• Tunnel and Underground Space
• /
• v.11 no.4
• /
• pp.289-300
• /
• 2001

In the design of tunnel, it contains inaccuracy of data, fuzziness of evaluation, observer error and so on. The face observation during tunnel excavation, therefore, plays an important role to raise stability and to reduce supporting cost. This study is carried out to minimize the subjectiveness of observer and to exactly evaluate the natural properties of ground during the face observation. For these purpose, fuzzy set theory and neuro-fuzzy techniques in artificial intelligent techniques are applied to the inference of the RMR value from the observation data. The correlation between original RMR vague and inferred RM $R_{_FU}$ and RM $R_{_NF}$ values from fuzzy set theory and neuro-fuzzy techniques is investigated using 46 data. The results show that good correlation between original RMR value and infected RM $R_{_FU}$ and RM $R_{_NF}$ value is observed when the correlation coefficients are ｜R｜=0.96 and ｜R｜=0.95 respectively. From these results, applicability of fuzzy set theory and neuro-fuzzy techniques to rock mats classification is proved to be sufficiently high enough. enough.

• International Journal of Computer Science & Network Security
• /
• v.24 no.1
• /
• pp.163-177
• /
• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of Navigation and Port Research
• /
• v.28 no.3
• /
• pp.177-184
• /
• 2004

The purpose of this study is to identify and evaluate the competitiveness of container ports in ASEAN(Association of Southeast Asian Nations) and Korea, which plays a leading role in basing the hub of international logistics strategies at the onset of the 21st century. Its ultimate purpose is to consider the relevant policy-making by comparing the competitiveness of ASEAN and Korea's container ports. This paper adopted the HFP method, which is an empirical analysis that evaluated the port competitiveness by quantifying it a, a qualitative attribute in the aforementioned area, where both ASEAN and Korea vie with each other for increasing container throughput. The results of this study showed that Singapore ranked the first in the subject of study in view of the competitiveness, followed by Busan(2) and Manila(2) as a leading group of the relevant ports in international logistics strategies. This analytic evaluation contributes to the empirical approach applied to policy-making by the HFP method, which is the newest research technique in social science through the comparative study of port competitiveness between ASEAN and Korea.

• International Journal of Automotive Technology
• /
• v.2 no.1
• /
• pp.17-23
• /
• 2001

Measurements of the initial values lead to an inverse and mathematically unprecisely formulated problem. A precise definition of an inverse problem is possible. It is to state a mathematical model of a physical process with clearly defined initial and exit values for the system behind the process. One can grasp the idea of an inverse problem by considering the tire as a copy of the objects of nature in a room with observations. Interpretation of nature is generally a result of an inverse problem. On one hand, the tire may be represented through the sensory organs and the nervous system as well as the experiences of the developer's existing apparatus of the projection of reality. On the other hand, it may be represented by a physical law or a model that can be confirmed or is to be refuted with the help of suitable measurements. During reconstruction of a measuring signal and the identification of a black box that can be assumed to be linear and causal, the tire becomes a first type Volterra integral equation of the convolution type. But measurements of the initial values are always fuzzy, the errors grow and the system behavior can no longer be forecasted. Thus, we have to deal with a chaotic system. This chaos produces fractals in a natural way. These are self-similar geometric structures. This self-similarity is clearly visible in the design.

• Journal of Korean Society of Rural Planning
• /
• v.13 no.2
• /
• pp.7-16
• /
• 2007

This study aims to develop an evaluation method of green-tourism potential in village level with amenity resources of rural villages, considering human resources of the village. The amenity resources evaluation system was classified into three sub-classes with social, industrial, and natural resources. The system consisted of a relationship diagram between three classes resources and tourists' behavior. The new methodology considers human resources as a key factor for green-tourism potential evaluation of villages, including the amenity resources of three sub-classes. In quantitative method for the criteria, this study adopted a new method of continuous linear score method, which is applying fuzzy theory, not to give score with the existing discrete scoring method with several steps. The weighting values of the evaluation criteria were calculated from the step wise pair-comparision results by AHP(Analytic Hierachy Process) method, which industrial, natural, and social resources have relative weighting values of 523/1000, 319/1000, and 158/1000, respectively. In evaluation of another weighting value by the same methodology, the results showed that the amenity and the human resources have weighting values of 627/100 and 373/1000, respectively. The new evaluation method was applied to make the potential evaluation for rural villages of the study area, which located on Narial-myun, Keumsan-gun, Chungnam province. The development priority among the villages could be suggested reasonably by the new findings of this study, according to the evaluation results showing that the village with high possibility for development in green-tourism has high score in the potential evaluation.

• The Journal of the Korea Contents Association
• /
• v.6 no.10
• /
• pp.1-8
• /
• 2006

The new system evaluating the pollution of the water quality for the branches of geum river using the fuzzy integral was proposed in this study. In this paper, the five individual factors, such as BOD(biochemical oxygen demand), COD(chemical oxygen demand), SS(suspended solids), T-N(total nitrogen), and T-P(total phosphorus) are selected. The measurement of fuzzy integral was determined depending on the degree of how they affect the pollution of water quality. The real values for the five factors measured and obtained from the branches of the geum river was normalized to ranging from 0 to 1. Finally, using the fuzzy integral, the degree of the pollution for the branches of geum river was expressed as the real numerical number. As a result, it appears that this approach can be proposed as the new system evaluating the pollution of the water quality for the branches of the geum river.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.4
• /
• pp.575-594
• /
• 2010

In this study, we propose a space search algorithm (SSA) and then introduce a hybrid optimization of fuzzy inference systems based on SSA and information granulation (IG). In comparison with "conventional" evolutionary algorithms (such as PSO), SSA leads no.t only to better search performance to find global optimization but is also more computationally effective when dealing with the optimization of the fuzzy models. In the hybrid optimization of fuzzy inference system, SSA is exploited to carry out the parametric optimization of the fuzzy model as well as to realize its structural optimization. IG realized with the aid of C-Means clustering helps determine the initial values of the apex parameters of the membership function of fuzzy model. The overall hybrid identification of fuzzy inference systems comes in the form of two optimization mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and polyno.mial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by SSA and C-Means while the parameter estimation is realized via SSA and a standard least square method. The evaluation of the performance of the proposed model was carried out by using four representative numerical examples such as No.n-linear function, gas furnace, NO.x emission process data, and Mackey-Glass time series. A comparative study of SSA and PSO demonstrates that SSA leads to improved performance both in terms of the quality of the model and the computing time required. The proposed model is also contrasted with the quality of some "conventional" fuzzy models already encountered in the literature.

• Survey Research
• /
• v.11 no.3
• /
• pp.57-79
• /
• 2010

This study evaluated the policy performance of i) Public Notice of Critical Information, ii) Substantiation of Facts in Labeling and Advertising, iii) Temporary Injunctions, and iv) Advertisement Correcting Misrepresented Facts, which were main policies belonged to Fair Labeling and Advertising Act(hereinafter referred to as "FLA Act"). The data was collected by visiting 76 persons personally, who were consumer policy and law experts, labeling and advertising staffs of corporations, and persons in charge of policies including public officials dealing with consumer policies at Korea Fair Trade Commission, while using a structured questionnaire at the same time. The survey was performed to examine the general policy performance and evaluation the results of FLA Act by evaluation methods. The results of the analysis are comprehensively summarized as follows. There were differences in the ranking of policies evaluated by labeling and advertising staffs of corporations and persons in charge of policies according to evaluation methods, and, in Simple Evaluation, higher scores were gained compared to Weighted Evaluation which reflected weighted values or Fuzzy Evaluation. The result shows that evaluation results can vary in policy performance evaluation according to evaluation methods.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.10
• /
• pp.141-151
• /
• 1999

The resistance Spot Welding is widely used in the field of assembling the plates. However we don't still have any satisfactory solution, which is non-destructive quality evaluation in real-time or on-line, against it. Moreover, even though the rate of welding under the condition of expulsion has been high until now, quality control of welding against expulsion hasn't still been established. In this paper, it was proposed on the quality assurance technique of resistance spot welding pieces using Neuro-Fuzzy algorithm. Four parameters from electrode separation signal in the case of non-expulsion, and dynamic resistance patterns in the case of expulsion are selected as fuzzy input parameters. The parameters consist of Fuzzy Inference System are determined through Neuro-Learning algorithm. And then, fuzzy Inference System is constructed. It was confirmed that the fuzzy inference values of strength have within ${\pm}$4% error specimen in comparison with real strength for the total strength range, and the specimen percent having within ${\pm}$1% error was 88.8%. According to KS(Korean Industrial Standard), tensile-shear strength limit for electric coated of zinc is 400kgf/mm2. Judging to the quality of welding is good or bad, according to this criterion and the results of inference, the probability of misjudgement that good quality is valuated into poor one was 0.43%, on contrary it was 2.59%. Finally, the proposed Neuro-Fuzzy Inference System can infer the tensile-shear strength of resistance spot welding pieces with high performance for all cases-non-expulsion and expulsion. And On-Line Welding Quality Inspection System will be realized sooner or later.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5229-5252
• /
• 2016

With proliferation of diverse network access technologies, users demands are also increasing and service providers are offering a Quality of Service (QoS) to satisfy their customers. In roaming, a mobile node (MN) traverses number of available networks in the heterogeneous wireless networks environment and a single operator is not capable to fulfill the demands of user. It is crucial task for MN for selecting a best network from the list of networks at any time anywhere. A MN undergoes a network selection situation frequently when it is becoming away from the home network. Multiple Attribute Group Decision (MAGD) method will be one of the best ways for selecting target network in heterogeneous wireless networks (4G). MAGD network selection process is predominantly dependent on two steps, i.e., attribute weight, decision maker's (DM's) weight and aggregation of opinion of DMs. This paper proposes Multi-Attribute Intuitionistic Fuzzy Group Decision Method (MAIFGDM) using TOPSIS for the selection of the suitable candidate network. It is scalable and is able to handle any number of networks with large set of attributes. This is a method of lower complexity and is useful for real time applications. It gives more accurate result because it uses Intuitionistic Fuzzy Sets (IFS) with an additional parameter intuitionistic fuzzy index or hesitant degree. MAIFGDM is simulated in MATLAB for its evaluation. A comparative study of MAIFDGM is also made with TOPSIS and Fuzzy-TOPSIS in respect to decision delay. It is observed that MAIFDGM have low values of decision time in comparison to TOPSIS and Fuzzy-TOPSIS methods.