• Journal of Information Science Theory and Practice
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• v.7 no.4
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• pp.56-64
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• 2019

Planting intercropping in rubber plantations is another alternative for generating more income for farmers. However, farmers still lack the knowledge of choosing plants. In addition, information for decision making comes from many sources and is knowledge accumulated by the expert. Therefore, this research aims to create a decision support system for growing rubber trees for individual farmers. It aims to get the highest income and the lowest cost by using semantic web technology so that farmers can access knowledge at all times and reduce the risk of growing crops, and also support the decision supporting system (DSS) to be more intelligent. The integrated intercropping ontology and rule are a part of the decision-making process for selecting plants that is suitable for individual rubber plots. A list of suitable plants is important for decision variables in the allocation of planting areas for each type of plant for multiple purposes. This article presents designing and developing the intercropping ontology for DSS which defines a class based on the principle of intercropping in rubber plantations. It is grouped according to the characteristics and condition of the area of the farmer as a concept of the rubber plantation. It consists of the age of rubber tree, spacing between rows of rubber trees, and water sources for use in agriculture and soil group, including slope, drainage, depth of soil, etc. The use of ontology for recommended plants suitable for individual farmers makes a contribution to the knowledge management field. Besides being useful in DSS by offering options with accuracy, it also reduces the complexity of the problem by reducing decision variables and condition variables in the multi-objective optimization model of DSS.

• IE interfaces
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• v.11 no.2
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.176-183
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• 2006

A novel intelligent anti-collision decision-making supporting system is addressed in this paper. To obtain precise anti-collision information capability, an innovative neurofuzzy network is proposed and applied. A fuzzy set interpretation is incorporated into the network design to handle imprecise information. A neural network architecture is used to train the parameters of the Fuzzy Inference System (FIS). The learning process is based on a hybrid learning algorithm and off-line training data. The training data are obtained by trial manoeuvre. This neurofuzzy network can be considered to be a self-learning system with the ability to learn new information adaptively without forgetting old knowledge. This supporting system can decrease ship operators' burden to deal with bridge data and help them to make a precise anti-collision decision.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.111-120
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• 1999

Although the concept of viewing knowledge as a critical resource has been widely accepted in prior studies, it is not fully understood how to acquire available knowledge in order to improve organizational effectiveness. However, it si sure that organizational knowledge management should pursuit the achievement of the business goal by delivering relevant and useful information to the right person at the right time. Group Support System (GSS) can play an important role to transfer scatter information into meaningful business knowledge for supporting strategic corporate decision-making. This study proposes a fuzzy GSS framework for acquiring workgroup knowledge from individual memory and aggregating workgroup knowledge to organizational knowledge. This study also proposes an architecture to support the fuzzy GSS framework. The architecture consists of user agents, information management agents, and a fuzzy model manager. To illustrate how the fuzzy GSS framework can be used to support the whole process of organization knowledge acquisition, an Internet-based GSS was developed and applied in a marketing decision process. It showed that the framework was effective for acquiring organizational knowledge.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.1-17
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• 2001

This paper deals with an agent-based decision-supporting system for Taguchi experiment planning. Among the four major parts of Taguchi experiment, the planning phase includes the most important decision-making issues such as determination of experiment objectives, quality characteristics, and control factors. The planning phase, however, has not been paid proper attention by experiment designers. In this research, an agent-based decision-supporting system for Taguchi experiment planning has been developed to facilitate the planning tasks of experiment designer. The decision-supporting system is composed of two agent-based mechanisms. The first employs an Internet agent that collects the domain knowledge from knowledge providers who may be distributed in remote places. Another agent then visualizes the collected knowledge and reports it to the experiment designer. Engineers who would normally have difficulties in collaborating because of limitations on their time or because they are in different places can easily work together in the same experiment team and brainstorm to make good decisions. The second agent-based mechanism offers context-sensitive advice generated by another intelligent agent during the experiment planning process. it prevents the experiment designer from making improper decisions, which will increase the feasibility of the experiment and minimize the unnecessary expense of time and resources.

• Journal of Physiology & Pathology in Korean Medicine
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• v.28 no.1
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• pp.113-121
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• 2014

With the development of information technology, knowledge information-oriented and information systems are being rapidly paced. In addition, doctor's needs of the system that assist decision making is gradually increasing. Because the complex process of decision-making should be a lot. We propose a web based system for supporting medical treatment based on Korean medicine ontology. There are three kinds of processes. First, a pattern is decided for patient' symptoms, a formula for the pattern is selected and medicinal materials constituting the formula is added or removed. Second, a formula is decided for patient' symptoms, medicinal materials constituting the formula is added or removed. Third, a Treat method is decided for patient' symptoms, medicinal materials constituting the formula is added or removed. We have designed and implemented the clinical decision support system that supports flexible processes and necessary information and functions. The system shows the appropriate form of ontology knowledge as interrelated and provide analysis and processing, does not show simply search. The system is one of the systems utilizing ontology and a web based system that can be used in anywhere. Therefore, This system Will be useful as for doctors to make decision.

• Journal of Information Science Theory and Practice
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• v.11 no.2
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• International Commerce and Information Review
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• v.8 no.3
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• pp.3-21
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• 2006

This study aims to explore the developing strategies of knowledge based industry in ChunChon Area. This study suggests several strategies for promoting local development in Chunchon Area as follows ; first, building of local innovation system in chunchon area and convergence and diffusion of knowledge based industries. second, making of industrial environment suitable to developing knowledge based industries. third, the establishment of overall industrial supporting systems. fourth, expansion of industrial infra and prevention of the brain drain. fifth, transformation of industrial complex into innovation clusters. The result of this study will be useful for the chief executives officers to make more rational decision making for industrial developing strategies is related to the Knowledge based Industries. The paper also strives to provoke debate in this area with to encouraging further research on the topic.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.97-106
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• 2012

In the past, executive managers made a decision based on personal experience and knowledge due to lack of the appropriate and timely information. With the development of information systems and technologies, efficiency and productivity of business operation has been enhanced. In this study, we propose a system design and architecture blue-print related to strategic decision making support system. The proposed system consists of 3 key parts; individual business feasibility test, business portfolio feasibility test, business portfolio management. The three key parts are comprised of 11 components to generate information and knowledge based on various data input from inside and outside of firm. This system is expected to provide objective and reliable output to users. In addition, the proposed strategic decision support system would help respond to a rapidly changing business environment.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.83-92
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• 2012

The development of science and technology oriented knowledge society accelerates the convergence between scientific theory and industrial technology and increases the complexity problem of social and economic sectors. These cause the difficulty of securing the reliability and objectivity of science and technology policy. These also are barriers of balanced evaluation between rational science and technology policy making, management, and policy coordination. In this regard, Advanced countries in science and technology develops policy support system and promotes the program of evidence-based SciSIP(Science of Science and Innovation policy) together. This paper introduces a new approach developing science service of science and technology policy utilizing business intelligence technology in Korea. Also, it proposes the integration method of policy knowledge base and component-based service supporting S&T policy decision-making process and introduces services case studies.