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

• The Journal of Information Systems
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• v.8 no.2
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• pp.91-110
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• 1999

Recently, searching agent systems to help purchase of products between business and customer have been actively studied in Electronic Commerce(EC). However, the most of comparative searching agent systems are only provided customers with searching results by the keyword-based search, and is not support the efficient decision models to be selected products considering the customer's requirements. This paper proposes the decision agent system applied decision model as well as searching functions based on the keyword-input to be selected useful products in EC. The proposed decision agent system is consist of the user interface, provider interface, decision model. Especially, as the example of the decision model, this paper is designed and implemented the prototype of decision agent system which is normalized the searching data and value of customer's preference weight as to each attribute, and orderly provided customers with computed results. This agent system is also carried out sensitive analysis according to the reflection ratio of the each attribute.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.1-16
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• 2012

This paper is aimed to present a fuzzy decision-making approach to deal with disaster recovery priority decision problem in information system. We derive an evaluation approach based on TOPSIS(Technique for Order Performance by Similarity to Ideal Solution), to help disaster recovery priority decision of total information system for port logistics in a fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by trapezoidal fuzzy numbers. This study applies the fuzzy multi-criteria decision-making method to determine the importance weight of evaluation criteria and to synthesize the ratings of candidate disaster recovery system. Aggregated the evaluators' attitude toward preference, then TOPSIS is employed to obtain a crisp overall performance value for each alternative to make a final decision. This approach is demonstrated with a real case study involving 4 evaluation criteria(system dependence, RTO, loss, alternative business support), 7 information systems for port logistics assessed by 5 evaluators from Maritime Affairs and Port Office.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.107-119
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• 2003

Expectation and interest about e-CRM are rising for more efficient customer management in on-line including electronic commerce. The decision-making tree can be used usefully as the data mining technology for e-CRM. In this paper, the representative decision making techniques, CART, C4.5, CHAID analyzed the differences in personalization point of view with actuality customer data through an experiment. With these analysis data, it is proposed a new decision-making tree system that has big advantage in personalization techniques. Through new system, it can get following advantage. First, it can form superior model more qualitatively in personalization by adding individual's weight value. Second it can supply information personalized more to customer. Third, it can have high position about customer's loyalty than other site of similar types of business. Fourth, it can reduce expense that cost marketing and decision-making. Fifth, it becomes possible that know that customer through smooth communication with customer who use personalized service wants and make from goods or service's quality to more worth thing.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.57-67
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• 2012

This paper presents the Multi Criteria Decision Making (MCDM) to evaluate water resources plan for agricultural reservoir. Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE) and Analytic Hierarchy Process (AHP) were used to estimate weight and priority of alternatives to find out the most reasonable and efficient way of water resources assessment. The 6 criteria that both decision maker and beneficiary are satisfied have been identified to secure agricultural water resources and then the priority of 10 subcriteria was set. An enhanced PROMETHEE-AHP model was used to perform pairwise comparison and find out the priority of each alternative because the existing decision making model have uncertainty and ambiguity. Comparison analysis of decision making models was carried out to find a way of suitable decision making and validity of PROMETHEE-AHP model was suggested.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.102-108
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• 2005

This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.

• Journal of Energy Engineering
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• v.8 no.4
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• pp.612-620
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• 1999

Environmental impact assessment in the step of the Life Cycle Assessment (LCA) measures relative values of importance or weight of the environmental load characterized in the inventory analysis. The weight measurements are used to evaluate the environmental load or the effect of the industrial product or technology. In this paper the Analytic Network Prpcess (ANP) is introduced to calculate a relative weighting of the environmental impact. The ANP is considered as one of the useful decision making framework and allow for more complex interrelationships, feedback, and inner/outer dependence among the decision level and factors. The weighting from the ANP may applied to obtain the overall evaluation value of environmental load.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.19-33
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• 2001

Link weight analysis approach is suggested as a heuristic for selection of input nodes in artificial neural network for bankruptcy prediction. That is to analyze each input node\\\\`s link weight-absolute value of link weight between an input node and a hidden node in a well-trained neural network model. Prediction accuracy of three methods in this approach, -weak-linked-neurons elimination method, strong-linked-neurons selection method and integrated link weight model-is compared with that of decision tree and multivariate discrimination analysis. In result, the methods suggested in this study show higher accuracy than decision tree and multivariate discrimination analysis. Especially an integrated model has much higher accuracy than any individual models.

• Journal of Korean Medicine for Obesity Research
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• v.19 no.1
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• pp.31-41
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• 2019

Objectives: The purpose of this study was to investigate the effects of gender, age, body weight, muscle mass, fat mass, body mass index (BMI), metabolism, and compliance with medication on weight loss in obese adults. Methods: We reviewed the medical records of 178 patients who were visited to the Korean Oriental Clinic for 3~6 month and had obesity treatment using Gamitaeumjowee-tang from April 2017 to May 2017. We conducted a paired T-test, correlation coefficient and decision tree to analyze factors influencing obesity treatment. Results: The results of correlation analysis showed that initial weight (kg), initial fat mass (kg), BMI ($kg/m^2$), compliance with medication (%), Original Harris-Benedict Equation, Revised Harris-Benedict Equation and The Mifflin St Jeor Equation was significantly correlated to weight loss (kg) (P<0.001). As a result of constructing the decision tree model, it showed that over 5% weight loss of their initial weight (n=154) was related with initial BMI ($kg/m^2$), compliance with medication (%) and initial muscle mass (kg). In case of over 5 kg weight loss of their initial weight (n=131), it was related with initial BMI ($kg/m^2$), compliance with medication (%) and final BMI ($kg/m^2$). Conclusions: This study suggests that weight loss may be affected by initial factors and that initial factors can be used for obesity treatment.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.27-33
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• 2011

For compensation of channel distortion from multipath fading and impulsive noise, a decision feedback equalizer (DFE) algorithm based on minimization of Error entropy (MEE) is proposed. The MEE criterion has not been studied for DFE structures and impulsive noise environments either. By minimizing the error entropy with respect to equalizer weight based on decision feedback structures, the proposed decision feedback algorithm has shown to have superior capability of residual intersymbol interference cancellation in simulation environments with severe multipath and impulsive noise.