Forecast of civil aviation freight volume using unbiased grey-fuzzy-Markov chain method

To fulfill the prospective student's information need about student admission, Gunadarma University has already many kinds of services which are time limited, such as website, book, registration place, Media Information Center, and Question Answering’s website (UG-Pedia). It needs a service that can serve them anytime and anywhere. Therefore, this research is developing the UGLeo as a web based QA intelligence chatbot application for Gunadarma University's student admission portal. UGLeo is developed by MegaHal style which implements the Markov Chain method. In this research, there are some modifications in MegaHal style, those modifications are the structure of natural language processing and the structure of database. The accuracy of UGLeo reply is 65%. However, to increase the accuracy there are some improvements to be applied in UGLeo system, both improvement in natural language processing and improvement in MegaHal style.

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A Markov Chain Method to Estimate the Tumour Progression Rate from Preclinical to Clinical Phase, Sensitivity and Positive Predictive Value for Mammography in Breast Cancer Screening

Journal of the Royal Statistical Society Series D (The Statistician) ◽

10.2307/2988469 ◽

1996 ◽

Vol 45 (3) ◽

pp. 307 ◽

Cited By ~ 51

Author(s):

H. H. Chen ◽

S. W. Duffy ◽

Laszlo Tabar

Keyword(s):

Breast Cancer ◽

Markov Chain ◽

Cancer Screening ◽

Positive Predictive Value ◽

Predictive Value ◽

Tumour Progression ◽

Progression Rate ◽

Phase Sensitivity ◽

Clinical Phase ◽

Markov Chain Method

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Estimation of Atmospheric Emissions by an Adaptive Monte Carlo Markov Chain Method

10.26678/abcm.cobem2021.cob2021-0623 ◽

2021 ◽

Author(s):

Roseane Albani ◽

Vinicius Albani ◽

Helio Migon ◽

Antônio Silva Neto

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Monte Carlo Markov Chain ◽

Atmospheric Emissions ◽

Adaptive Monte Carlo ◽

Markov Chain Method

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On the Markov Chain Simulation Method for Uniform Combinatorial Distributions and Simulated Annealing

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964800000267 ◽

1987 ◽

Vol 1 (1) ◽

pp. 33-46 ◽

Cited By ~ 58

Author(s):

David Aldous

Keyword(s):

Markov Chain ◽

Simulated Annealing ◽

Simulated Annealing Algorithm ◽

Simulation Method ◽

Careful Analysis ◽

Eigenvalue Estimate ◽

Uniform Distributions ◽

Markov Chain Method ◽

Annealing Algorithm ◽

Second Largest Eigenvalue

Uniform distributions on complicated combinatorial sets can be simulated by the Markov chain method. A condition is given for the simulations to be accurate in polynomial time. Similar analysis of the simulated annealing algorithm remains an open problem. The argument relies on a recent eigenvalue estimate of Alon [4]; the only new mathematical ingredient is a careful analysis of how the accuracy of sample averages of a Markov chain is related to the second-largest eigenvalue.

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