• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of Korean Academy of Nursing
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• v.23 no.1
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• pp.118-129
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• 1993

In order to approach the nursing care of clients who are using oriental medicine and to understand the perception of the client who uses oriental medicine practices and the need to develop a model of nursing related to oriental medicine it is important to examine the major nursing concepts as they are found in oriental medicine and as they are differently defined according to the basic thought, theory and philosophical perspectives between East and West. Oriental medicine developed based on Sung Confucianism the teachings of Chut-zu, especially Tai-Chi-Tu Shuo and energy thought which are similar to traditional Korean Sasang Constitutional medicine. The basic theory on which oriental medicine is build is the theory of the five elements of Yin / Eum-Yang Theory(cosmic dual forces) and Meridian Theory. The most important attribute of Yin Yang is the concept of duality, confrontation and dependence, within Yin Yang but which do not exist separately. That is, the universe is a vast, indivisible entity within which all things exist in harmonious interdependence and balance. Harmony is achieved only when the two primorial forces, Yin and Yang, are brought into perfect balance. Each is contained within the other and there is a continuing interchange between the two. This also applies to the human body including human health which is defined as balanced harmony. The most universal connection of Yin and Yang is found in the universe where the five elements of life, fire, water, earth, wood and metal can be explained as having either Yin or Yang and therefore being in a state of connectedness but systematically circulating between the two, that is essentalilly one (the control of the unified ) or as coexistant poles of individual wholes (the pluralism of Yin Yang Theory) so that it is all unified(balanced) in the Great Absoulte. Human beings also maintain a balance of Yin and Yang in the five elements and this relationship is very important in approaching ·oriental medicine, The meridians are the channels in the body through which the life force flow throughout the body. In oriental medicine the meridians are seen as the railroad, the acupuncture points on the meridians as the stations and energy as the train. In the normal healthy organism, all are maintained in balance and in a contiuous circulation of energy. illness is the result of the energy flow becoming disarranged. Although practitioners of oriental medicine approach the client differently than do practitioners of Western medicine and their method of examining the patient is different, the basic objectives of the examination are the same for practitioners of both types of medicine. Therefore if each could be used to supplement the defiencies in the other and achieve a harmonious cooperation between the two, a higher level of care which is culturally appropriate to korean culture could be achieved. The traditional korean concept of health is a naturalistic view which emphasizes being in harmony with nature. Any manifestation of disease is considered a sign that the body is in a state of disequilibrium and is thus no longer in harmony with the universe. The wholistic view of the world held by practitioners of oriental medicine can be used by nursing in the development of a world view of nursing in which the human being is seen within the macrocosm as part of the natural phenomenon of the universe and but also as a microcosm of the universe, a universe which is a vast and indivisible entity within which all things exist in harmonious interdependence and balance. Interaction between human beings and their environment and the relationship of this interaction to health are concepts that are also found in nursing. Nursing views human brings, not as an accumulation of separate cells and organs but, as unified wholes interacted in very close relationship nth their environment. Nursing also maintains a view of human beings in which emphasis is placed on the role of the mind in explaining the concepts of harmony and balance in health. Although there are differences between oriental medicine and nursing in approaches to clients, the basic point of view and philosophy have many fundamental similarites. An understanding of the basic thought and philosophy of oriental medicine if applied to nursing, would allow for the development, not only of nursing related to oriental medicine, but of a nursing theory appropriate to the korean context.

• Journal of Technologic Dentistry
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• v.28 no.1
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• pp.121-142
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• 2006

Collecting materials for study on teaching efficiency and satisfaction of clinical training, it changes. Dental technology's educational procedure to many ways of a prospect. In a circumstance that needed higher level of education, this study is aimed on realizing an importance of clinical training through the various materials that previously carried out and offering basic knowledge to take better clinical training for the students. Study results below 1. This Investigation conducted on 123 of sophomores(70.3%) and 52 of juniors(29.7%) who have been taken clinical training, and men's proportion(51.45%)is a bit higher than girls(48.6%). The 64% of respondents taken largest proportion were 20 to 24 years old. As 67.9% of respondents attended daytime school and 30.3% of them attended nighttime one, their school time shows a little difference. In a question about relation ship, one answered "Harmonious" took largest proportion by 72.6% during training, and about the degree of satisfaction of campus life who answered "normal" were the most with 59.4%. 2. About the reason choosing dental technology as a major, 41.1% taken the most answered "due to the specialized job", "Getting job easily" was second with 26.9%, and third was "recommended from around" with 18.3%. 50.3% of the respondents answered "normal" about the Satisfaction of their major, student marked in grade "B" most with 51.4% 3. In a investigation result about clinical training statues and preference, most(72.6%) choose place less than 10 for clinical training, and 60.6% of them resided own home. About their commuting time from home to training place, 44% was under 30min, 40% took time 30-60min. It shows students prefer shotter distance in terms of choosing training place. 4. Each part manager took large proportion as a clinical trainer with 33.7%, Training curriculum reform and developing method were most answer as a improvement measure after completing training with 30%. 5. The average of total score about clinical training was 3.15 of 5. In the detailed question, 'satisfaction of clinical training' got 3.38 as a highest score, the lowest score was 2.86 that is about satisfaction of clinical training period. The average score about efficiency of study was 2.86 and in detailed question, 'a Role model' got 3.26 as a highest score and participation of student got 3.05 as a lowest score. 6. The result of T-test to see the difference of the satisfaction according to the general character and clinic training condition between teaching efficiency is that the degree of satisfaction of clinical training showed statistical significance only in the degree of satisfaction of campus life(p<0.05), and teaching efficiency has a statistical significance with their age, grade, and satisfaction of campus life (p<0.05). 7. The relation between of teaching efficiency of clinical training and satisfaction of clinical training of dental technologic student has a statistical meaning in significance leveler 0.01. Now, therefore we suggest following based on these result. 1. To elevate satisfaction of clinical training, it agentry needs development of consistent clinical training curriculum. 2. To grasp the satisfaction and requirement, in needs to measure anxiousness and satisfactory degree after completing training 3. To train efficiently and evaluate efficiency over the teaching activities, it needs to develop measuring tools for teaching efficiency in terms of teacher's important rules in a clinical training. 4. Strengthen the relations with the study developing and managing curriculum gathering theoretical knowledge and practice. And make an effort to apply to their students. 5. Let the trainee take a class setting a belief, sense of value, function and obtain behavior by making the students comfort over clinical training as increasing teaching efficiency.

• Cross-Cultural Studies
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• v.26
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• pp.465-485
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• 2012

Instructing "History of Spanish Literature" class faces various types of limits and obstacles, just as other foreign language literature history classes do. Majority of students enter the university without having any previous spanish learning experience, which means, for them, even the interpretation of the text itself can be difficult. Moreover, the fact that "History of Spanish Literature" is traced all the way back to the Middle Age, students encounter even more difficulties and find factors that make them feel the class is not interesting. To list several, such factors include the embarrassment felt by the students, antiquated expressions, literature texts filled with deliberately broken grammars, explanations written in pretentious vocabularies, disorderly introduction of many different literary works that ignores the big picture, in which in return, reduces academic interest in students, and finally general lack of interest in literate itself due to the fact that the following generation is used to visual media. Although recognizing such problem that causes the distortion of the value of our lives and literature is a very imminent problem, there has not even been a primary discussion on such matter. Thus, the problem of what to teach in "History of Spanish Literature" class remains unsolved so far. Such problem includes wether to teach the history of authors and literature works, or the chronology of the text, the correlations, and what style of writing to teach first among many, and how to teach to read with criticism, and how to effectively utilize the limited class time to teach. However, unfortunately, there has not been any sorts of discussion among the insructors. I, as well, am not so proud of myself either when I question myself of how little and insufficiently did I contemplate about such problems. Living in the era so called the visual media era or the crisis of humanity studies, now there is a strong need to bring some change in the education of literature history. To suggest a solution to make such necessary change, I recommended to incorporate the visual media, the culture or custom that students are accustomed to, to the class. This solution is not only an attempt to introduce various fields to students, superseding the mere literature reserch area, but also the result that reflects the voice of students who come from a different cultural background and generation. Thus, what not to forget is that the bottom line of adopting a new teaching method is to increase the class participation of students and broaden the horizon of the Spanish literature. However, the ultimate goal of "History of Spanish Literature" class is the contemplation about humanity, not the progress in linguistic ability. Similarly, the ultimate goal of university education is to train students to become a successful member of the society. To achieve such goal, cultural approach to the literature text helps not only Spanish learning but also pragmatic education. Moreover, it helps to go beyond of what a mere functional person does. However, despite such optimistic expectations, foreign literature class has to face limits of eclecticism. As for the solution, as mentioned above, the method of teaching that mainly incorporates cultural text is a approach that fulfills the students with sensibility who live in the visual era. Second, it is a three-dimensional and sensible approach for the visual era, not an annotation that searches for any ambiguous vocabularies or metaphors. Third, it is the method that reduces the burdensome amount of reading. Fourth, it triggers interest in students including philosophical, sociocultural, and political ones. Such experience is expected to stimulate the intellectual curiosity in students and moreover motivates them to continues their study in graduate school, because it itself can be an interesting area of study.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.95-103
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• 2019

Temperature and relative humidity are important factors in crop cultivation and should be properly controlled for improving crop yield and quality. In order to control the environment accurately, we need to predict how the environment will change in the future. The objective of this study was to predict air temperature and relative humidity at a future time by using a multilayer perceptron (MLP). The data required to train MLP was collected every 10 min from Oct. 1, 2016 to Feb. 28, 2018 in an eight-span greenhouse ($1,032m^2$) cultivating mango (Mangifera indica cv. Irwin). The inputs for the MLP were greenhouse inside and outside environment data, and set-up and operating values of environment control devices. By using these data, the MLP was trained to predict the air temperature and relative humidity at a future time of 10 to 120 min. Considering typical four seasons in Korea, three-day data of the each season were compared as test data. The MLP was optimized with four hidden layers and 128 nodes for air temperature ($R^2=0.988$) and with four hidden layers and 64 nodes for relative humidity ($R^2=0.990$). Due to the characteristics of MLP, the accuracy decreased as the prediction time became longer. However, air temperature and relative humidity were properly predicted regardless of the environmental changes varied from season to season. For specific data such as spray irrigation, however, the numbers of trained data were too small, resulting in poor predictive accuracy. In this study, air temperature and relative humidity were appropriately predicted through optimization of MLP, but were limited to the experimental greenhouse. Therefore, it is necessary to collect more data from greenhouses at various places and modify the structure of neural network for generalization.

• (The)Study of the Eastern Classic
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• no.69
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• pp.563-592
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• 2017

This paper is to examine philosophy of Jurye(周禮, national rituals) described on GyeongJeMunGam and GyeongJeMunGamByeolJip. As it is widely known, Sambong Jeong Do-Jeon (三峯 鄭道傳), regardless of evaluation by posterity, is definitely a figure who established 500 years of Joseon with almost everything handled by his own hands from presenting founding principle of Joseon to organizing the bureaucratic system. In the third year of King Taejo (1394) with Jurye as an ideological model for social innovation, Jeong Do-Jeon wrote Joseongyeonggukjeon and offered it to the king. Joseongyeonggukjeon is a sort of guide for new codes written by Jeong Do-Jeon as a part of defining culture and institutions of the new dynasty, which is based on Confucianism, the ruling idea of the new dynasty. GyeongJeMunGam supplements the section ChiJeon(治典: Articles for Governing) of JoSeonGyeongGukJeon(the first constitution of Joseon Dynasty) mainly to specify the duties and jobs of the prime minister; and also the duties and jobs of the highest secretaries of the kings, and provincial and county governors, whereas GyeongJeMunGamByeolJip consists of the section GunDo specifying the duties and jobs of the kings and the section Euiron additionally explaining about the kings' duties and jobs in the viewpoint of the philosophy of the Book of Change. That is, GyeongJeMunGam finely describes not only the changes, advantages and disadvantages of prime minister system of every dynasty of China and Korea but also the prime minister's duties/jobs and attitude for kings; and it also specifies the duties and jobs of the kings' highest secretaries, guards, provincial and county governors; on the other hand, GyeongJeMunGamByeolJip says that the king should play the symbolic figure setting their mind in right ways and train themselves with virtue through the idea of GunJuSuShin (君主修身: ) to point out a good and capable prime minister and make him govern the country without using their power fully.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.