Using fuzzy time series with and without markov chain: to forecast of edible bird nest exported from Indonesia

Edible bird nest (EBN) were traditional medicine consumed by the Tiongkok. This study compared two-algorithm method. Fuzzy time series and Markov chain as forecast method the number of bird nest exported from Indonesia. The secondary data between 2012 and 2018 were from Bureau Central Statistic (BPS). The scope using in this study were bird nest between 2012 until 2018, with a unit of volume kilograms (Kg). Used secondary export data, collected from BPS of Indonesia. Data were analysed using Fuzzy Time Series with and without Markov Chain using R Studio. The result showed that Fuzzy Time Series with and without Markov Chain method performs better in the forecasting ability in short-term period prediction and the values of Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) tends to be smaller than the Fuzzy Time Series without Markov Chain. It can be concluded the number of exported can be used Fuzzy time series.

Application of Game Theory and Markov Chains on English Premier League (EPL) Scorelines Analysis

The aim of this paper is to obtain the optimal strategies of two competitive players using Game Theorem and to make future predictions of games using Markov Chains involving the EPL. All the teams that have participated since 2005/2006 EPL season to EPL 2019/2020 season were considered and the method of proportion of wins was used to select five best teams. Linear programming was employed to select the optimal strategies, while the predictions for seasons 2020/2021 to 2023/2024 are obtained by Markov chain method. The results obtained revealed that Man U is the optimal strategy for Player A, and that Player A has to choose Man U to maximize his profit, meanwhile, Chelsea is the optimal strategy for Player B and he has to choose Chelsea to minimize his loss. The findings of the results also revealed that for Man U or Chelsea to win their home games, it will depend on their current home winning against the team they are playing with.

Gaussian Process based Remaining useful life Prediction for Electric Energy Metering Equipment

Electric energy metering equipment (EEME) will fail in advance not as designed running in extreme environments. A multi-kernel Gaussian process regression model using measurement error data to perceive remaining useful life (RUL) for EEME is proposed. Firstly, the gauss kernel and periodic kernel are used to match the health index trend of EEME under a variety of typical environmental stresses. Furthermore, the Bayesian method and Monte Carlo Markov chain method are used to solve the model, and the Weibull distribution is used to fit the posterior trajectory to get the probability density estimation of the RUL.

Implementation of Markov Chain in Detecting Opportunities for Natural Disasters in Klaten (Case Study: Number of Floods, Landslides, and Hurricanes 2019-2020)

Java Island is one of the areas that is very fertile and densely populated, but on the other hand, Java Island is also one of the areas that is most frequently hit by natural disasters, one of which is Klaten Regency. Natural disaster itself is an event that threatens and disrupts human life caused by nature. Some of the natural disasters that often occur simultaneously in Klaten Regency are floods, landslides, and hurricanes. These three disasters usually occur during the rainy season. This of course makes the government need to take action by seeing the large chance of a disaster occurring in order to optimize disaster management. Then research will be carried out that aims to determine the chances of natural disasters occurring in the next few years. Forecasting will be carried out using the Markov chain method, with this method the probability value of the future period can be estimated using the current period probability value based on the characteristics of the past period. So that the value of the steady state chance of floods and landslides in period 36 (December 2023) and hurricanes in period 15 (March 2022) with the chances of a disaster are 34.21%, 15.38%, and 73.53%, respectively.Received August 31, 2021Revised October 27, 2021Accepted November 11, 2021

The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution

The distribution of fitness effects (DFE) for new mutations is fundamental for many aspects of population and quantitative genetics. In this study, we have inferred the DFE in the single-celled alga Chlamydomonas reinhardtii by estimating changes in the frequencies of 254 spontaneous mutations under experimental evolution and equating the frequency changes of linked mutations with their selection coefficients. We generated seven populations of recombinant haplotypes by crossing seven independently derived mutation accumulation lines carrying an average of 36 mutations in the homozygous state to a mutation-free strain of the same genotype. We then allowed the populations to evolve under natural selection in the laboratory by serial transfer in liquid culture. We observed substantial and repeatable changes in the frequencies of many groups of linked mutations, and, surprisingly, as many mutations were observed to increase as decrease in frequency. We developed a Bayesian Monte Carlo Markov Chain method to infer the DFE. This computes the likelihood of the observed distribution of changes of frequency, and obtains the posterior distribution of the selective effects of individual mutations, while assuming a two-sided gamma distribution of effects. We infer that the DFE is a highly leptokurtic distribution, and that approximately equal proportions of mutations have positive and negative effects on fitness. This result is consistent with what we have observed in previous work on a different C. reinhardtii strain, and suggests that a high fraction of new spontaneously arisen mutations are advantageous in a simple laboratory environment.

COMPLEX ASSOCIATION ANALYSIS OF ANTIOXIDANT GENES POLYMORPHIC DNA-MARKERS WITH AGE IN THE ETHNIC GROUP OF ABKHAZIANS

Впервые в этнической группе абхазов выполнен анализ ассоциаций полиморфных ДНК-маркеров генов антиоксидантной системы CAT (rs1001179), MSRA (rs10098474), GPX1 (rs1050450), GSR (rs1002149), GSTP1 (rs1695), SOD1 (rs2070424), SOD2 (rs4880), PON1 (rs662), PON2 (rs7493) с возрастом. С использованием ROC-анализа и логистической регрессии установлено, что спектр частот аллелей и генотипов полиморфных маркеров генов PON1 и GSTP1 меняется на протяжении всего исследуемого возрастного периода (21 107 лет); распределение частот аллелей и генотипов по полиморфным маркерам генов CAT и SOD2 изменяется на рубеже 60 лет. Методом Монте-Карло марковскими цепями определены мультилокусные генетические маркеры долголетия. У лиц 60-107 лет статистически значимо повышена частота встречаемости паттернов GSTP 1* G/G + PON 1* G ( OR =6,59, PFDR =0,018) и GSTP 1* G/G + SOD 1 *A ( OR =3,4, PFDR =0,041); аллель GSTP 1* A в разных комбинациях с аллелями PON 1*A, PON2 * C и CAT * C встре чается реже (OR=0,3, PFDR<0,05). For the first time in the ethnic group of Abkhazians, the association analysis of polymorphic DNA-markers of the antioxidant genes CAT ( rs 1001179), MSRA ( rs 10098474), GPX 1 ( rs 1050450), GSR ( rs 1002149), GSTP 1 ( rs 1695), SOD 1 ( rs 2070424), SOD 2 ( rs 4880) , PON 1 ( rs 662), PON 2 ( rs 7493) with age was performed. Using ROC-analysis and logistic regression, it was found that the spectrum of alleles and genotypes frequencies of PON 1 and GSTP 1 genes polymorphic markers change throughout the studied age period (21-107 years old); the distribution of allele and genotype frequencies of CAT and SOD 2 genes polymorphic markers changes within the age of 60 years. Multilocus genetic markers of longevity were determined by the Monte Carlo Markov chain method. Among persons in the age range 60-107 years, the frequency of observation of the patterns GSTP 1* G/G + PON 1* G ( OR =6,59, P FDR=0,018) and GSTP 1* G/G + SOD 1 *A ( OR =3,4, P FDR=0,041) is statistically significantly increased; the GSTP 1* A allele in various combinations with the PON 1* A , PON 2* C and CAT * C alleles are less common ( OR =0,3, P FDR<0,05).

Half-Graphs, Other Non-stable Degree Sequences, and the Switch Markov Chain

One of the simplest methods of generating a random graph with a given degree sequence is provided by the Monte Carlo Markov Chain method using switches. The switch Markov chain converges to the uniform distribution, but generally the rate of convergence is not known. After a number of results concerning various degree sequences, rapid mixing was established for so-called P-stable degree sequences (including that of directed graphs), which covers every previously known rapidly mixing region of degree sequences. In this paper we give a non-trivial family of degree sequences that are not P-stable and the switch Markov chain is still rapidly mixing on them. This family has an intimate connection to Tyshkevich-decompositions and strong stability as well.

Machine Maintenance Design using Markov Chain Method to Reduce Maintenance Costs

PT. XYZ is a company that focuses on construction with ready mix concrete product (cast). The problem faced by the company is that the schedule is not suitable for machine maintenance activities so that it still results in high maintenance costs incurred by the company. By using the markov chain method can plan maintenance time in order to reduce downtime so as to minimize maintenance costs. The results obtained by the proposal for the company are for proposal I it takes 49.78 hours = 50 hours at a cost of Rp. 16,984,605, the cost savings of Rp. 73,545,395 (81.24%). Schedule for each machine such as wheel loaders every 14,009 hours, batching plant machines every 16,604 hours, truck mixer machines every 19,168 hours. Scheduling the second proposal will take 26.62 hours = 27 hours at a cost of Rp. 9,080,664, the cost savings of Rp. 81,449,336 (89.97%). Schedule for every machine such as wheel loaders every 7,490 hours, batching plant machines every 8,877 hours, mixer truck machines every 10,248 hours. Judging from the results obtained, the recommendation given is