• ETRI Journal
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• v.44 no.4
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• pp.560-572
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• 2022

H²RDC (heuristic handover based on RCC-DTSK-C), a heuristic algorithm based on a highly interpretable deep Takagi-Sugeno-Kang fuzzy classifier, is proposed for suppressing the mobile heterogeneous networks problem of frequent handover and handover ping-pong in the multibase-station scenario. This classifier uses a stack structure between subsystems to form a deep classifier before generating a base station (BS) priority sequence during the handover process, and adaptive handover hysteresis is calculated. Simulation results show that H²RDC allows user equipment to switch to the best antenna at the optimal time. In high-BS density load and mobility scenarios, the proposed algorithm's handover success rate is similar to those of classic algorithms such as best connection (BC), self tuning handover algorithm (STHA), and heuristic for handover based on AHP-TOPSIS-FUZZY (H²ATF). Moreover, the handover rate is 83% lower under H²RDC than under BC, whereas the handover ping-pong rate is 76% lower.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.487-496
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• 2018

In route selection process of NIMBY facilities, many conflicts occur due to route selection procedure and NIMBY syndrome. Especially, the social conflicts surrounding the site selection and operation are frequent enough to account for 70% of the total conflict cases, causing significant losses. To resolve the conflict in route selection, social conflicts are considered. Therefore, this study proposes an improved process of selecting route considering social conflicts in the power transmission line. First, the analysis of previous research trends and interviews with experts revealed the improved exclusion zone criteria, the factors and priorities of NIMBY facilities. After selecting the candidate routes, the optimal route is selected by using Fuzzy-TOPSIS. Hence, 83.3% of six experts have verified that this model minimizes conflicts and has sufficient applicability. The proposed model is expected to be used as a tool to minimize social conflict in the selection process of the power transmission line in the early stage of the project.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.229-236
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• 2014

Failure modes and effects analysis (FMEA) is a widely used engineering tool in the fields of the design of a product or a process to improve its quality or performance by prioritizing potential failure modes in terms of three risk factors-severity, occurrence, and detection. In a classical FMEA, the risk priority number is obtained by multiplying the three values in 10 score scales which are evaluated for the three risk factors. However, the drawbacks of the classical FMEA have been mentioned by many previous researchers. As a way to overcome these difficulties, this paper suggests the ELECTRE III that is a representative technique among outranking models. Furthermore, fuzzy linguistic variables are included to deal with ambiguous and imperfect evaluation process. In addition, when the importances for the three risk factors are obtained, the entropy method is applied. The numerical example which was previously studied by Kutlu and Ekmekio$\breve{g}$lu(2012), who suggested the fuzzy TOPSIS method along with fuzzy AHP, is also adopted so as to be compared with the results of their research. Finally, after comparing the results of this study with that of Kutlu and Ekmekio$\breve{g}$lu(2012), further possible researches are mentioned.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.159-170
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• 2022

As the severity of water-related disasters increases in urban watersheds due to climate change, reducing flood damage in urban watersheds is one of the important issues. This study focuses on prioritizing the optimal site for permeable pavement to maximize the efficiency of reducing flood damage in urban watersheds in the future climate environment using multi-criteria decision making techniques. The Mokgamcheon watershed which is considerably urbanized than in the past was selected for the study area and its 27 sub-watersheds were considered as candidate sites. Six General Circulation Model (GCM) of Coupled Model Intercomparison Project 6(CMIP6) according to two Shared Socioeconomic Pathway (SSP) scenarios were used to estimate future monthly precipitation for the study area. The Driving force-Pressure-State-Impact-Response (DPSIR) framework was used to select the water quantity evaluation criteria for prioritizing permeable pavement, and the study area was modeled using ArcGIS and Storm Water Management Model (SWMM). For the values corresponding to the evaluation criteria based on the DPSIR framework, data from national statistics and long-term runoff simulation value of SWMM according to future monthly precipitation were used. Finally, the priority for permeable pavement was determined using the Fuzzy TOPSIS and Minimax regret method. The high priorities were concentrated in the downstream sub-watersheds where urbanization was more progressed and densely populated than the upstream watersheds.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3794-3820
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• 2019

In recent years, a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability is much needed. This study presents a cloud storage framework, wherein a 128-bit encryption key has been generated by combining deoxyribonucleic acid (DNA) cryptography and the Hill Cipher algorithm to make the framework unbreakable and ensure a better and secured distributed cloud storage environment. Moreover, the study proposes a DNA-based encryption technique, followed by a 256-bit secure socket layer (SSL) to secure data storage. The 256-bit SSL provides secured connections during data transmission. The data herein are classified based on different qualitative security parameters obtained using a specialized fuzzy-based classification technique. The model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers. A fuzzy-based technique for order of preference by similarity to ideal solution (TOPSIS) multi-criteria decision-making (MCDM) model has been employed for this, which can decide on the set of suitable storage servers on which the data must be stored and results in a reduction in execution time by keeping up the level of security to an improved grade.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.

• Geomechanics and Engineering
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• v.28 no.2
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• pp.145-155
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• 2022

Safety is a most important parameters in underground railway transportation; Also stability of underground tunnel is very important in tunneling engineering. Design of a reliable support system requires an evaluation of both ground demand and support capacity. Iran's traditional railway tunnels are mainly supported with masonry structures or unsupported in high quality rock masses. A decrease in rock mass quality due to changes in groundwater regime creep and fatigue in rock and similar phenomena causes tunnel safety to decrease during time. The case study is an old tunnel in Iran, called "Keshvar"; it is more than 50 years old railway organization. In operating this Tunnel, until the several problems came up based on stability and leaking water. The goal of study is evaluation of the various reinforcement systems for supporting of the tunnel. The optimal selection of the reinforcement system is examined using TOPSIS Fuzzy method in light of the looming and available uncertainties. Several factors such as; the tunnel span, maintenance, drainage, sealing, ventilation, cost and safety were based to choose the method and system of designing. Therefore, by identifying these parameters, an optimal reinforcement system was selected and introduced. Based on optimization system for analysis, it is revealed that the systematic rock bolts and shotcrete protection had a most appropriate result for these kind of tunnel in Iran.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.385-385
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• 2020

본 연구에서는 가뭄과 연관되는 다양한 관련 요인을 포함한 가뭄취약성 평가방안을 수립하고 이를 적용하는 것을 목표로 하였다. 평가기법은 평가인자와 가중치 선정, 평가자료 데이터베이스 구축, 평가자료와 가중치를 조합한 평가의 세 단계로 구성되었으며 평가인자 및 가중치 선정에는 Delphi 조사기법을 적용하고 평가기법으로는 최근 널리 적용되고 있는 MCDM (Multi-Criteria Decision Making) 방법인 TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) 기법을 활용하였다. 평가인자는 기상분야(Meteorological factors), 농업분야(Agricultural factors), 사회경제분야(Socioeconomic factors), 환경분야(Natural System)로 구성하였으며 선정된 인자에 대한 데이터베이스를 구성하기 위하여 기상청, 농어촌공사, 수자원공사 등의 관계기관이 관리하는 자료를 수집하였다. 수립한 가뭄취약성 평가방안을 2016년 3월부터 2019년 9월까지 우리나라 시군구 행정구역 단위, 총 167개 지역이며 순위법, 비율법, fuzzy 등 가중치 선정방법에 따라 결과에 약간의 차이가 나타난다. 가뭄예보결과와 취약성 평가결과를 비교해 보면 충청남도 홍성군이 동기간 동안 가뭄예경보 발령 횟수가 가장 많았으며, 충청남도 보령시와 서산시도 매우 높은 빈도로 확인되었다. 평가 결과, 충청북도, 경상남도, 전라남도에 가뭄 취약지역이 다수 도출 되어 이들 지역에 대한 가뭄 대응 방안 수립이 필요한 것으로 분석되었다.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.149-159
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• 2019

Six sigma is an innovative management movement which provides improved business process by adapting the paradigm and the trend of market and customers. Suitable selection of six sigma project could highly reduce the costs, improve the quality, and enhance the customer satisfaction. There are existing studies on the selection of Six Sigma projects, but few studies have been conducted to select the correct project under an incomplete information environment. The purpose of this study is to propose the application of integrated MCDM techniques for correct project selection under incomplete information. The project selection process of six sigma involves four steps as follows: 1) determination of project selection criteria 2) calculation of relative importance of team member's competencies 3) assessment with project preference scale 4) finalization of ranking the projects. This study proposes the combination methods by applying group fuzzy Analytical Hierarchy Process (AHP), an easy defuzzified number of Trapezoidal Fuzzy Number (TrFN) and Grey Relational Analysis (GRA). Both of the weight of project selection criteria and the relative importance of team member's competencies can be evaluated by group fuzzy AHP. Project preferences are assessed by easy defuzzified scale of TrFN in case of incomplete information.)