• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.477-491
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• 1997

A new predictive classification rule for assigning future cases into one of two multivariate normal population (with unknown normal mixture model) is considered. The development involves calculation of posterior probability of each possible normal-mixture model via a default Bayesian test criterion, called intrinsic Bayes factor, and suggests predictive distribution for future cases to be classified that accounts for model uncertainty by weighting the effect of each model by its posterior probabiliy. In this paper, our interest is focused on constructing the classification rule that takes care of uncertainty about the types of covariance matrices (homogeneity/heterogeneity) involved in the model. For the constructed rule, a Monte Carlo simulation study demonstrates routine application and notes benefits over traditional predictive calssification rule by Geisser (1982).

• Transactions of Materials Processing
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• v.17 no.8
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• pp.579-585
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• 2008

Numerous experimental investigations on metallic materials and solid polymers have shown that relaxation behavior is nonlinearly dependent on prior strain rate. The stress drops in a constant time interval nonlinearly increase with an increase of prior strain rate. And the relaxed stress associated with the fastest prior strain rate has the smallest stress magnitude at the end of relaxation periods. This paper deals with the performance of three classes of unified constitutive models in predicting the characteristic behaviors of relaxation. The three classes of models are categorized by a rate sensitivity of kinematic hardening rule. The first class uses rate-independent kinematic hardening rule that includes the competing effect of strain hardening and dynamic recovery. In the second class, a stress rate term is incorporated into the rate-independent kinematic hardening rule. The final one uses a rate-dependent format of kinematic hardening rule.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.1
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• pp.37-45
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• 1990

In this paper, a knowledge base editor is presented as a supporting environment for an expert system building tool, OPS5. The knowledge base editor is especially useful for the fast and easy development of a knowledge base when the OPS5 production language is used. This knowledge base editor has some special facilities such as syntax and type checking, rule browsing and automatic bokkeeping. The syntax and type checking provides the facilities to find syntax and type errors in an edited knowledge base, respectively. The rule browsing facility offers various pattern matching schemes to see the causes and effects of a concerned rule. Automatic bookkeeping keeps the updated date and user name of a rule for the later reference whenever a user adds or changes a rule.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.67-72
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• 1991

This paper evaluates thequality of synthesized speech by rule using the LPC CD in the objective measure and then compares the result with the subjective analysis. By evaluating the quality of synthesized speech by rule objectively. We have tried to resolve the problems (Evaluation time or size expansion, variables within the analysis results) that arise when the evaluation is done subjectively. Also by comparing intelligibility-the index for the subjective quality evaluation of synthesized speech by rule-with evaluation results obtained using MOS and the objective evaluation. We have proved the validity of the objective analysis and thus provides a guide that would be useful when R&D and marketing of synthesis by rule method is done.

• Journal of the military operations research society of Korea
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• v.26 no.2
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• pp.55-74
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• 2000

A knowledge-based with production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a method to reflect the dynamic nature of a system when we make inferences with a knowledge-based system. This paper suggests a strategy of dynamic inference that can be used to take into account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy production rules. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by the AHP(Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected in an inference with fuzzy production systems.

• Korean Management Science Review
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• v.10 no.1
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• pp.171-192
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• 1993

In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule is presented. The MDR dispatching rule has been designed to maximize utilization of resources in a resource-constrained job shop with general precedence constraints. In shown that solving the above scheduling problem with the MDR dispatching rule is equivalent to multiple solving of the maximum clique problem. A graph theoretic approach is used to model the latter problem. The pairwise counting heuristic of computational time complexity O(n$^{2}$) is developed to solve the maximum clique problem. An attempt is made to combine the MDR dispatching rule with the existing look-ahead dispatching rules. Computational experience indicates that the combined MDR dispatching rules provide solutions of better quality and consistency than the dispatching rules tested in a resource-constrained job shop.

• Journal of Information Technology Services
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• v.2 no.2
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• pp.63-73
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• 2003

Insurance system has a lot of decision factors which are affected by the kinds of insurance products. and has the features of many exceptions. Since in applying the product attributes to the current system the value definition through tables and the exception treatment logic (if then else) are used in parallel, the cost of a product change and a new product development becomes increased and the prompt market reaction is difficult. In this paper, we propose the well formed rule base system which makes data for the business logic of insurance attributes and discuss the benefit of application of this system to the real project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.19-26
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• 2010

In this paper, we propose an efficient decision rule in order to get better chance to detect the unused spectrum assigned to a licensed user and improve reliability of spectrum sensing performance. Each secondary user receives the signals from the licensed user. And the resulting signals input to an energy detector. Then, each sensing result is combined and used to make a decision whether the primary user is present at the licensed spectrum band or not. In order to make the reliable decision, we apply an efficient decision rule that is called as a majority rule in this paper. The simulation results show that spectrum sensing performance with the proposed decision rule is more reasonable and efficient than that with conventional decision rules.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.207-216
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• 2005

One of the well-studied problems in data mining is the search for association rules. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. There are three criteria of association rule; support, confidence, lift. The goal of association rule mining is to find all the rules with support and confidence exceeding some user specified thresholds. We can know there is association between two items by the criteria of association rules. But we can not know the degree of association between two items. In this paper we examine the relation between the measures of association and the criteria of association rule for ordinal data.

• Review of KIISC
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• v.5 no.2
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• pp.32-48
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• 1995

Our paper describes an Intrusion Detection Parallel System(IDPS) which detects an anomaly activity corresponding to the actions that interaction between near detection events. IDES uses parallel inductive approaches regarding the problem of real-time anomaly behavior detection on rule-based system. This approach uses sequential rule that describes user's behavior and characteristics dependent on time. and that audits user's activities by using rule base as data base to store user's behavior pattern. When user's activity deviates significantly from expected behavior described in rule base. anomaly behaviors are recorded. Observed behavior is flagged as a potential intrusion if it deviates significantly from the expected behavior or if it triggers a rule in the parallel inductive system.