• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.563-573
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• 2018

An Expert Seasonal Prediction System for operational Seasonal Outlook (ESPreSSO) is developed based on the APEC Climate Center (APCC) Multi-Model Ensemble (MME) dynamical prediction and expert-guided statistical downscaling techniques. Dynamical models have improved to provide meaningful seasonal prediction, and their prediction skills are further improved by various ensemble and downscaling techniques. However, experienced scientists and forecasters make subjective correction for the operational seasonal outlook due to limited prediction skills and biases of dynamical models. Here, a hybrid seasonal prediction system that grafts experts' knowledge and understanding onto dynamical MME prediction is developed to guide operational seasonal outlook in Korea. The basis dynamical prediction is based on the APCC MME, which are statistically mapped onto the station-based observations by experienced experts. Their subjective selection undergoes objective screening and quality control to generate final seasonal outlook products after physical ensemble averaging. The prediction system is constructed based on 23-year training period of 1983-2005, and its performance and stability are assessed for the independent 11-year prediction period of 2006-2016. The results show that the ESPreSSO has reliable and stable prediction skill suitable for operational use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Journal of Information Technology Applications and Management
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• v.11 no.1
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• pp.117-135
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• 2004

Since human decision making behavior is likely to follow nonlinear strategy, it is conjectured that the human decision making behavior can be modeled better by nonlinear models than by linear models. All that linear models can do is to approximate rather than model the decision behavior. This study attempts to test this conjecture by analyzing human decision making behavior and combining the results of the analysis with predictive performance of both linear models and nonlinear models. In this way, this study can examine the relationship between the predictive performance of models and the existence of valid nonlinear strategy in decision making behavior. This study finds that the existence of nonlinear strategy in decision making behavior is highly correlated with the validity of the decision (or the human experts). The second finding concerns the significant correlations between the model performance and the existence of valid nonlinear strategy which is detected by Lens Model. The third finding is that as stronger the valid nonlinear strategy becomes, the better nonlinear models predict significantly than linear models. The results of this study bring an important concept, validity of nonlinear strategy, to modeling human experts. The inclusion of the concept indicates that the prior analysis of human judgement may lead to the selection of proper modeling algorithm. In addition, lens Model Analysis is proved to be useful in examining the valid nonlinearity in human decision behavior.

• Journal of Korean Society of Forest Science
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• v.99 no.1
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• pp.111-124
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• 2010

This study has intended to develop an evaluation model to select suitable locations of recreation forests in accordance with their types, and to apply the models to the feasibility study of selecting suitable recreation forest locations of candidate sites. To reach this goal, this study employed a Delphi expert survey method and Analytic Hierarchy Process (AHP) for the whole process of model building. And the followings are what this study has found during model building and application process. First, the assessment criteria for classifying recreation forests and selecting suitable locations were initially identified through justification process with two rounds of expert review, after broken down into 2 categories, and then further divided into 6 items and 12 indicators accompanying with hierarchical structure. Second, in the third phase of Delphi expert survey, the relative weights of the assessment criteria were derived by employing AHP. Through overlaying two evaluation categories including resource and usability, 4 types of recreation forest were presented. In the forth phase of the Delphi survey, this study has developed an evaluation model to select suitable locations of recreation forests in accordance with their types using relative weights of the selected indicators through. This study has applied the models to the feasibility study of selecting suitable recreation forest locations of candidate sites, and found that the usability of recreation forest was severely affected by the distance from the capital region, that the closer the locations of natural recreation forests from the capital region, the more advantageous. The developed model can be used to designate recreation forests in accordance with their types.

• Computational Structural Engineering
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• v.3 no.2
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• pp.97-108
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• 1990

An expert system for the preliminary design of the building structures, which is most important in the design stages, is modeled in this paper. Considering various factors such as structural safety, constructability, and architectural spacing as well as material cost, this expert system serves as a starting point for the building details.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1374-1375
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• 2011

Mixed combustion expert system is implemented to prevent various problems in combustion process by increasing rate of mixing low calorific value coal to reduce costs. This system shows optimal coal mixture rate by interfacing CBS(Coal Blending Screener, Implementing slagging and fouling factors by coal characteristic and algorithm), SGE(Stream Generate Expert, Combustion process model) and CFS(Configured Fireside Simulator, Computational fluid dynamics).

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.375-381
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• 2007

Cognitive map (CM) has long been used as an effective way of constructing the human thinking process. In literature regarding CM, a number of successful researches were reported, where CM based what-if analysis could enhance firm's performance. However, there exit very few researches investigating the CM generation method. Therefore this study proposes a GENCOM (Genetic Algorithm based Cognitive Map Generator). In this model combined with CM and GA, GA will find the optimal weight and input vector so that the CM generation. To empirically prove the effectiveness of GENCOM, we collected valid questionnaires from expert in S/W sales cases. Empirical results showed that GENCOM could contribute to effective CM simulation and very useful method to extracting the tacit knowledge of sales experts.

• Journal of Industrial Technology
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• v.15
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• pp.187-193
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• 1995

In this paper, a short-term load forecasting expert system considering the load variation due to the change in temperature is presented. The change in temperature is an important load variation factor that varies the normal load pattern. The conventional load forecasting methods by artificial neural networks have used the technique where the temperature variables were included in the input neurons of artificial neural networks. However, simply adding the input units of temperature data may make the forecasting accuracy worse, since the accuracy of the load forecasting in this method depends on the accuracy of weather forecasting. In this paper, the fuzzy expert system that modifies the forecasted load using fuzzy rules representing the relations of load and temperature is presented and compared with a conventional load forecasting technique. In the test case of 1991, the proposed model provided a more accurate forecast than the conventional technique.

• International Commerce and Information Review
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• v.6 no.2
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• pp.129-146
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• 2004

Nowadays, practical use of the internet is generalized in enterprise's business management as well as individual's everyday life. Also using internet, E-trade has given the very important meaning to company which do import and export as a part for extension of more opportunities and business scopes. In this study, I examined the actual conditions of industrial frame and information level in Gwangju Chonnam areas to achieve the easy and wide using of e-trade systems. Next, I examined the present condition and problem of education systems regarding e-trade expert incubator program of Gwangju Chonnam area. Finally, this study presented the successful cooperation model of Chosun university TI center in industrial section, educational section, and government section for more effective development systems of e-trade expert incubator program.

• Korean Journal of Computational Design and Engineering
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• v.22 no.1
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• pp.18-27
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• 2017

As building space constitution and layout are critical for satisfying the building owner and users, their optimization is so important in the design process. However it's not always simple to set up objective criteria for the space layout optimization for different requirements and the architects mostly depend on their own experience for these. This study is to suggest a way to make up for this issue by referencing and deducing the space layout based on the given BIM space information and existing knowledge. For this purpose, the Space Syntax is applied to extract the information from a space model and an Expert System is used to make the best use of the relevant knowledge. Based on the Integration indexes for all the spaces, we could compare the space layout alternatives and determine the best selection for different accessibility conditions.