sustainability of the military pension will be confirmed from a long term perspective by viewing the military group as a system and applying it to the Markov chain model by checking the probability of transfer of status such as promotion, maintaining the current grade, and retirement during the period.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.265-273
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• 2018

In this paper, we propose an acoustic event detection method in tunnels using non-negative tensor factorization (NTF) and hidden Markov model (HMM) applied to multi-channel audio signals. Incidents in tunnel are inherent to the system and occur unavoidably with known probability. Incidents can easily happen minor accidents and extend right through to major disaster. Most incident detection systems deploy visual incident detection (VID) systems that often cause false alarms due to various constraints such as night obstacles and a limit of viewing angle. To this end, the proposed method first tries to separate and detect every acoustic event, which is assumed to be an in-tunnel incident, from noisy acoustic signals by using an NTF technique. Then, maximum likelihood estimation using Gaussian mixture model (GMM)-HMMs is carried out to verify whether or not each detected event is an actual incident. Performance evaluation shows that the proposed method operates in real time and achieves high detection accuracy under simulated tunnel conditions.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.159-163
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• 1991

For a continuous-time absorvation Markov chain, we apply and simplify the general method of finding the transition rates given the transition probabilities obtained from discrete observation of the continuous system. An example is given.

• ICROS
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• v.2 no.1
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• pp.31-36
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• 1996

본 고의 취지는 강인 제어 방법 중 하나인 확률제어의 동향을 정리하여 보는 것이다. 다음 절에서는 확률적으로 모델을 할 때 기본이 되는 Brownian 운동과 마코프 프로세스에 대하여 간단히 설명하고, 3절에서는 여러 확률제어 방법들을 논의한다. 4절에서는 이 방법을 항공, 건축제어, 경제 분야 등에 응용한 예를 들어 본다. 마지막으로 결론과 앞으로의 연구 방향을 제시해 보고자 한다.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.342-342
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• 2004

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.3-6
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• 2007

사람들이 어떠한 행동을 할 때는 특정 의도를 가지고 있기 때문에 상황에 맞는 적합한 서비스를 제공하기 위해서는 사용자가 현재 하고 있는 행동에 대한 의도를 파악해야한다. 이를 위해 의도와 행동사이의 연관성을 이용하여 사용자의 의도에 따른 행동의 모델을 만든다. 일상생활에서 사람들이 하는 행동은 작은 단위 행동들의 연속(sequence)으로 이루어지므로, 사용자의 단위행동의 순서를 분석한다면 의도에 따른 행동 모델을 만들기가 용이해진다. 하지만, 이런 단위 행동 분석 방법의 문제점은 같은 의도를 가진 행동이 완벽하게 동일한 단위 행동의 순서로 일어나지는 않는다는 점이다. 시스템은 동일한 동작 순서로 일어나지 않는 행동들을 서로 다른 의도를 가진 행동으로 이해하게 된다. 따라서 이 문제점을 해결할 수 있는 사용자 의도 파악 기법이 필요하다. 본 논문에서는 과거의 사용자의 행동 정보를 기반으로 행동들의 유사성을 판별하였고, 그 결과를 이용하여 행동의 의도를 파악하는 방법을 사용한다. 이를 위해, 과거 사용자가 한 행동들을 단위 시간 별로 나누어 단위 행동의 순서로 만들고, 이를 K-평균 군집화 방법(K-means)으로 군집들의 순서로 나타내었다. 이 변경된 사용자 행동 정보를 사용하여 은닉 마코프 모델을 학습 시키고, 이렇게 만들어진 은닉 마코프 모델은 현재 사용자가 행한 행동이 어떤 행동인지를 예측하여 사용자의 의도를 파악한다.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.315-328
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• 2004

Recent increase of green house gases may increase the frequency of meteorological extremes. In this study, using the index and meteorological data generated by the Markov chain model under the condition of GCM predictions, the possible width of variability of flood and drought occurrences were predicted. As results, we could find that the frequency of both floods and droughts would be increased to make the water resources planning and management more difficult. Thus, it is recommended to include the effect of climate change on water resources in the related policy making.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.459-464
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• 2001

This paper discusses a stochastic stabilization of Takagi-Sugeno(TS) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delary of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time TS fuzzy system with the Markovian input delay is discretized for easy handling delay, according, the discretized TS fuzzy system is represented by a discrete-time TS fuzzy system with jumping parameters. The stochastic stabilizibility of the jump TS fuzzy system is derived and formulated in terms of linear matrix inequalities (LNIS)

• Journal of KIISE:Information Networking
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• v.31 no.1
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• pp.112-122
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• 2004

In this paper, we propose a mobility estimation model based on inner regions in a cell and a dynamic resource reservation scheme which can control dynamically classes of mobile hosts on the mobile network. The mobility estimation model is modeled based on the reducible Markov chain. And the mobility estimation model provides a new hand off probability and a new remaining time for the dynamic resource reservation scheme. The remaining time is n estimated time that mobile hosts can stay in a cell. The dynamic resource reservation scheme can reserve dynamically a requested resource according to the classes of mobile hosts. This scheme can efficiently improve the connection blocking probability and connection dropping probability.