• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.419-422
• /
• 2003

To improve the recognition accuracy of a developed artificial odor discrimination system for three mixture fragrance recognition, Fuzzy Similarity based Self-Organized Network inspired by Immune Algorithm (F-SONIA) is proposed. Minimum, average, and maximum values of fragrance data acquisitions are used to form triangular fuzzy numbers. Then the fuzzy similarity treasure is used to define the relationship between fragrance inputs and connection strengths of hidden units. The fuzzy similarity is defined as the maximum value of the intersection region between triangular fuzzy set of input vectors and the connection strengths of hidden units. In experiments, performances of the proposed method is compared with the conventional Self-Organized Network inspired by Immune Algorithm (SONIA), and the Fuzzy Learning Vector Quantization (FLVQ). Experiments show that F-SONIA improves recognition accuracy of SONIA by 3-9％. Comparing to the previously developed artificial odor discrimination system that used FLVQ as pattern classifier, the recognition accuracy is increased by 14-25％.

• Nuclear Engineering and Technology
• /
• v.56 no.9
• /
• pp.3626-3643
• /
• 2024

One of the issues in the development of the sodium-cooled fast reactor (SFR) using transuranic (TRU) metallic fuel is the absence of criticality benchmark experiment that faithfully mocks up the nuclear characteristics of the target design for validation of the reactor core design code and its uncertainty quantification (UQ). This study aims to quantify the criticality uncertainty of a typical TRU burner with metallic fuel by using the standard upper safety limit (USL) estimation framework based on the similarity analysis of existing benchmark experiments but elaborated in two aspects:1) application of two-sided rather than one-sided tolerance interval and 2) inclusion of additional uncertainty to account for fission products and minor actinides not included in the benchmark experiments. To conduct the similarity analysis and evaluate the nuclear-data induced uncertainty, existing, well-verified computing codes were integrated, including the nuclear data sampling code SANDY, the nuclear data processing code NJOY, and the continuous-energy Monte Carlo code McCARD. Finally, using the SFR benchmark database comprising both publicly available and proprietary benchmark experiments, the criticality uncertainty of the TRU core model with metallic fuel was evaluated.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.46 no.4
• /
• pp.328-333
• /
• 2001

Allium is one of the largest genera, which has more than 700 species. PCR by URP (universal rice primer) primers was carried out to get phylogenetic information on 26 species, 62 accessions of subgenus Rhizirideum. The accessions were divided into seven groups at 0.76 similarity level. A. tuberosum (Chinese chives) and A. ramosum represented high similarity of 0.91. A. montanum, A. nutans, A. senescens, A. libani, A. odorum, A. austrosibiricum, and A. narcissiflorium grouped at 0.80 similarity. Some of the wild species, such as A. prostratum, A. polyrhizum, A. odorum, and A. mongolicum, showed different band patterns according to polyploidy, occurrence of B-chromosome, collection site, and origin.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.10
• /
• pp.4987-5005
• /
• 2017

This paper introduces a new method to solve Similarity Recognition for Cloth Products, which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience, it is called the SRCPFP method hereafter. In this paper, the SRCPFP method combines Fuzzy Logic (FL) and Particle Swarm Optimization (PSO) algorithm to solve similarity recognition for cloth products. First, it establishes three features, length, thickness, and temperature resistance, respectively, for each cloth product. Subsequently, these three features are engaged to construct a Fuzzy Inference System (FIS) which can find out the similarity between a query cloth and each sampling cloth in the cloth database D. At the same time, the FIS integrated with the PSO algorithm can effectively search for near optimal parameters of membership functions in eight fuzzy rules of the FIS for the above similarities. Finally, experimental results represent that the SRCPFP method can realize a satisfying recognition performance and outperform other well-known methods for similarity recognition under considerations here.

• Journal of the Korea Convergence Society
• /
• v.4 no.2
• /
• pp.35-41
• /
• 2013

Data management with fuzzy entropy and similarity measure were discussed and verified by applying reliable data selection problem. Calculation of certainty or uncertainty for data, fuzzy entropy and similarity measure are designed and proved. Proposed fuzzy entropy and similarity are considered as dissimilarity measure and similarity measure, and the relation between two measures are explained through graphical illustration.Obtained measures are useful to the application of decision theory and mutual information analysis problem. Extension of data quantification results based on the proposed measures are applicable to the decision making and fuzzy game theory.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.11
• /
• pp.25-30
• /
• 2015

The enormous increase of data with the development of the information technology make internet users to be hard to find suitable information tailored to their needs. In the face of changing environment, the information filtering method, which provide sorted-out information to users, is becoming important. The data on the internet exists as various type. However, similarity calculation algorithm frequently used in existing collaborative filtering method is tend to be suitable to the numeric data. In addition, in the case of the categorical data, it shows the extreme similarity like Boolean Algebra. In this paper, We get the similarity in SNS user's information which consist of the mixed data using the Gower's similarity coefficient. And we suggest a method that is softer than radical expression such as 0 or 1 in categorical data. The clustering method using this algorithm can be utilized in SNS or various recommendation system.

• International journal of advanced smart convergence
• /
• v.12 no.3
• /
• pp.75-88
• /
• 2023

In a specific domain, experts have different understanding of domain knowledge or different purpose of constructing ontology. These will lead to multiple different ontologies in the domain. This phenomenon is called the ontology heterogeneity. For research fields that require cross-ontology operations such as knowledge fusion and knowledge reasoning, the ontology heterogeneity has caused certain difficulties for research. In this paper, we propose a novel ontology matching model that combines word embedding and a concatenated continuous bag-of-words model. Our goal is to improve word vectors and distinguish the semantic similarity and descriptive associations. Moreover, we make the most of textual and structural information from the ontology and external resources. We represent the ontology as a graph and use the SimRank algorithm to calculate the structural similarity. Our approach employs a similarity queue to achieve one-to-many matching results which provide a wider range of insights for subsequent mining and analysis. This enhances and refines the methodology used in ontology matching.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.317-320
• /
• 2004

In this work we have managed to find parameters for defining athlete's aerobic and anaerobic thresholds. Thresholds which are of vital importance for top athletes. It is shown how differential evolution and different similarity measures has been used to tune computational model for threshold definitions. From our results it is obvious that the use of right parameter values for this kind expert system is of vital importance.

• International Commerce and Information Review
• /
• v.11 no.1
• /
• pp.139-155
• /
• 2009

This study investigates empirically the export competitiveness of Korea and Japan in America by calculating 4 indexes such as market share index(MSI), export similarity index(ESI), market comparative adventage index(MCAI) and market share expansion ratio(MSER)-export similarity deepening ratio(ESDR). The empirical finding of this analysis shows that Korea is competitive in the labor-intensive products and Japan in the technology-intensive products. This result also meets the general understandings that Japan is superior to Korea in the export competitiveness such as value added of goods, etc. Therefore, in order to strengthen the export competitiveness of Korea in the US market, it's desirable for our firms and government to improve the quality of product ranges by developing technologies focused on the higher value-added products.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.9 no.6
• /
• pp.118-126
• /
• 2000

In this study, geometrical similarity conditions for drills of various diameters are discussed. The effect of geometrical similarity on the chip shape and forces of different sized conventional drills has been experimentally confirmed. Drilling tests are carried out for SM45C by using the conventional HSS drills. The torque and thrust forces are measured and compared with those chip forms. Chip shape in drilling are affected by three factors being flow angle, side and up curl of the chip. It is found that the feedrate and drill diameter are more affected than cutting speed on the chip form and cutting forces. The similarity conditions gives easily to estimate the chip shape, the thrust and the torque for drills of different diameters.