• Management Science and Financial Engineering
• /
• v.10 no.1
• /
• pp.1-23
• /
• 2004

The changing structure of organization and the increasing diversity of business have forced organizations to have abilities to coordinate dispersed business activities. They have required cooperation and coordination among the functional units in the organization which should involve group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative process of group decision-making, they often lack the features supporting the dynamic complexity issue frequently occurring at group decision-making processes. This results in cognitive unfit between the group decision-making tasks and their supporting tools, bringing about mixed results in their effects on group decision-making. This study proposes system dynamics modeling as a group decision-making support tool to deal with the group decision -making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Journal of Biosystems Engineering
• /
• v.27 no.2
• /
• pp.161-172
• /
• 2002

Database as a supporting system for decision-making is one of essential parts for realizing precision farming. Application models on constructing a database for precision farming, including collection of spatial and attribute data, were suggested using a GPS, DXF files, AutoCAD, a Java application program and PostgreSQL DBMS in this study. The constructed spatial database based on the schema design of spatial and attribute data table was evaluated as a supporting system for decision-making by a simulation of a virtual variable-rate chemical applicator. The applicator could extract the values of soil property at its consecutive location in the tested field in communication with the constructed database, and prescribe the corresponding variable-rate of chemicals. The results of the study suggested the possibility that the constructed database can function a supporting system for decision-making for precision farming.

• Journal of the Korea Society for Simulation
• /
• v.12 no.1
• /
• pp.49-58
• /
• 2003

There have been growing recognition on the needs of coordination of diverse activities across cross-functional business areas necessarily involving group decision-making processes. Although many group decision-making support tools and methods have been introduced to enable the collaborative processes of group decision-making, they often lack features supporting the dynamic complexity issues. This study proposes system dynamics modeling approach based on simulation techniques to deal with the group decision-making tasks having properties of dynamic complexity.

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

• Journal of Intelligence and Information Systems
• /
• v.12 no.4
• /
• pp.127-136
• /
• 2006

This paper describes the result of a case study for developing an expert system framework in order to support Korean Army tactical C4I system. Korean Army had developed an expert system, STAFS(Situation & Threat Assessment Fusion Expert System), for supporting field intelligence analysis activities which has been implemented through traditional manual process inside the division level combat briefing room. STAFS, however, has serious limitations for supporting combat commander's decision making processes because of its limited capabilities, since the system had been developed for supporting only intelligence analysis function rather than for integrated combat decision making processes inside the combat briefing room. Thus, this paper proposed an integrated expert system framework for supporting the commander's decision making by addressing various activities implemented in the briefing room.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.958-965
• /
• 2003

The rapidly changing business environment has required cooperation and coorduiation among functional units n organizations which should Involve group decision-making processes Although many group derision-making support tools and methods have provided the collaborative capabilities for organizational members, they often lack features supporting the dynamic complexity issue frequently occurring at group decision-making processes This study proposes system dynamics modeling as a group decision-making support tool to deal with the group derision-making tasks having properties of dynamic complexity in terms of cognitive fit theory.

• Knowledge Management Research
• /
• v.10 no.3
• /
• pp.17-33
• /
• 2009

The emergence of the Internet shopping agent enabled consumers to enjoy Internet shopping more easily and quickly. Especially, the role of Internet shopping agent is becoming more important following the information overload trend on the Internet in that the consumers can promptly obtain information about a certain product and its price among countless items on the Internet. As a result, consumers can now enjoy shopping more easily, compared to the offline shopping which requires a lot of efforts in comparing the products and purchasing them. Since the Internet shopping agents collect extensive information about the products' price, delivery period, detailed characteristics, etc., and present a comparison table containing the information to the consumers, the consumers can shop more quickly at lower price using such shopping agents. However, it has not been sufficiently studied about how the various functions of shopping agents actually support consumers' purchase decision making procedure in everyday life, and if they do, in which stages they play a supporting role in consumers' purchase decision making system. Therefore, this study conducts an empirical analysis on the role of the Internet shopping agents in the purchase decision making process of the consumers, considering the Internet shopping agent as a decision making supporting system. Moreover, it analyzes how the effects of the Internet shopping agent differs according to the consumers' knowledge level about the products.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.4
• /
• pp.551-557
• /
• 2017

Commanders want to receive quickly scientific and analytic results about the battlefield situation. Unfortunately, decision support system of Army Tactical Command Information System(ATCIS) is restricted to message procedures and searching function based on manual work. In this paper, we propose applying Data Mining to ATCIS for supporting rapid decision making based on the scientific and analytic method. The purpose of this proposal is to efficiently execute the tactical planning and employment of the subordinate units in order to achieve the mission.

• Journal of the Ergonomics Society of Korea
• /
• v.17 no.1
• /
• pp.37-46
• /
• 1998

A human sensibility ergonomics design supporting system was applied to the product development for the customer's satisfaction based on ergonomics technology. The system is composed of three major subsystems such as customer's sensibility analysis, inference mechanism, and presentation technology. The main approaches of the system are to analyze customer's sensibilities and to translate them into product design elements. The purpose of this paper is to develop a design supporting system in which the relationship between customer's sensibility and product design elements is reasoned by a MADM(Multi-Attribute Decision Making) fuzzy model. In this model, three variables such as multiple correlation coefficients, partial correlation coefficients, and category scores were used in reasoning process. The weighted value of the words were also considered in fuzzy decision process. As a case study, the design supporting system with the MADM fuzzy model was applied to the personnel computer design.

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