• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.67-77
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• 2020

Traditionally nuclear thermal hydraulic and nuclear safety has relied on numerical simulations to predict the system response of a nuclear power plant either under normal operation or accident condition. However, this approach may sometimes be rather time consuming particularly for design and optimization problems. To expedite the decision-making process data-driven models can be used to deduce the statistical relationships between inputs and outputs rather than solving physics-based models. Compared to the traditional approach, data driven models can provide a fast and cost-effective framework to predict the behavior of highly complex and non-linear systems where otherwise great computational efforts would be required. The objective of this work is to develop an AI algorithm to predict the peak fuel cladding temperature as a metric for the successful implementation of FLEX strategies under extended station black out. To achieve this, the model requires to be conditioned using pre-existing database created using the thermal-hydraulic analysis code, MARS-KS. In the development stage, the model hyper-parameters are tuned and optimized using the talos tool.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.420-424
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• 1993

New conditions for the exponential stability for both linear nonautnomous finite and a class of infinite dimensional systems described by parabolic partial differential equations (PDE's) are derived. The results for the parabolic systems are derived via semigroup approach.

• 시스템엔지니어링워크숍
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• s.1
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• pp.32-39
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• 2003

This work describes a study of analysis and evaluation activities applied systems engineering approach. It is presented technique of derivation and management requirement. A scheme of the defence project analysis and evaluation using a systems engineering process is described.

• Molecular & Cellular Toxicology
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• v.3 no.sup4
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• pp.37.5-37.5
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• 2007

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.620-630
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• 2005

This paper presents a digital controller for a single phase UPS inverter under two main considerations: (i) the overall system shall keep very low AC-voltage tracking error as well as no phase delay over different load conditions, and (ii) the digital controller shall be employed at a fixed sampling time. We propose that the former can be achieved by the proposed controller using the error-state approach and the latter can be dealt with by the socalled characteristics ration assignment.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.271-281
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• 2003

In this paper, a new nonlinear programming approach is suggested to solve biaffine matrix inequality (BMI) problems in multiobjective and structured controls. It is shown that these BMI problems are reduced to nonlinear minimization problems. An algorithm that is easily implemented with existing convex optimization codes is presented for the nonlinear minimization problem. The efficiency of the proposed algorithm is illustrated by numerical examples.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.176-182
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• 2012

This paper presents a new approach to risk comparison in uncertain environment. Based on the uncertainty theory, some uncertain risk measures and risk comparison rules are proposed. Afterward the bridges are built between uncertain risk measures and risk comparison rules. Finally, several comparable examples are given.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.458-463
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• 1997

In this paper, we propose a variable structure control approach for the system with matched and unmatched uncertainty. By using time-varying sliding mode, the reaching mode is removed, and the design methodology represents a realistic design approach with quadratic criterion for systems incorporating both matched and unmatched uncertainties. The criterion contains states and linear part of input for all time. The practical application of the control strategy is presented in the design of a stability augmentation system for an aircraft is presented.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.169-172
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• 2001

In recent years, many studies regarding the modeling of fuzzy system have been conducted. In this paper, a new computational approach to modeling of linguistic fuzzy system is proposed The fuzzy system is modeled as a combination of affine systems, The proposed method can be used in a rigorous stability analysis of fuzzy system including the linguistic fuzzy controller.