• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2942-2960
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• 2022

The core of cognitive radio is the problem concerning intelligent decision-making for communication parameters, the objective of which is to find the most appropriate parameter configuration to optimize transmission performance. The current algorithms have the disadvantages of high dependence on prior knowledge, large amount of calculation, and high complexity. We propose a new decision-making model by making full use of the interactivity of reinforcement learning (RL) and applying the Q-learning algorithm. By simplifying the decision-making process, we avoid large-scale RL, reduce complexity and improve timeliness. The proposed model is able to find the optimal waveform parameter configuration for the communication system in complex channels without prior knowledge. Moreover, this model is more flexible than previous decision-making models. The simulation results demonstrate the effectiveness of our model. The model not only exhibits better decision-making performance in the AWGN channels than the traditional method, but also make reasonable decisions in the fading channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권2호
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• pp.647-669
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• 2016

Multiple attribute for decision making including user preference will increase the complexity of route selection process. Various approaches have been proposed to solve the optimal route selection problem. In this paper, multi attribute decision making (MADM) algorithms such as Simple Additive Weighting (SAW), Weighted Product Method (WPM), Analytic Hierarchy Process (AHP) method and Total Order Preference by Similarity to the Ideal Solution (TOPSIS) methods have been proposed for acoustic signature based optimal route selection to facilitate user with better quality of service. The traffic density state conditions (very low, low, below medium, medium, above medium, high and very high) on the road segment is the occurrence and mixture weightings of traffic noise signals (Tyre, Engine, Air Turbulence, Exhaust, and Honks etc) is considered as one of the attribute in decision making process. The short-term spectral envelope features of the cumulative acoustic signals are extracted using Mel-Frequency Cepstral Coefficients (MFCC) and Adaptive Neuro-Fuzzy Classifier (ANFC) is used to model seven traffic density states. Simple point method and AHP has been used for calculation of weights of decision parameters. Numerical results show that WPM, AHP and TOPSIS provide similar performance.

• 한국시뮬레이션학회논문지
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• 제23권4호
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• pp.203-210
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• 2014

본 연구는 생산공정운영시 발생하는 담당자의 의사결정 지원을 위한 학습형 공정 의사결정 시스템 구축방법에 대한 것이다. 먼저 추출 및 누적된 각 공정 별 이력 데이터에서, 주요한 주요자원(Critical Resource)을 단계적 회귀법에 따라 선정한다. 선정된 주요자원을 독립변수로 취급하여 담당자의 의사결정 대상이 되는 공정운영 성과를 종속변수로 하는 회귀모형을 산출하고, 해당 주요자원으로 구성된 시뮬레이션 모형을 설계한다. 메타휴리스틱 방법을 통하여 의사결정 시점의 생산계획 및 목적에 대한 시뮬레이션 분석을 실행하고, 복수 대안 및 가능해(기대성과)를 산출한다. 각각의 대안에서 주요자원 별 회귀모형을 구성하는 분석 값을 회귀식에 대입하고, 여기에서 얻어지는 값과 시뮬레이션 분석에 의해 산출된 가능해 간의 비교를 통하여 그 차이가 가장 작은 대안을 최적대안으로 선정하고 실제 공정운영 의사결정에 반영하여 생산을 실시한다. 이때 발생하는 공정 이력 데이터들은 이후 의사결정을 위한 회귀모형에 피드백 된다.

• 정보처리학회논문지B
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• 제16B권4호
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• pp.327-331
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• 2009

퍼지 논리에서 불확실성의 병합은 일반적으로 t-norm 과 t-conorm 같은 연산자에 의해 수행된다. 그러나 기존의 병합 연산자는 다음과 같은 단점을 가지고 있다 : 첫째, 그들은 상황에 독립적이다. 결과적으로 동적 병합 과정에 적절히 적용하기 어렵다. 둘째, 의사결정 과정에의 직관적 연결성을 제공하지 못한다. 이러한 문제점을 해결하기 위해 의사결정 과정에서 옵션들의 강점 정도를 반영해 주는 퍼지 다차원 의사결정분석에 기반을 둔 $\varepsilon$-AMDA 알고리즘을 제안한다. $\varepsilon$-AMDA 알고리즘은 옵션의 강점 정도를 나타내 주는 매개변수의 값에 따라 최소값(옵션의 최약점)과 최대값(옵션의 최강점) 사이에서 적응적인 병합 결과를 생성한다. 이러한 관점에서 이는 동적 병합에 적용될 수 있다. 또한, 의사결정을 위한 퍼지 다차원 의사결정 분석에 대한 메커니즘을 제공하고 의사결정 과정에의 직관적 연결성을 제공한다. 결과적으로 제안된 방법은 의사결정자가 옵션의 강점 정도에 따라 적절한 의사결정을 하도록 지원할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.485-488
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of ruler from human operators. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.1107-1109
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• 2007

Context-based access control is an emerging approach for modeling adaptive solution, making access control management more flexible and powerful. However, these strategies are inadequate for the increased flexibility and performance that ubiquitous computing environment requires because such systems can not utilize effectively all benefit from this environment. In this paper, we propose a solution based on risk to make use of many context parameters in order to provide good decisions for a safety environment. We design a new model for risk assessment in ubiquitous computing environment and use risk as a key component in decision-making process in our access control model.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1996년도 제10회 동계학술발표회 논문집
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• pp.241-264
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• 1996

This article introduces the five functions of the national innovation system (NIS). As the national innovation system is a kind of social systems in the national level, the five generic functions of open system-production boundary spanning, maintenance, adaptation management functions-are applied to the NIS. The production function is the primary process, which produces innovative products and services of the NIS. The boundary spanning function is the function of procuring the input and disposing the innovation output or aiding in these process. Experienced R&D human resources, R&D funds, technology etc. belong to the input of the NIS. The maintenance function is responsible for the smooth operation and upkeep of the system in terms of various conditions. The adaptive function is to help the system change and adapt, scan the environment for problems, opportunities, and technological developments. It faces outward for the survival of the system from the long-term view. The management function carries out planning and controlling the overall activities for the other four functions in order to run the system. Finally it discuses implications for the diagnosis and the decision making process of S&T policy.

• 한국초지조사료학회지
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• 제41권3호
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• pp.189-197
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• 2021

Climate change effects are particularly apparent in many cool-season grasslands in South Korea. Moreover, the probability of climate extremes has intensified and is expected to increase further. In this study, we performed climate change vulnerability assessments in cool-season grasslands based on the analytic hierarchy process method to contribute toward effective decision-making to help reduce grassland damage caused by climate change and extreme weather conditions. In the analytic hierarchy process analysis, vulnerability was found to be influenced in the order of climate exposure (0.575), adaptive capacity (0.283), and sensitivity (0.141). The climate exposure rating value was low in Jeju-do Province and high in Daegu (0.36-0.39) and Incheon (0.33-0.5). The adaptive capacity index showed that grassland compatibility (0.616) is more important than other indicators. The adaptation index of Jeollanam-do Province was higher than that of other regions and relatively low in Gangwon-do Province. In terms of sensitivity, grassland area and unused grassland area were found to affect sensitivity the most with index values of 0.487 and 0.513, respectively. The grassland area rating value was low in Jeju-do and Gangwon-do Province, which had large grassland areas. In terms of vulnerability, that of Jeju-do Province was lower and of Gyeongsangbuk-do Province higher than of other regions. These results suggest that integrating the three aspects of vulnerability (climate exposure, sensitivity, and adaptive capacity) may offer comprehensive and spatially explicit adaptation plans to reduce the impacts of climate change on the cool-season grasslands of South Korea.