• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.960-968
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• 2005

The high cost in maintaining complex manufacturing process makes it necessary to enhance an efficient maintenance system. For the effective maintenance of manufacturing process, precise fault diagnosis should be performed and an appropriate maintenance action should be executed. This paper suggests an intelligent fault diagnosis system using hybrid data mining. In this system, the rules for the fault diagnosis are generated by hybrid decision tree/genetic algorithm and the most effective maintenance action is selected by decision network and AHP. To verify the proposed intelligent fault diagnosis system, we compared the accuracy of the hybrid decision tree/genetic algorithm with one of the general decision tree learning algorithm(C4.5) by data collected from a coil-spring manufacturing process.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.97-108
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• 2010

The objective of this study is to develop evaluation indices which can be applied to analyze rational rehabilitation-policy directions of redundant farmlands. To achieve this objective, the main tasks of this research are 1) categorizing the redundant farmlands rehabilitation types 2) developing the evaluation indices of redundant farmlands rehabilitation 3) determining the weights of each index. The redundant farmlands rehabilitation types were classified into agricultural rehabilitation type, non-agricultural rehabilitation type and hybrid type which are called by agricultural income model, rural environment improvement model and hybrid model as development project name, respectively. The 5 parts and 21 indices for evaluation of redundant farmlands rehabilitation directions were extracted by case studies and experts brainstorming. The weights of each index were determined by Analytic Hierarchy Process (AHP). The developed evaluation indices were applied to study areas located on Yanghwa district of Gongju-city and Aewol district of Jeju-city. From the results of this study, it was ascertained that the evaluation indices developed in this study would help the decision-makers in the planning process of redundant farmlands rehabilitation directions.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.59-67
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• 2009

The purpose of this study is to provide a decision support to select an appropriate layered manufacturing(LM) machine that suits the application of a part. Selection factors include concept model, form/fit/functional model, pattern model far molding, material property, build time and part cost that greatly affect the performance of LM machines. However, the selection of a LM is not an easy decision because they are uncertain and vague. For this reason, the aim of this research is to propose hybrid multiple attribute decision making approaches to effectively evaluate LM machines. In addition, because subjective considerations are relevant to selection decision, a fuzzy logic approach is adopted. The proposed selection procedure consists of several steps. First, we identify LM machines that the users consider After constructing the evaluation criteria, we calculate the weights of the criteria by applying the fuzzy Analytic Hierarchy Process(AHP) method. Finally, we construct the fuzzy Technique of Order Preference by Similarity to Ideal Solution(TOPSIS) method to achieve the ranking order of all machines providing the decision information for the selection of LM machines.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.111-118
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• 2012

Recently, most of firms have continuously released new products satisfying various needs of customers in order to increase market share. As a lot of products with various functionalities, prices and designs are released in the market, users have difficulties in choosing an appropriate product, especially for information technology driven devices. In case of digital cameras, inexperienced users spend a lot of time and efforts to find proper model for them. In this study, therefore, we design and implement a personalized recommendation system using analytic hierarchy process, one of the multi-criteria decision making techniques, and hybrid filtering combining content-based filtering and collaborative filtering to recommend a suitable product for inexperienced users of information technology devices.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.124-131
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• 2000

A shop floor can be considered as and importand level to develop a Computer Integrated Manufacturing system (CIMs). The shop foor is a dynamic environment where unexpected events contrinuously occur, and impose changes to planned activities. The shop floor should adopt an appropriate control system that is responsible for scheduling coordination and moving the manufacturing material and information flow. In this paper, the architecture of the hybrid control model identifies three levels; i.e., the shop floor controller (SFC), the cell controller(CC) and the equipment controller (EC). The methodology for developing these controller is employ an object-oriented approach for static models and IDEF0 for function models for dispatching a job. SFC and CC are coordinated by employing a multi-factors bidding and an adapted Analytic Hierarchy Process(AHP) prove applicability of the suggested method. Test experiment has been conducted by with the shopfloor, consisting of six manufacturing cells.

• Environmental Engineering Research
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• v.24 no.4
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• pp.559-565
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• 2019

In order to alleviate the environmental pressure caused by production process of thermal power plants, the application of cleaner production is imperative. To estimate the implementation effects of cleaner production in thermal plants and optimize the strategy duly, it is of great significance to take a comprehensive evaluation for sustainable development. In this paper, a hybrid model that integrated the analytic hierarchy process (AHP) with least squares support vector machine (LSSVM) algorithm optimized by grid search (GS) algorithm is proposed. Based on the establishment of the evaluation index system, AHP is employed to pre-process the data and GS is introduced to optimize the parameters in LSSVM, which can avoid the randomness and inaccuracy of parameters' setting. The results demonstrate that the combined model is able to be employed in the comprehensive evaluation of the cleaner production in the thermal power plants.

• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.105-122
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• 2012

This paper proposes a fuzzy-based AHP model by which the greenhouse gas reduction for container terminal problem was systematically structured and then evaluated. The model was established by exploiting a fuzzy theory and AHP for capturing the inexactness and vagueness of information. In this study, measurement areas were selected for equipment aspect, operating aspect, and energy aspect. The greenhouse gas reduction is the number one priority in the equipment aspect, operating aspect, energy aspect in order. The analysis result of equipment aspect reveals that the most important element is electrical T/C. The most important element of operating and energy aspect were a container rehandling and a LED lighting. As for the whole priority which conversion weight was applied, the results were shown as follows: an electrical T/C(16.2%) as the first rank: a hybrid Y/T(14.4%) as the second rank: a AMP(10.6%) as the third rank. The result of this study suggests some guidelines for deciding priority of greenhouse gas reduction for container terminal.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.205-214
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• 2007

Nowadays the customer is classified with external customers and the inside customers. Which are not only end users who consume products but also all people who contribute to their earnings through the management activity of the enterprise. Furthermore, the fact that the external customer satisfaction index and inside customer satisfaction index are closely related is supported by many researches. It is interpreted if the inside customer satisfaction is not improved, achievement of the external customer satisfaction cannot be easy. In this paper, First, we will deduce the inefficient index through DEA model in each department after setting up the weight of items of inside customer satisfaction and measuring them. Second, as well as research entire models about improvement methods of inside customer satisfaction getting improvement methods for reaching a goal in the minimum amount of efforts.

• The Journal of Korean Medicine
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• v.33 no.3
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• pp.10-19
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• 2012

Objectives: This study aimed to assess the priorities among the environmental factors on, and to build core strategies for fostering Korean medical tourism. Methods: We used an A'WOT hybrid method which combined SWOT with Analytic Hierarchy Process (AHP), that is, the strategic factors in each strengths, weaknesses, opportunities, and threats group were selected by medical tourism experts' opinion, and then the importance of the factors in each SWOT group were pair-wise compared. Results: The results presented that the opportunities and the strengths groups are relatively more important than the other groups. The key competitive factors include high-quality human resources of traditional medicine, modernized system of Korean medical institutions, and local governments' willpower to promote herbal industries. Conclusions: Based on the results of analysis, it is suggested for government to build a timely strategic plan, to enhance cooperative activities with the private sector, to organize local resources, and to provide marketing support.