• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.182-182
• /
• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• Ocean and Polar Research
• /
• 제36권4호
• /
• pp.487-494
• /
• 2014

Deep-seabed test miner operated by a self-propelled mining system moving on soft soil is an essential device to secure floating and towing performances. The performances of the tracked vehicle are seriously influenced by noise factors such as the shear strength of the seafloor, bottom current, seafloor slope, speed of tracked vehicle, reaction forces of flexible hose, steering ratio, etc. Due to uncertainties related to noise factors, the design of a deep-sea manganese nodules test miner that satisfies target reliabilities is difficult. Therefore, reliability-based design optimization (RBDO) is required to guarantee system reliability under circumstances where uncertainties related to noise factors prevail. Among noise factors, the bottom current, a bimodal distribution, is censored due to the observation limit of measurement devices. Therefore, estimated distribution of the bottom current is inaccurate without considering these characteristics and the result of RBDO cannot be guaranteed. In this paper, we define censored data as unknown values over the limit of observation. If this data is estimated by using Akaike information criterion (AIC) that cannot consider the characteristics of censored data, the distribution of estimated data cannot guarantee accurate reliability. Therefore, censored AIC that can consider the characteristics of data is used to estimate accurate distribution of the bottom current. Finally, RBDO, under circumstances where uncertainties related to noise factors combined censored data are present, is performed on the mobility of a deep-sea manganese nodules test miner.

• 한국산림과학회지
• /
• 제104권1호
• /
• pp.111-116
• /
• 2015

본 연구의 목적은 임의효과(random effect)를 포함하는 혼합모형(mixed model)을 이용하여 흉고직경과 수고의 변화량을 평가하는데 있다. 강원도 굴참나무 임분을 대상으로 흉고직경과 수고를 조사하고 3년 후 동일 임분을 재조사하였다. 혼합모형에서 굴참나무의 흉고직경-수고 관계는 고정효과(fixed effect)이고 초기측정과 반복측정의 흉고직경과 수고 차이를 임의효과로 설정하였다. 임의효과에 따른 모형의 적합도를 검정하기 위하여 아카이케의 정보기준(akaike information criterion, AIC)을 참고하고 반복 측정에 따른 분산-공분산 행렬과 오차항을 산정하였다. 추정된 공분산은 -0.0291이고 오차항은 0.1007을 나타내었다. 분산-공분산 행렬을 이용한 임의효과가 포함된 모형의 AIC(=-215.5)는 고정효과를 고려한 모형의 AIC(=-154.4)에 비해 낮은 수치를 나타내었다. 이러한 결과는 범주형 자료의 임의효과가 모형 개발에 반영되는 결과인 것으로 조사되었다. 그러므로, 본 연구에서 적용된 혼합모형은 반복 측정 자료를 이용한 모형 개발에 활용이 가능한 것으로 판단된다.

• 터널과지하공간
• /
• 제29권4호
• /
• pp.243-261
• /
• 2019

미소진동기술을 활용한 계측 및 안전관리는 전통적인 방법에 비해 우수성이 인정되어 국내외 광산 등에서 활용되고 있다. 그러나 국내 지하광산의 비정형화와 채굴적과 암반 등이 혼재한 복잡한 구조는 미소 진동 전파속도 산정과 미소진동 신호의 초동발췌를 어렵게 한다. 본 연구에서는 여러 초동발췌방법과 차원에 따른 음원위치의 결정에 대해 실험적 연구를 수행하였다. 초동발췌방법은 FTC(First Threshold Cross), Picking window, AIC(Akaike Information Criterion)을 사용하였으며, 2차원 센서 배열일 때 2차원과 3차원 음원발생 실험을 수행하였다. 각 실험에서 음원위치결정 알고리즘은 반복법과 유전자 알고리즘을 사용하였다. 반복법은 센서 배열과 음원발생이 동차원인 경우 효과적이나 음원발생이 상위차원인 경우에는 적합하지 않았다. 반면, RCGA를 이용한 음원위치결정의 경우 상위차원 음원위치를 결정할 수 있었으나 계산속도가 다소 느렸다. 초동발췌방법의 정확도는 음원위치결정 방법에 따라 다르게 나타났으나, Picking window가 전반적으로 높은 정확도를 나타냈다.

• Asian-Australasian Journal of Animal Sciences
• /
• 제33권3호
• /
• pp.408-415
• /
• 2020

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas. Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit. Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values. Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

• Journal of Forest and Environmental Science
• /
• 제34권2호
• /
• pp.119-125
• /
• 2018

The tropical forests in developing countries are faced with the problem of illegal exploitation of trees. However, dearth of empirical means of expressing the dimensions, structure, quality and quantity of a removed tree has imped conviction of offenders. This study aimed at developing a model that can effectively estimate individual tree basal area (BA) from stump diameter (Ds) for Tectona grandis stands in Omo Forest Reserve, Nigeria, for timber valuation in case of illegal felling. Thirty-six $25m{\times}25m$ temporary sample plots (TSPs) were laid randomly in six age strata; 26, 23, 22, 16, 14, and 12 years specifically. BA, Ds and diameter at breast height were measured in all living T. grandis trees within the 36 TSPs. Least square method was used to convert the counted stumps into harvested stem cross-sectional areas. Six basal area models were fitted and evaluated. The BA-Ds relationship was best described by power model which gave least values of Root mean square error (0.0048), prediction error sum of squares (0.0325) and Akaike information criterion (-15391) with a high adjusted coefficient of determination (0.921). This study revealed that basal area estimation was realistic even when the only information available was stump diameter. The power model was validated using independent data obtained from additional plots and was found to be appropriate for estimating the basal area of Tectona grandis stands in Omo Forest Reserve, Nigeria.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제23권1호
• /
• pp.41-53
• /
• 2018

Comprehensive statistical analysis for the 127 groundwater monitoring stations in Jeju Island during 2005~2015 was carried out for the re-establishment of management groundwater level. Three probability distribution functions such as normal distibution, GEV (General Extreme Value) distribution, and Gumbel distribution were applied and the maximum likelihood method was used for parameter estimation of each distribution. AIC (Akaike information criterion) was calculated based on the estimated parameters to determine the proper probability distribution for all 127 stations. The results showed that normal distribution and Gumble distribution were found in 11 stations. Whereas GEV distribution were found in 105 stations, which covered most of groundwater monitoring stations. Therefore, confidence levels should be established in accord with the proper probability distribution when groundwater level management is determined.

• 한국주거학회논문집
• /
• 제25권4호
• /
• pp.59-72
• /
• 2014

This study proposes a data-mining analysis method for examining variable multi-attribute big-data, which is considered to be more applicable in social science using a Correspondence Analysis of variables obtained by AIC model selection. The proposed method was applied on the Seoul Survey from 2005 to 2010 in order to extract interesting rules or patterns on characteristics of single household. The results found as follows. Firstly, this paper illustrated that the proposed method is efficiently able to apply on a big dataset of huge categorical multi attributes variables. Secondly, as a result of Seoul Survey analysis, it has been found that the more dissatisfied with residential environment the higher tendency of residential mobility in single household. Thirdly, it turned out that there are three types of single households based on the characteristics of their demographic characteristics, and it was different from recognition of home and partner of counselling by the three types of single households. Fourthly, this paper extracted eight significant variables with a spatial aggregated dataset which are highly correlated to the ratio of occupancy of single household in 25 Seoul Municipals, and to conclude, it investigated the relation between spatial distribution of single households and their demographic statistics based on the six divided groups obtained by Cluster Analysis.

• Asian-Australasian Journal of Animal Sciences
• /
• 제29권6호
• /
• pp.759-767
• /
• 2016

The aim of this study was to compare two random regression models (RRM) fitted by fourth ($RRM_4$) and fifth-order Legendre polynomials ($RRM_5$) with a lactation model (LM) for evaluating Holstein cattle in Brazil. Two datasets with the same animals were prepared for this study. To apply test-day RRM and LMs, 262,426 test day records and 30,228 lactation records covering 305 days were prepared, respectively. The lowest values of Akaike's information criterion, Bayesian information criterion, and estimates of the maximum of the likelihood function (-2LogL) were for $RRM_4$. Heritability for 305-day milk yield (305MY) was 0.23 ($RRM_4$), 0.24 ($RRM_5$), and 0.21 (LM). Heritability, additive genetic and permanent environmental variances of test days on days in milk was from 0.16 to 0.27, from 3.76 to 6.88 and from 11.12 to 20.21, respectively. Additive genetic correlations between test days ranged from 0.20 to 0.99. Permanent environmental correlations between test days were between 0.07 and 0.99. Standard deviations of average estimated breeding values (EBVs) for 305MY from $RRM_4$ and $RRM_5$ were from 11% to 30% higher for bulls and around 28% higher for cows than that in LM. Rank correlations between RRM EBVs and LM EBVs were between 0.86 to 0.96 for bulls and 0.80 to 0.87 for cows. Average percentage of gain in reliability of EBVs for 305-day yield increased from 4% to 17% for bulls and from 23% to 24% for cows when reliability of EBVs from RRM models was compared to those from LM model. Random regression model fitted by fourth order Legendre polynomials is recommended for genetic evaluations of Brazilian Holstein cattle because of the higher reliability in the estimation of breeding values.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권5호
• /
• pp.533-542
• /
• 2021

The main objective of this article is to investigate the existence of the lunar effect during the full moon period (FM period) and the new moon period (NM period) on the selected Islamic stock market returns and volatilities. For this purpose, the Ordinary Least Squares model, Autoregressive Conditional Heteroscedasticity model, Generalised Autoregressive Conditional Heteroscedasticity model and Generalised Autoregressive Conditional Heteroscedasticity-in-Mean model are employed using the mean daily returns data between January 2010 and December 2019. Next, the log-likelihood, Akaike Information Criterion and Schwarz Information Criterion value are analyzed to determine the best models for explaining the returns and volatility of returns. The empirical results have deduced that, during the NM period, excluding Malaysia, the total mean daily returns for all of the selected countries have increased mean daily returns in contrast to the mean daily returns during the FM period. The volatility shocks are intense and conditional volatility is persistent in all countries. Subsequently, the volatility behavior tends to have lower volatility during the FM period and NM period in the Islamic stock market, except Malaysia. This article also concluded that the ARCH (1) model is the preferred model for stock returns whereas GARCH-M (1, 1) is preferred for the volatility of returns.