• Journal of Information Processing Systems
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• v.12 no.1
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• pp.109-128
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• 2016

This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.10-26
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• 1987

If the forecasts from different, sources are combined in some way, the resulting forecasts may be more accurate than any of the individual components. In this paper, the established procedures of combining forecasts are reviewed and the alternative procedures are suggested. By the results of empirical analysis from survey data, the method of combining forecasts using the restricted regression weights, the restricted robust regression weights, and mixed regression weights are robust. We can not find the most efficient combined forecasts in any case if we select the corresponding decision by preliminary analysis for the statistical properties of individual dorecasts, our results of combined forecast can became useful.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.645-651
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• 2021

With the advent of the Fourth Industrial Revolution, modern society uses a diverse pool of devices. In this context, there is increasing interest in removing various kinds of noise arising in data transmission. However, it is difficult to restore image that damaged by mixed noise, and a digital filter that effectively restores an image according to the characteristics of the noise is required. In this paper, we propose a digital switching filter algorithm to remove mixed noise generated during digital image transmission. The proposed algorithm switches the filtering process through noise judgment and reconstructs the image using fuzzy weights and combined weights based on the pixel values inside the mask. To evaluate the proposed algorithm, we compared it with existing filter algorithms through simulation. Filtering results were expanded and compared for visual evaluation, and PSNR comparison was used for quantitative evaluation.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.6
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• pp.877-883
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• 2006

A feeding trial was conducted on commercial broilers for a period of 35 days to determine the individual and combined effects of aflatoxin (AF) and T-2 toxin (T-2) on performance, organ weights and immune status. The efficacy of dietary glucomannan-containing yeast product (GYP) ($Mycosorb^{(R)}$) and hydrated sodium calcium aluminosilicate (HSCAS) in preventing the adverse effects of aflatoxin and T-2 toxin was also evaluated. Twelve dietary treatments ($4{\times}3$ factorial) comprising two dietary levels each of AF (0 and 2 mg/kg), T-2 toxin (0 and 1 mg/kg), GYP (0 and 1 kg/ton) and HSCAS (0 and 10 kg/ton) were tested on 720 commercial broiler chickens divided at random into 36 replicates of 20 chicks each (10 males and 10 females). Weight gain and feed intake were recorded weekly. Organ morphology and antibody titers for Newcastle disease (ND) and infectious bursal disease (IBD) were measured on the $35^{th}$ day. AF and T-2 toxin individually decreased weight gain and increased feed conversion ratio (FCR) (p<0.05). AF alone (p<0.05) increased weights of liver, kidney, gizzard and spleen and reduced thymus and bursal weights. T-2 toxin (p<0.05) increased liver and gizzard weights and decreased thymus weight. Both AF and T-2 toxin when fed individually affected ND and IBD titers in a significant manner. Significant interactions between AF and T-2 toxin were observed for their additive effects on weight gain, FCR, organ weights and antibody titers. Addition of GYP (p<0.05) improved weight gain, feed conversion efficiency and restored the organ weights. Antibody titers against ND and IBD were significantly improved with the supplementation of GYP. Supplementation of HSCAS (p<0.05) resulted in improvement in weight gain and restored organ weights in the groups fed AF alone, but not in T-2 toxin fed groups. HSCAS inclusion did not influence FCR in toxin fed groups. Addition of HSCAS (p<0.05) improved the antibody titers against ND and IBD only in AF fed groups. Thus, the results indicate that addition of GYP is effective in averting the individual and combined toxicity of aflatoxin and T-2 toxin in commercial broilers, while HSCAS is effective only against aflatoxin.

• 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.7 no.3
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• pp.441-448
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• 1994

Postweaning performance data were obtained on 187 group fed purebred Angus calves from 12 selected sires (six high and six low feed conversion sires) in 1985 and 1986. The objective of this portion of the study was to develop prediction equations for feed conversion from a stepwise regression analysis. Variables measured were on-test weight (ONTSTWT), on-test age (ONTSTAG), five weights by 28-d periods, seven linear body measurements: heart girth (HG), hip height (HH), head width (HDW), head length (HDL), muzzle circumference (MC), length between hooks and pins (HOPIN) and length between shoulder and hooks (SHHO), and backfat thickness (BF). Stepwise regressions for maintenance adjusted feed conversion (ADJFC) and unadjusted feed conversion (UNADFC) over the first 140 d of the test, and total feed conversion (FC) until progeny reached 8.89 mm of back fat were obtained separately by conversion groups and sexes and for combined feed conversion groups and sexes. In general, weights were more important than linear body measurements in prediction of feed utilization. To some extent this was expected as weight is related directly to gain which is a component of feed conversion. Weight at 112 d was the most important variable in prediction of feed conversion when data from both feed conversion groups and sexes were combined. Weights at 84 and 140 d were important variables in prediction of UNADFC and FC, respectively, of bulls. ONTSTWT and weight at 140 d had the highest standardized partial regression coefficients for UNADFC and ADJFC, respectively, of heifers. Results indicated that linear measurements, such as MC, HDL and HOPIN, are useful in prediction of feed conversion when feed in takes are unavailable.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1147-1151
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• 2009

In this study, we address the problem of producing probability forecasts of summer seasonal rainfall, on the basis of Hindcast experiments from a ensemble of GCMs(cwb, gcps, gdaps, metri, msc_gem, msc_gm2, msc_gm3, msc_sef and ncep). An advanced Hierarchical Bayesian weighting scheme is developed and used to combine nine GCMs seasonal hindcast ensembles. Hindcast period is 23 years from 1981 to 2003. The simplest approach for combining GCM forecasts is to weight each model equally, and this approach is referred to as pooled ensemble. This study proposes a more complex approach which weights the models spatially and seasonally based on past model performance for rainfall. The Bayesian approach to multi-model combination of GCMs determines the relative weights of each GCM with climatology as the prior. The weights are chosen to maximize the likelihood score of the posterior probabilities. The individual GCM ensembles, simple poolings of three and six models, and the optimally combined multimodel ensemble are compared.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.75-84
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• 1994

The uncertainty in the relative weights of a pairwise comparison matrix n Multi-attribute Decision Making (MADM) is caused by imprecise preference information of decision maker. In this paper, it is shown how weight of attributes can be derived from the pairwise comparison matrix with interval pairwise comparison. The preference information of each pair of attributes with a point pairwise comparison is combined with an interval pairwise comparison in order to estimate a point pairwise comparison for a pair of attributes with the imprecise preference information. A numerical example shows the suggested procedure for deriving weights of attributes.

• Management Science and Financial Engineering
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• v.16 no.2
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• pp.53-65
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• 2010

Despite the overall success of neighbor-based CF methods, there are some fundamental questions about neighbor selection and prediction mechanism including arbitrary similarity, over-fitting interpolation weights, no trust consideration between neighbours, etc. This paper proposes a simple method to compute absolute interpolation weights based on similarity values. In order to supplement the method, two schemes are additionally devised for high-quality neighbour selection and trust metrics based on co-ratings. The former requires that one or more neighbour's similarity should be better than a pre-specified level which is higher than the minimum level. The latter gives higher trust to neighbours that have more co-ratings. Experimental results show that the proposed method outperforms the pure IBCF by about 8% improvement. Furthermore, it can be easily combined with other predictors for achieving better prediction quality.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.381-384
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• 2003

Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve the problem, we propose the edge enhanced error diffusion using the edge information of the original images. The edge enchanted weights is computed by adding local characteristic weights and input pixels multiplied a constant. Also, we combined the edge enhanced method with the adaptive error diffusion using human spatial and frequency perception characteristic. The performance of the proposed method is compared with conventional method by measuring the edge correlation. The halftoned images applied the proposed method get more fine quality due to the enchanced edge and better quality in halftoned image. And the detailed edge is preserved in the halftoned images by the proposed method.