• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.27-30
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• 2018

We design an expert system for tomato smart farm using decision trees and construct a control system with decision structure similar to that of farmers by using the data generated by factors that vary depending on the surrounding environment of each house. At present, Smart farm's control system does not control itself like the way farmers have done so far. Therefore, the dependency of smart farm control system is still not high. Direct intervention by farmers is indispensable for environmental control based on surrounding environment such as sensor value in smart farm. Therefore, we aimed to design a controller that incorporates decision trees into the expert system to make a system similar to the decision making of farmers. Prior to controlling the equipment in the house, it automatically selects the most direct effect among the various environmental factors, and then builds an expert system for complex control by including criteria for decision making by farmers. This study focused on deriving results using data without using heavy tools. Data is coming out of many smart farms at present. We expect this to be a standard for a methodology that allows farmers to access quickly and easily and reduce direct intervention.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.496-507
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• 2001

An expert system for the diagnosis and indication of hypertension is implemented through HTML-based backward inference. HTML-based backward inference is performed using the hypertext function of HTML, and many HTML files, which are hyperlinked to each other based on the backward rules, should be prepared beforehand. The development and maintenance of the HTML files are conducted automatically using the decision graph. Still, the drawing and input of the decision graph is a time consuming and tedious job if it is done manually. So, automatic generator of the decision graph for the diagnosis and indication of hypertension was implemented. The HTML-based backward inference ensures accessibility, multimedia facilities, fast response, stability, easiness, and platform independency of the expert system. So, this research reveals that HTML-based inference approach can be used for many Web-based intelligent site with fast and stable performance.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.255-266
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• 1999

The purpose of this paper is to describe the design of the decision support system for container terminal ship planning and to introduce the implemented system. The ship planning in container terminals consists of three major decision processes -the working schedule of gantry cranes the discharging sequence of inbound containers the loading position and sequence of outbound containers. For making these decision the proposed system can provide two ship planning modes the interactive planning mode with user-friendly GUI and the automated planning made. To implement the automated planning routine we acquired the planning rules from the expert planner in container terminals and developed an expert system based on the rules. Finally we evaluated the system developed and the potential for commercialization by using container terminal data.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.13
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• pp.23-28
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• 1986

The qualitative aspects of decision making have been the toughest problems that could nor be easily manipulated and solved by the traditional management science techniques. The expert systems has been emerged as a powerful tool for handling such difficulties. In this article, the concept, the structure of the expert systems would be reviewed and the expert systems application to management would be discussed.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.532-539
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• 1996

Existing assessment methodologies present a considerable problem because of fuzzy situation of deterioration mechanism of concrete bridges; namely, qualitative, subjective or inconsistent. This paper discusses current assessment methods in aspect of uncertainty. The expert system, COBDA, is developed for consistent and fast assessment of deteriorantion of concrete bridges. Briefly introduced in this paper are the structure of expert system and several methodologies for decision making of deterioration situation and providing repair option. COBDA is configured by PROLOG for logic approach and expert system shell based on Bayesian subjective probability. The methodologies are illustrated and discussed by comparison of condition assessment results in a case study.

• Korean Journal of Remote Sensing
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• v.3 no.2
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• pp.115-119
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• 1987

After the introduction of the topologically structured geographic information system(GIS) with relational DBMS, the attribute data can be handled without considering locational data. By utilzing of the characteristic of the relational DBMS, it can be used as an expert system building tool in GIS. The relational DBMS of the GIS furnishes the data needed to perform deductive functions of the expert system, and the rule based approach provides the decision rules. Therefore, rule based approach with the expert judgement can be easily combined with relational DBMS.

• The Journal of Information Systems
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• v.1
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• pp.149-178
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• 1992

The field of Artificial Intelligence (AI) is growing, and many firms are investing in expert system, one of AI's subfields. An expert system is defined as a computer program designed to replicate some aspect of the decision making of one or more experts and to be used by nonexperts. The kernel of an expert system is the knowledge base, which consists of the facts and rules that represent the expert's knowledge. Firms need expert systems for training employees to provide competitive advantage. This paper describes the model of an instructional expert training system which interfaces to external programs, such as an ASCII file, a work-sheet program, and a database program. A model for such an expert training system, and its prototype have been developed to demonstrate its functionality. A modular knowledge base has been developed and implemented in support of this study. The modularized knowledge base offers the user an easy and quick maintenance of facts and rules, which are frequently required to change in future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.15-23
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• 2014

A Case Study on Venture and Small-Business Executives' Use of Strategic Intuition in the Decision Making Process This paper is a case study on how Venture and Small-Business Executives managers can take advantage of their intuitions in situations where the business environment is increasingly uncertain, a novel situation occurs without any data to reflect on, when rational decision-making is not possible, and when the business environment changes. The case study is based on a literature review, in-depth interviews with 16 business managers, and an analysis of Klein, G's (1998) "Generic Mental Simulation Model." The "intuition" discussed in this analysis is classified into two types of intuition: the Expert Intuition which is based on one's own experiences, and Strategic Intuition which is based on the experience of others. Case study strategic management intuition and intuition, the experts were utilized differently. Features of professional intuition to work quickly without any effort by, while the strategic intuition, is time-consuming. Another feature that has already occurred, one expert intuition in decision-making about the widely used strategic intuition was used a lot in future decision-making. The case study results revealed that managers were using expert intuition and strategic intuition differentially. More specifically, Expert Intuition was activated effortlessly, while strategic intuition required more time. Also, expert intuition was used mainly for making judgments about events that have already happened, while strategic intuition was used more often for judgments regarding events in the future. The process of strategic intuition involved (1) Strategic concerns, (2) the discovery of medium, (3) Primary mental simulation, (4) The offsetting of key parameters, (5) secondary mental simulation, and (6) the decision making process. These steps were used to develop the "Strategic Intuition Decision-making Model" for Venture and Small-Business Executives. The case study results further showed that firstly, the success of decision-making was determined in the "secondary mental simulation' stage, and secondly, that more difficulty in management was encountered when expert intuition was used more than strategic intuition and lastly strategic intuition is possible to be educated.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.35-52
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• 2021

Nowadays data-based decision making is emerging as the center of the business environment paradigm, but many companies do not have data-driven decision-making systems. It has also been studied that using an expert's intuition in decision making can be more efficient in terms of speed and cost, compared to analytical decision making. The goal of this study is to analyze customer churn factors using a group of experts within a financial company from the viewpoint of decision-making efficiency. We applied a debit card 'A', product of the National Credit Union Federation of Korea. The churn factors of all the financial expert groups were examined. Also. the difference in each group (management support, card recruitment, customer service group) was analyzed. We expect that this study will be helpful in the practical aspects of managers whose environments is lack data-oriented infrastructure and culture.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.159-177
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• 1995

The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.