• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.199-207
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• 2009

In this paper, new vehicular load model is developed for reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In the previous paper, truck weight data collected at eight locations using WIM or BWIM system are analyzed to calculate the maximum truck weights for specified bridge lifetime. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I (Gumbel Distribution) and 100 years maximum weights are estimated by linear regression. In this study, effects of multiple presence of trucks are analyzed. Probability of multiple presence of trucks are estimated and corresponding multiple truck weights are calculated using the same probability distribution function as in the previous paper. New vehicular live load model are proposed for span length from 10 m to 200 m. New model is compared with current Korean model and various load models of other countries.

• The Mathematical Education
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• v.55 no.2
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• pp.147-169
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• 2016

This study analyzes the mathematical creativity test as an illustrative example with scoring domains of fluency, flexibility and originality in order to make suggestions for obtaining maximum reliability based on a composite score depending on combinations of each scoring domain weights. This is done by performing a multivariate generalizability analysis on the test scores, which were allowed to access publicly, of 30 mathematically gifted elementary school students, and therefore error variances, generalizability coefficients, and effective weights have been calculated. The main results were as follows. First, the optimal weights should adjust to .5, .4, and .1 based on the maximum generalizability coefficient even though the original weights in the mathematical creativity test were equal for each scoring domain with fluency, flexibility and originality. Second, the mathematical creativity test using the three scoring domains of fluency, flexibility, and originality showed higher reliability than using one scoring domain such as fluency. These results are limited to the mathematical creativity test used in this study. However, the methodology applied in this study can help determine the optimal weights depending on each scoring domain when the tests constructed in various researchers or educational fields are composed of multiple scoring domains.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.85-101
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• 2006

Actual type of aggregation performed by an ordered weighted averaging (OWA) operator heavily depends upon the weighting vector. A number of approaches have been suggested for obtaining the associated weights. In this paper, we present analytic forms of OWA operator weighting functions, each of which has such properties as rank-based weights and constant value of orness, irrespective of number of objectives aggregated. Specifically, we propose four analytic forms of OWA weighting functions that can be positioned at 0.25, 0.334, 0.667, and 0.75 on the orness scale. The merits for using these weights over other weighting schemes can be mentioned in a couple of ways. Firstiy, we can efficiently utilize the analytic forms of weighting functions without solving complicated mathematical programs once the degree of orness is specified a priori by decision maker. Secondly, combined with well-known OWA operator weights such as max, min, and average, any weighting vectors, having a desired value of orness and being independent of the number of objectives, can be generated. This can be accomplished by convex combinations of predetermined weighting functions having constant values of orness. Finally, in terms of a measure of dispersion, newly generated weighting vectors show just a few discrepancies with weights generated by maximum entropy OWA.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.914-918
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• 2004

The random regression model methodology was applied into the estimation of genetic parameters for body weights in Chinese Simmental cattle to replace the traditional multiple trait models. The variance components were estimated using Gibbs sampling procedure on Bayesion theory. The data were extracted for Chinese Simmental cattle born during 1980 to 2000 from 6 national breeding farms, where records from 3 months to 36 months were only used in this study. A 3 orders Legendre polynomial was defined as the submodel to describe the general law of that body weight changing with months of age in population. The heritabilities of body weights from 3 months to 36 months varied between 0.31 and 0.48, where the heritabilities from 3 months to 12 months slightly decreased with months of age but ones from 13 months to 36 months increased with months of age. Specially, the heritabilities at eighteenth and twenty-fourth month of age were 0.33 and 0.36, respectively, which were slightly greater than 0.30 and 0.31 from multiple trait models. In addition, the genetic and phenotypic correlations between body weights at different month ages were also obtained using regression model.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.327-332
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• 2010

In this paper we presents an approach to assessing the efficiency of freight railroad stations reflecting freight item importance weights with multiple performance indicators and multiple operational condition indicators. We evaluate 187 freight railroad stations using data envelopment analysis with assurance region. Each freight item's loading/unloading volume is used as a performance indicator. Freight labor and yard capacity are used as operational condition indicators. Freight item importance weights are reflected to the data envelopment analysis as assurance region. The evaluation results facilitates the organization's decision making by providing valuable information.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.3
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• pp.193-199
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• 2000

In many studies, considerable attention has been focussed upon choosing a model which represents underlying process of time series and forecasting the future. In the real world, however, there may be some cases that one model can not reflect all the characteristics of original time series. Under such circumstances, we may get better performance by combining the forecasts from several models. The most popular methods for combining forecasts involve taking a weighted average of multiple forecasts. But the weights are usually unstable. In cases the assumptions of normality and unbiasedness for forecast errors are satisfied, a Bayesian method can be used for updating the weights. In the real world, however, there are many circumstances the Bayesian method is not appropriate. This paper proposes a PNN(Probabilistic Neural Net) approach as a method for combining forecasts that can be applied when the assumption of normality or unbiasedness for forecast errors is not satisfied. In this paper, PNN method, which is similar to Bayesian approach, is suggested as an updating method of the unstable weights in the combination of the forecasts. The PNN method has been usually used in the field of pattern recognition. Unlike the Bayesian approach, it requires no assumption of a specific prior distribution because it gets probabilities by using the distribution estimated from given data. Empirical results reveal that the PNN method offers superior predictive capabilities.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.537-540
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• 1999

We propose a decision model to incorporates the values assigned by a group of experts on different factors in selecting robots. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for robot selection. A numerical example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values and eliminates the highest and lowest experts' values allocating the weights and the subjective factors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1074-1077
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• 1993

The objective of this paper is to develop a fuzzy logic based decision-making system to detect low current faults using multiple detection algorithms. This fuzzy system utilizes a fuzzy expert model which executes an operation without complicated mathematical models. This fuzzy system decides the performance weights of the detection algorithms. The weights and the turnouts of the detection algorithms discriminate faults from normal events. This system can also be a generic group decision-making tool for other areas of power system protection.

• Journal of the Korean Mathematical Society
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• v.61 no.2
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• pp.207-226
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• 2024

In this paper, the weighted L^p boundedness of multilinear commutators and multilinear iterated commutators generated by the multilinear singular integral operators with generalized kernels and BMO functions is established, where the weight is multiple weight. Our results are generalizations of the corresponding results for multilinear singular integral operators with standard kernels and Dini kernels under certain conditions.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.4
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• pp.717-722
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• 1992

An experiment was conducted to examine the feasibility of producing multiple calves using embryo transfer in Japanese Black cattle. Milk yield of cows and forage intake of calves were measured for 11 cows with single calves, 14 cows with twins and one cow with triplets. The means of 26 weeks cumulative milk yield were 854, 1028 and 1271 kg for cows having singles, twins and triplets, respectively. Male birth weights for single calves, twins and triplet were 34.9, 26.6 and 19.9 kg, and female ones were 31.7, 24.1 and 22.1 kg, respectively. Weight and daily gain of calves were affected by weeks (W), sex (S), the number of calves (N), parity, birth season, $W{\times}N$, $S{\times}N$ and regression on milk yield. Growth rate was higher for single calves than for twins until about 9 weeks of age, then weights increased at a similar rate. Male calf weaning weights for singles, twins and triplets were 207.0, 177.1 and 162.2 kg, and those for females were 185.4, 151.6 and 180.4 kg, respectively. Average regression coefficients of calf growth on milk yield were significant, and single calf was affected more than twin calves by increment of milk yield. As the number of calves per cow increased, hay intake of calves decreased and concentrate intake tended to increase between 6 and 13 weeks of age.