• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.274-283
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• 2002

This paper presents an efficient models for reinforeced concrete structures using CART-ANFIS(classification and regression tree-adaptive neuro fuzzy inference system). a fuzzy decision tree parttitions the input space of a data set into mutually exclusive regions, each of which is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the Predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it everywhere continuous and smooth. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• Korean Journal of Artificial Intelligence
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• v.4 no.1
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• pp.11-13
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• 2016

These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

• Journal of Sasang Constitutional Medicine
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• v.29 no.3
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• pp.248-261
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• 2017

Objectives The purpose of this study is to analyze the decision making process of prescribing Yeoldahanso-tang and Taeeumjowi-tang Choweseuncheng-tang using decision tree. Methods We used collected the prospective clinical data of TE type from September 2012 to July 2015. In this study, we used gender, BMI, blood pressure, pulse and clinical symptoms (digestion, sweat, defecation, urination, sleep, physical status, emotion, heat-coldness, water consumption, facial color) as variables. Decision trees were analyzed using open source R version 3.3.2. Results & Conclusions We found that the decision trees differed among institutions. However, in all institutions, it was found that stool type (ordinary symptom), urine frequency (ordinary and present symptom) and anxiety (ordinary symptom) were important in the decision of prescription. Besides, clinical informations such as sex, Body Mass Index and blood pressure affected the prescription decision.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.350-358
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• 2021

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.203-212
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• 2002

This study examined the predictive power of data mining algorithms by comparing the performance of logistic regression and decision tree algorithm, called CHAID (Chi-squared Automatic Interaction Detection), On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system (HIS ). This system can help improve decision making capability of doctors and improve accessibility of educational material for patients.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.263-277
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• 2016

Recently, 3D printing technology has been considered as a core applicable technology because it brings many improvements such as the development of medical technology, medical customization, and reducing production cost and shortening treatment period. This research suggests a market prediction framework for medical 3D printing business. As an immature market situation, it is important to control some uncertainty for market prediction such as a customers' conversion rate. So we adopt decision making tree (DMT) model which used to choose an optimal decision making among diverse pathway. Among medical industries this paper just focuses on dentistry business. For predicting a 5 year period trend expected market size, we identified some replaceable denture procedure by 3D printing, collected related data, controlled uncertain variables. The result shows that medical 3D printing business could be a market of 28.2 billion won at 1st year and in the end of fifth year it could become on a scale of 61.1 billion won market.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.34-55
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• 2002

This paper deals with the multiple attribute decision making problem when a decision maker incompletely articulates his/her preferences about the attribute weight and alternative value. Furthermore, we consider the attribute tree which is structured hierarchically. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, we propose solution techniques to handle this difficulty. Also, to handle the tree structure, we break down the attribute tree into sub-trees. Due to there cursive structure of the solution technique, the optimization results from sub-trees can be utilized in computing the value interval on the topmost attribute. The value intervals computed by the proposed solution techniques can be used to establishing the pairwise dominance relation between alternatives. In this paper, pairwise dominance relation will be represented as strict dominance and weak dominance, which ware already defined in earlier researches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.674-679
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• 1998

In this paepr, we proposed a new way to make a pre-pruned searching tree for GO game moves from macroscopic strategy described in linguistic expression. The strategy was a consequence of macroscopic recognition of GO game situations. The definitions of fuzzy macroscopic strategy, fuzzy tactics and tactical sequences using fuzzy set are shown and its family, so called "multi level fuzzy set". Some examples are also shown.

• Agribusiness and Information Management
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• v.5 no.1
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• pp.31-41
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• 2013

The research assesses the impact of a digital procurement (e-purjee) system for sugarcane growers in Bangladesh. The system itself is simple, transmitting purchase orders to local farmers via SMS text notification. It replaces a traditional paper-based system fraught with low reliability and delivery delays. Applying expected value theory, and using decision tree representations to depict growers' decision-making complexity in an information-asymmetric environment, we compute outcomes for the strategies and sub-strategies of ICT vs. traditional paper-based order management from the sugarcane growers' perspective. The study results show that the digital procurement system outperforms the paper-based system by tangibly reducing growers' economic losses. The digital system also appears to benefit growers non-monetarily, because of reduced uncertainty and a higher level of perceived fairness. Sugarcane growers appear to value the non-monetary benefits even higher than the economic advantages of the e-purjee system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.4 no.4
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• pp.63-69
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• 1981

As enterprises are getting bigger and bigger and more competecious, an engineering economy for the maximization of profit based on basic theory must be considered. This thesis present dynamic computer model for the decision which controls complicated and various man- machine system optimally. This model occur in general stage can be adaptable to every kind of enterprises. So, any one who has no expert knowledge is able to get the optimal solution. And decision tree used in this paper can be applied in every kinds of academic circles as well as whole the industrial world. This paper studied optimal management of engineering project based upon basic theory of engineering economy. It introduces and functionizes the variables which generalize every possible elements, set up a model in order to find out the variable which maximize the calculated value among many other variables. And the selected values ate used as decision- marking variables for the optimal management of engineering projects. It found out some problem of this model. They are : 1. In some kinds of man-machine system it refers to Probability, but other case, it depends on only experimental probability. 2. Unless decision making process (decision tree) goes on, this model can not be applied. So these cases, this paper says, can be solved by adapting finite decision tree which is analyzed by using the same technic as those in product introduction problem. And this paper set up the computer model in order to control every procedure quickly and optimally, using Fortran IV.