• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.130-141
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• 2017

Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.169-183
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• 2009

The purpose of this research, based on the Media Selection Theory, the Technology Acceptance Model, and the Social Influence Theory, is to investigate the influential factors that affect media selection in banking transactions. Analyses showed that for location sensitive bank windows and ATMs(automatic teller machines), defined as offline-based transaction channels, convenience was the variable affecting media selection. However, in the case of online media not related to location, (phone banking, internet banking, and mobile banking) reliability was the significant variable influencing use. The findings show that banking organizations may benefit from identifying traits of media affecting use, and should differentiate customer services for competitive advantage.

• Earthquakes and Structures
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• v.14 no.2
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• pp.143-153
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• 2018

Correlation among different factors must be considered for selection of influencing factors in safety monitoring of high dam including positive correlation of variables. Therefore, a new factor selection method was constructed based on Copula entropy and mutual information theory, which was deduced and optimized. Considering the small sample size in high dam monitoring and distribution of daily monitoring samples, a computing method that avoids causality of structure as much as possible is needed. The two-dimensional normal information diffusion and fuzzy reasoning of pattern recognition field are based on the weight theory, which avoids complicated causes of the studying structure. Hence, it is used to dam safety monitoring field and simplified, which increases sample information appropriately. Next, a complete system integrating high dam monitoring and uncertainty prediction method was established by combining Copula entropy theory and information diffusion theory. Finally, the proposed method was applied in seepage monitoring of Nuozhadu clay core-wall rockfill dam. Its selection of influencing factors and processing of sample data were compared with different models. Results demonstrated that the proposed method increases the prediction accuracy to some extent.

• The Journal of Korean Academy of Prosthodontics
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• v.34 no.3
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• pp.457-463
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• 1996

An esthetically pleasing result in denture service is dependent upon several consideration. Esthetic considerations for the edentulous patient include tooth size, shape, arrangement, positioning, gingival contour, age, sex, personality differences, and ethnic type. Especially, the form of anterior artificial teeth is an important factor on the esthetics. The selection of artificaial teeth requires understanding and knowledge on physical and biologic factors and has to meet the indivisul esthetics and functional needs of each patient. However, the selection of artificial teeth is based on the large degree of subjective judgement of the dentist, Therefore, this is one of the most unscientific processes. Many attempts have been made to find a guideline for the selection of artificial teeth. Temperamental theory by White and Hall utillized with the physical characteristics such as body size, body form, color of eyes and hair, and disposition. SPA theory by Frush and Fisher utilized with the basis of sex, personalities, and age of the indivisual. There has not been provided for a guideline and study on the selection of artificial teeth for Koreans yet. This study was aimed to evaluate the William's typal matching theory in Koreans. 1. The facial forms of korean adult were ovoid(46.3%), square(36.7%) and tapered(17.0%) form. 2. The anatomic forms of natural maxillary incisors were ovoid(45.3%), tapered(31.3%), square(23.3%) form. 3. The forms of face and natural maxillary incisors were ovoid(21.9%), squared(11%), tapered(6.3%). 4. The natural maxillary incisors were similar in form to the facial form only in 39%. There was no correlation between the form of the face and the form of natural maxillary central inisors in Koreans. 5. Artificaial teeth which was selected according to the typal matching theory did not represent the form of the natural teeth in 61 per cents of the fatal, but it felt that they harmonized with the form of the patient's face and produced good results.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.223-229
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• 2014

In an attempt to retrieve useful information for an efficient decision in the large knowledge system, it is generally necessary and important for a refined feature selection. Rough set has difficulty in generating optimal reducts and classifying boundary objects. In this paper, we propose quick reduction algorithm generating optimal features by rough entropy analysis for condition and decision attributes to improve these restrictions. We define a new conditional information entropy for efficient feature extraction and describe procedure of feature selection to classify the significance of features. Through the simulation of 5 datasets from UCI storage, we compare our feature selection approach based on rough set theory with the other selection theories. As the result, our modeling method is more efficient than the previous theories in classification accuracy for feature selection.

• Honam Mathematical Journal
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• v.19 no.1
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• pp.125-130
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• 1997

In this paper, we give a characterization of collectionwise normality using continuous functions. More precisely, we give a new and short proof of the Dowker's theorem using selection theory that a $T_1$ space X is collectionwise normal if every continuous mapping of every closed subset F of X into a Banach space can be continuously extended over X. This is also a generalization of Tietze's extension theorem.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.135-145
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• 1998

There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.16-25
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• 1998

In this paper, we propose features extraction method using Rough sets theory for efficient data classifications in hyperspectral environment. First, analyze the properties of multispectral image data, then select the most efficient bands using discemibility of Rough sets theory based on analysis results. The proposed method is applied Landsat TM image data, from this, we verify the equivalence of traditional bands selection method by band features and bands selection method using Rough sets theory that pmposed in this paper. Finally, we present theoretical basis to features extraction in hyperspectral environment.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.123-137
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• 1995

Most of solution methods in scheduling attempt to generate good solutions by either developing algorithms or heuristic rules. However, scheduling problems in the real world require considering more factors such as multiple objectives, different combinations of heuristic rules due to problem characteristics. In this respect, the traditional mathematical a, pp.oach showed limited performance so that new a, pp.oaches need to be developed. Expert system is one of them. When an expert system is developed for scheduling one of the most difficult processes faced could be knowledge acquisition on scheduling heuristics. In this paper we propose a method for the acquisition of knowledge on the selection of scheduling heuristics using Dempster-Shafer Theory(DST). We also show the examples in the multi-objectives environment.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.3
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• pp.299-303
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• 2012

Inbreeding is the mating of relatives that produce progeny having more homozygous alleles than non-inbred animals. Inbreeding increases numbers of recessive alleles, which is often associated with decreased performance known as inbreeding depression. The magnitude of inbreeding depression depends on the level of inbreeding in the animal. Level of inbreeding is expressed by the inbreeding coefficient. One breeding goal in livestock is uniform productivity while maintaining acceptable inbreeding levels, especially keeping inbreeding less than 20%. However, in closed herds without the introduction of new genetic sources high levels of inbreeding over time are unavoidable. One method that increases selection response and minimizes inbreeding is selection of individuals by weighting estimated breeding values with average relationships among individuals. Optimum genetic contribution theory (OGC) uses relationships among individuals as weighting factors. The algorithm is as follows: i) Identify the individual having the best EBV; ii) Calculate average relationships ($\bar{r_j}$) between selected and candidates; iii) Select the individual having the best EBV adjusted for average relationships using the weighting factor k, $EBV^*=EBV_j(1-k\bar{{r}_j})$ Repeat process until the number of individuals selected equals number required. The objective of this study was to compare simulated results based on OGC selection under different conditions over 30 generations. Individuals (n = 110) were generated for the base population with pseudo random numbers of N~ (0, 3), ten were assumed male, and the remainder female. Each male was mated to ten females, and every female was assumed to have 5 progeny resulting in 500 individuals in the following generation. Results showed the OGC algorithm effectively controlled inbreeding and maintained consistent increases in selection response. Difference in breeding values between selection with OGC algorithm and by EBV only was 8%, however, rate of inbreeding was controlled by 47% after 20 generation. These results indicate that the OGC algorithm can be used effectively in long-term selection programs.