• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.4
• /
• pp.692-700
• /
• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• Structural Engineering and Mechanics
• /
• v.33 no.4
• /
• pp.539-542
• /
• 2009

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.7
• /
• pp.921-927
• /
• 2013

The performance estimation of a landing gear with uncertain parameters is presented. In actual use, many parameters can have certain degrees of variations that affect the energy absorbing performance. For example, the shock strut gas pressure, oil volume, tire pressure, and temperature can deviate from their nominal values. The objective function in this study is the ground reaction during touchdown, which is a function of the abovementioned parameters and time. To consider the uncertain properties, convex modeling and interval analysis are used to calculatethe objective function. The numerical results show that the ground reaction characteristics are quite different from those of the deterministic method. The peak load, which affects the efficiency and structural integrity, is increases considerably when the uncertainties are considered. Therefore, it is important to consider the uncertainties, and the proposed methodology can serve as an efficient method to estimate the effect of such uncertainties.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.127-127
• /
• 2021

In order to estimate parameter uncertainty of hydrological models, the consideration of the likelihood functions which provide reliable parameters of model is necessary. In this study, the Bayesian Markov Chain Monte Carlo (MCMC) method with informal likelihood functions is used to analyze the uncertainty of parameters of the SURR model for estimating the hourly streamflow of Gunnam station of Imjin basin, Korea. Three events were used to calibrate and one event was used to validate the posterior distributions of parameters. Moreover, the performance of four informal likelihood functions (Nash-Sutcliffe efficiency, Normalized absolute error, Index of agreement, and Chiew-McMahon efficiency) on uncertainty of parameter is assessed. The indicators used to assess the uncertainty of the streamflow simulation were P-factor (percentage of observed streamflow included in the uncertainty interval) and R-factor (the average width of the uncertainty interval). The results showed that the sensitivities of parameters strongly depend on the likelihood functions and vary for different likelihood functions. The uncertainty bounds illustrated the slight differences from various likelihood functions. This study confirms the importance of the likelihood function selection in the application of Bayesian MCMC to the uncertainty assessment of the SURR model.

• Journal of Korean Society for Quality Management
• /
• v.32 no.1
• /
• pp.92-101
• /
• 2004

Tris paper present an economic statistical design which have statistically constraints for the optimal design of an EWMA control charts with variable sampling interval. Cost function use that proposed by Lorenzen and Vance, and the optimal design parameters include the sample size, control limit width, sampling interval, EWMA weight value. Comparisons between VSI EWMA control charts optimal economic design and optimal economic statistical designs show the following fact. Although have demerits which are more costly than economic design, have merits which to detect shifts more efficiently and to improve statistical performance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4573-4584
• /
• 2015

The traditional feature extraction algorithms for recognition of communication signals can hardly realize the balance between computational complexity and signals' interclass gathered degrees. They can hardly achieve high recognition rate at low SNR conditions. To solve this problem, a novel feature extraction algorithm based on Holder coefficient was proposed, which has the advantages of low computational complexity and good interclass gathered degree even at low SNR conditions. In this research, the selection methods of parameters and distribution properties of the extracted features regarding Holder coefficient theory were firstly explored, and then interval gray relation algorithm with improved adaptive weight was adopted to verify the effectiveness of the extracted features. Compared with traditional algorithms, the proposed algorithm can more accurately recognize signals at low SNR conditions. Simulation results show that Holder coefficient based features are stable and have good interclass gathered degree, and interval gray relation classifier with adaptive weight can achieve the recognition rate up to 87% even at the SNR of -5dB.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.5
• /
• pp.705-711
• /
• 2013

In this paper, we introduce an design of multi-output fuzzy neural networks based on Interval Type-2 fuzzy set. The proposed Interval Type-2 fuzzy set-based fuzzy neural networks with multi-output (IT2FS-based FNNm) comprise the network structure generated by dividing the input space individually. The premise part of the fuzzy rules of the network reflects the individuality of the division space for the entire input space and the consequent part of the fuzzy rules expresses three types of polynomial functions with interval sets such as constant, linear, and modified quadratic inference for pattern recognition. The learning of fuzzy neural networks is realized by adjusting connections of the neurons in the consequent part of the fuzzy rules, and it follows a back-propagation algorithm. In addition, in order to optimize the network, the parameters of the network such as apexes of membership functions, uncertainty factor, learning rate and momentum coefficient were automatically optimized by using real-coded genetic algorithm. The proposed model is evaluated with the use of numerical experimentation.

• Asian-Australasian Journal of Animal Sciences
• /
• v.8 no.4
• /
• pp.321-323
• /
• 1995

Observations were recorded regarding various fertility parameters on 26 Jersey donor cows following superovulation under tropical conditions. These cows, in their mid-luteal phase were treated with 2,500-3,000 i.u. PMSG or 28-40 mg FSH followed by $500{\mu}g$ $PGF_{2{\alpha}}$ injection 48-60 hours later, to induce oestrus. The cows were bred artificially twelve hours following standing oestrus. Embryo collection was carried out 7 days after oestrus. $PGF_{2{\alpha}}$ was injected to each donor cow after embryo recovery to regress the corpora lutea. Fertility data($PGF_{2{\alpha}}$-Oestrus interval, services per conception, days between embryo collection and successful service and any pathololgical condition) were recorded. $PGF_{2{\alpha}}$-Oestrus interval and correlation (r) between number of corpora lutea and $PGF_{2{\alpha}}$-Oestrus interval were $30.9{\pm}6.3$ and 0.17, respectively. Of 26 treated donors, 19 conceived within a period of $91.7{\pm}18.8$ days after embryo recovery. Average services per conception were $2.3{\pm}0.3$. Only two cows developed metritis which conceived after treatment with antibiotics. These observations indicated no profound adverse effect of superovulation on subsequent reproduction of donor cows, except some effect on services per conception, under tropical conditions.

• Asian-Australasian Journal of Animal Sciences
• /
• v.16 no.8
• /
• pp.1093-1101
• /
• 2003

Reproductive data, such as numbers of days to the first estrus and A.I. service postpartum, number of days to conception, number of A.I. services required for conception, interval between the first estrus and first A.I. service and the average interval of A.I. service in Thai native-Friesian crossbred and pure Friesian dairy cows, were compiled in the National Dairy Training and Applied Research Institute in Chiang Mai, Thailand. The data were analyzed statistically and the effect of milk production on these reproductive traits was investigated. The reproductive efficiency of purebred cows was obviously inferior when compared with crossbred animals, in spite of special care being given to the purebred only in order to alleviate the effect of a tropical climate and provide better feeding. However, the regression analysis between reproductive and lactational parameters revealed a definite antagonistic effect of lactation on reproduction, especially in the purebred cows, which had a larger amount of milk production and longer lactation period. If these effects of lactation were eliminated, there would be no evident difference in reproductive efficiency between purebred and crossbred cows in the conditions of this study. Among the reproductive parameters examined, the number of days to the first estrus and interval between the first estrus and first A.I. service were less affected by breed difference and the magnitude of lactation than other reasons.

• Environmental Engineering Research
• /
• v.24 no.2
• /
• pp.298-308
• /
• 2019

This work deals with the membrane fouling mode and the unclogging in seawater ultrafiltration process. The identification of the fouling mechanism by modeling the experimental flux decline was performed using both the classical models of Hermia and the combined models of Bolton. The results show that Bolton models did not bring more precise information than the Hermia's and the flux decline can be described by one of the four Hermia's models since the backwash interval is ${\leq}60$ min. An experimental screening study has been then conducted to choose among 5 parameters (backwash interval, duration, pulses and the flow-rate or injected hypochlorite concentration) those that are the most influential on the fouling and the net water production. It has emerged that fouling is mainly affected by the backwash interval; its prolongation from 30 to 60 min engenders an increase in the reversible fouling and a decrease in the irreversible fouling. This later is also significantly reduced when the hypochlorite concentration increases from 4.5 to 10 ppm. Moreover, the net water production significantly increases with increasing the filtration duration up to 60 min and decreases with decreasing the backwash duration and backwash flow-rate from 10 to 40 s and from 15 to ${\geq}20L.min^{-1}$, respectively.