• Economic and Environmental Geology
• /
• 제50권3호
• /
• pp.195-214
• /
• 2017

Statistical landslide susceptibility analysis, which is widely used among various landslide susceptibility analysis approaches, predicts the unstable area by analyzing statistical relationship between landslide occurrence locations and landslide controlling factors. However, uncertainties are involved in the procedures of the susceptibility analysis and therefore, fuzzy approach has been used to deal properly with uncertainties. The fuzzy approach used fuzzy set theory and fuzzy membership function to quantify uncertainties involved in landslide controlling factors. Various fuzzy approaches were suggested in the procedure of the membership value determination and fuzzy operation in the previous researches. However, few studies were carried out to compare the analysis results obtained from various approaches for membership function determination and fuzzy operation. Therefore, in this study, the authors selected Jinbu area, which a large number of landslides were occurred at in 2006, to apply two most commonly used methods, the frequency ratio and the cosine amplitude method to derive membership values for each controlling factor. In addition, the integration of different thematic layers to produce landslide susceptibility map was performed by several fuzzy operators such as AND, OR, algebraic product, algebraic sum and Gamma operator. The results of the landslide susceptibility analysis using two different methods for the determination of fuzzy membership values and various fuzzy operators were compared on the basis of ROC graph to check the feasibility of the fuzzy based landslide susceptibility analysis.

• Safety and Health at Work
• /
• 제7권4호
• /
• pp.307-316
• /
• 2016

Background: Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors-self-organization, teamwork, redundancy, and fault-tolerance-in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. Methods: The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different ${\alpha}$-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four abovementioned factors. Results: The results showed that as ${\alpha}$ approached 0 and the system became fuzzier (${\alpha}=0.3$ and ${\alpha}=0.1$), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as ${\alpha}$ approached 1 and the fuzzy system went toward a certain mode (${\alpha}=0.9$ and ${\alpha}=1$), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. Conclusion: The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• 제50권7호
• /
• pp.339-349
• /
• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Journal of the Korea Society of Computer and Information
• /
• 제15권11호
• /
• pp.47-56
• /
• 2010

In navigation, officers receive data about inside and outside of ship from several devices(ex, GPS / AIS / ECDIS / ARPA Radar / etc) in bridge, and use it to recognize and predict safety situations. However, observation work of a officer is still hard for a torrent of data from several devices, and the problem of inconsistent data among the devices. In previous research, we presented the conceptual model of Intelligent Navigation Safety Information System based on information fusion, and showed the example of the conceptual model using CF (Certainty Factor) expert system to solve this problem. The information fusion technology needs various reasoning skills, and CF expert system is not enough to express ambiguous or indefinite factors. In this paper, we propose the concept of an intelligent navigation information fusion using fuzzy expert system to describe the ambiguous factors, and show the validity of applying fuzzy expert system to the Navigation Safety Information System through the design and implementation of the proposed concept.

• Journal of the Korean Institute of Intelligent Systems
• /
• 제18권1호
• /
• pp.122-126
• /
• 2008

Integrating a 3D solid modeler with a general purpose FEM code, an automatic stress intensity factor analysis system of the 3D crack problems has been developed. A geometry model, i.e. a solid containing one or several 3D cracks is defined. Several distributions of local node density are chosen, and then automatically superposed on one another over the geometry model by using the fuzzy knowledge processing. Nodes are generated and quadratic tetrahedral solid elements are generated by the Delaunay triangulation techniques. Finally, the complete finite element(FE) model generated, and a stress analysis is performed. This paper describes the methodologies to realize such functions, and demonstrates the validity of the present system.

• Journal of Korea Port Economic Association
• /
• 제27권2호
• /
• pp.39-57
• /
• 2011

Recently Incheon Port and Pyeongtak·Dangjin Port called as Capital Region Ports have enjoyed ever-increasing cargo volumes. However, there is a lack of research on this region while plenty of outputs were suggested on mega hub and regional hub ports in terms of shipping companies and stakeholders' port choice criteria. To identify and evaluate the Capital Region Ports, this paper identifies the factors and sub-components influencing their port choice and presents a structure for evaluating them. Based on the literature related to port selection and competition, a regional survey employed Factor Analysis to reveal that 'port facility and link', 'cost and service', 'port hinterland' and 'information service and port operation policy' are the determining factors in these regions. From the overall evaluation using Fuzzy Theory, Port of Incheon Port obtained high score compare to that of Port of Pyeongtak Dangjin.

• Journal of KIISE:Software and Applications
• /
• 제32권1호
• /
• pp.1-9
• /
• 2005

In this paper we propose a modified fuzzy min-max neural network model for pattern classification and discuss the usefulness of the model. We define a new hypercube membership function which has a weight factor to each of the feature within a hyperbox. The weight factor makes it possible to consider the degree of relevance of each feature to a class during the classification process. Based on the proposed model, a knowledge extraction method is presented. In this method, a list of relevant features for a given class is extracted from the trained network using the hyperbox membership functions and connection weights. Ft)r this purpose we define a Relevance Factor that represents a degree of relevance of a feature to the given class and a similarity measure between fuzzy membership functions of the hyperboxes. Experimental results for the proposed methods and discussions are presented for the evaluation of the effectiveness and feasibility of the proposed methods.

• Geomechanics and Engineering
• /
• 제27권6호
• /
• pp.605-614
• /
• 2021

Water inrush from fault is one of the most severe hazards during tunnel excavation. However, the traditional evaluation methods are deficient in both quantitative evaluation and uncertainty handling. In this paper, a comprehensive methodology method combined intuitionistic fuzzy AHP with a Bayesian network for the risk assessment of water inrush from fault in the subsea tunnel was proposed. Through the intuitionistic fuzzy analytic hierarchy process to replace the traditional expert scoring method to determine the prior probability of the node in the Bayesian network. After the field data is normalized, it is classified according to the data range. Then, using obtained results into the Bayesian network, conduct a risk assessment with field data which have processed of water inrush disaster on the tunnel. Simultaneously, a sensitivity analysis technique was utilized to investigate each factor's contribution rate to determine the most critical factor affecting tunnel water inrush risk. Taking Qingdao Kiaochow Bay Tunnel as an example, by predictive analysis of fifteen fault zones, thirteen of them are consistent with the actual situation which shows that the IFAHP-Bayesian Network method is feasible and applicable. Through sensitivity analysis, it is shown that the Fissure development and Apparent resistivity are more critical comparing than other factor especially the Permeability coefficient and Fault dip. The method can provide planners and engineers with adequate decision-making support, which is vital to prevent and control tunnel water inrush.

• Journal of Digital Convergence
• /
• 제16권2호
• /
• pp.179-188
• /
• 2018

In this paper, we analyze accident factors that occur in the unloading of steel cargoes and try to derive priority of importance among factors. The Fuzzy-AHP, which enables hierarchical analysis through pairwise comparison of factors, is used to derive priorities of safety factors to consider when unloading steel cargo. In the top factor analysis results, weights were ranked in order of human factors, safety education, equipment and facilities, and business environment. The purpose of this paper is to contribute to the improvement of the safety consciousness of the field workers and enterprises and to reduce the incidence of accidents in the unloading and unloading operations by deriving the relative importance between the factors. In the future, it is necessary to study the cargoes of other disasters such as container cargo as well as steel cargo.

• Journal of Navigation and Port Research
• /
• 제35권5호
• /
• pp.439-444
• /
• 2011

This study is aimed to extract the key role of port operation organizations for the development of region ports and identify the operating efficiency priorities of three ports such as Busan, Incheon and UIsan port operated by PA(port authority). The Factor Analysis(FA) and Fuzzy Method were used as the analysis methodes. As an important role of port authority and regional maritime affairs & port office, thirteen sub-evaluation factors and four top-level evaluation factors were selected using the FA. Among the top-level evaluation factors i.e. 'port security, information management', service for regional society and customers', 'port marketing' and 'customer attraction', the most important factor was identified as 'port marketing'. The total port efficiency was evaluated using these factors and Fuzzy Method. As a result, Busan ranked 1st, followed by Incheon and Ulsan.