• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.7
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• pp.30-41
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• 1992

As a general model of rule-based systems, we propose a model for a fuzzy production system having chaining rules and an inference engine associated with the model. The concept of so-called 'fuzzy petri nets' is used to model the fuzzy production system and the inference engine is designed to be capable of handling inexact knowledge. The fuzzy logic is adopted to represent vagueness in the rules and the certainty factor is used to express uncertainty of each rules given by a human expert. Parallel, inference schemes are devised by transforming Fuzzy Petri nets to matrix formula. Futher, the inference engine mechanism under the Mamdani's implication method can be desceribed by a simple algebraic formula, which makes real time inference possible.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.105-121
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• 2018

The hybrid electric powertrain is a robust solution that allows for major improvements in both fuel economy and emission reduction. In the present study, a through-the-road hybrid vehicle model with an electric motor driving the rear axle and an Internal Combustion Engine (ICE) driving the front axle has been constructed. We then present a systematic method for the determination of a real time applicable optimal Energy Management Strategy (EMS) for a hybrid road vehicle. More precisely, we compare the performance of rule-based EMS strategies to an optimization-based strategy, namely ECMS (Equivalent Consumption Minimization Strategy). The comparison is conducted in parallel with a parameterization of the size of the internal combustion engine and the implementation of a Continuously Variable Transmission (CVT) that allows following the line of best fuel economy. For the FTP-75 driving cycle, the constrained engine On-off control algorithm is shown to offer a 28% improvement potential of fuel consumption compared to the conventional internal combustion engine while the ECMS strategy achieves an improved potential of nearly 33%.

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.50-55
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• 2003

This paper presents an intelligent computer system, which can easily diagnose electrical fire causes, without the help of human experts of electrical fires diagnosis. For this system, a database is built with facts and rules driven from real electrical fires, and an intellectual database system which even a beginner can diagnose fire causes has been developed, named as an Electrical Fire Causes Diagnosis System : EFCDS. The database system has adopted, as an inference engine, a mixed reasoning approach which is constituted with the rule-based reasoning and the case-based reasoning. The system for a reasoning model was implemented using Delphi 3, one of program development tools, and Paradox is used as a database building tool. To verify effectiveness and performance of this newly developed diagnosis system, several simulated fire examples were tested and the causes of fire examples were detected effectively by this system. Additional researches will be needed to decide the minimal significant level of the solution and the weighting level of important factors.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.263-266
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• 1995

Comtputer Aided Process Planning(CAPP) has been emerged as playing a key role in Computer Integrated Manufactunng(CIM) as the most critical link to integrate CAD and CAM. A modified variant CAPP system based on process planning rule base is developed in this paper. This CAPP system generates process plans automatically according to the GT code data provided as input. In order to execute process planning, various process planning rules are constructed in the form of decision tree and the inference engine that extracts the process plan based on the tree-structured rules are implemented.

• The Journal of Society for e-Business Studies
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• v.12 no.1
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• pp.99-122
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• 2007

The rule based system is inference engine which can correspond quickly to new business model change and improvement requirement by dealing with the business know-how and expert knowledge as well as business process of enterprise and has been trying to apply to the various industries. As a part of application cases for rule-based system, we develop and implement the rule-based insurance product recommend and design system for the efficient decision making of insurance product in insurance industry which is sensitively affected by needs of customers, various kinds of product, and environment changes. The process of fuzzy inference of the developed system helps to recommend and design the proper Insurance product using the information of the present customer and the previous members. This approach is expected that it will be the core technology for the recommendation and design of the tailored insurance product by deciding and corresponding needs of various kinds of customer quickly in future insurance industry.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.27-33
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• 2017

To efficiently provide cloud computing services to users over the Internet, IT resources must be configured in the data center based on virtualization and distributed computing technology. This paper focuses specifically on the problem that new training data can be added at any time in a wide range of fields, and new attributes can be added to training data at any time. In such a case, rule generated by the training data with the former attribute set can not be used. Moreover, the rule can not be combined with the new data set(with the newly added attributes). This paper proposes further development of the new inference engine that can handle the above case naturally. Rule generated from former data set can be combined with the new data set to form the refined rule.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1329-1332
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• 1987

This paper describes a design of the expert system for diagnosis of abnormal gait patients. This system makes the rule-based representation that can easily extend the knowledge-base and naturally represent the uncertainty, and the inference engine that uses forward chaining which covers the reasoning from the first condition to the goal. The results of inferring various maladies using this system are as follows: 1) In cases of progressive muscular dystrophy, cerebral vascular accident, peripheral neuropathic lesion and peroneal nerve injury, the result of inference is the same as that of medical specialists' with 100% accuracy. 2) In cases of Neuritis, Paralysis agitan and Brain tumor, the accuracy of inference is less than 50% compared to that of medical specialists. With above results, we decide that the rule-based representations of some maladies ard accurate relatively, but that the correction and the extention of some rules and some methods of problem solving are required in order to construct the complete expert system for diagnosis of abnormal gait patients.

• New & Renewable Energy
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• v.4 no.4
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• pp.65-71
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• 2008

Considering the world's environmental problem, HEVs are projected as one of the solution. The keys of the HEV cruise control are expanding the use of electric motor and operating the internal combustion engine in the efficient region. This paper presents a new structure of SOC sustaining model where state-machine control is used. The proposed model defines battery charging and discharging as states and SOC of the battery as control variables. In this paper, we introduce various methods in deterministic rule-based control for HEV and describe a new SOC sustaining controller used by state-machine.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.34-40
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• 2005

In this paper we propose a turbojet engine controller of unmanned aircraft based on the Fuzzy-PI algorithm. To prevent any surge or a flame out event during the engine acceleration or deceleration, the PI-type fuzzy controller effectively controls the fuel flow input of the control system. The fuzzy inference rule made by the logarithm function of acceleration error improves the tracking error. Computer simulations applied to the linear model of a turbojet engine show that the proposed method has good tracking performance for the reference acceleration and deceleration commands.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.111-117
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• 2011

This paper suggests the passenger model considered evacuation behavioral characteristics on the passenger ship fire using a rules-based agent technique. The existing evacuation simulation system was modeled only passenger speed. The speed-based model considered passenger's physical characteristics, so it couldn't consider evacuation behavioral characteristics. For solving this problem, we modeled the passenger model using a rule-based agent applied evacuation behavioral characteristics. The rule-based agent consists of knowledge base and inference engine. In knowledge base, we represented evacuation behavioral characteristics, and chose the examples of the evacuation behavioral characteristics to show various patterns of behavior. And we simulated in the IMO MSC/Circ.1238 example 8 and we proved the simulation results could represent variety patterns of human behavior.