• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년 학술대회 논문집 정보 및 제어부문
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• pp.181-183
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• 2006

This paper proposes an intelligent decision framework for update of the environment model using GSPN(generalized stochastic petri nets). The GSPN has several advantages over direct use of the Markov Process. The modeling, analysis, and performance evaluation are conducted on the mathematical basis. By adopting the probabilistic approach, our decision framework helps the robot to decide the time to update the map. The robot navigates autonomously for a long time in dynamic environments. Experimental results show that the proposed scheme is useful for service robots which work semi-permanently and improves dependability of navigation in dynamic environments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권1호
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• pp.20-28
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• 2012

We define a language $\mathcal{RS}$, a subclass of the scheduling language $\mathcal{RS}V$ (resource constrained project scheduling with variant processes). $\mathcal{RS}$ involves the determination of the starting times for ground activities of a project satisfying precedence and resource constraints, in order to minimize the total project duration. In $\mathcal{RS}$ ground activities and two structural symbols (operators) 'seq' and 'pll' are used to construct activity-terms representing scheduling problems. We consider three different variants for formalizing the $\mathcal{RS}$-scheduling problem, the optimizing variant, the number variant and the decision variant. Using the decision variant we show that the problem $\mathcal{RS}$ is $\mathcal{NP}$-complete. Further we show that the optimizing variant (or number variant) of the $\mathcal{RS}$-problem is computable in polynomial time iff the decision variant is computable in polynomial time.

• 품질경영학회지
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• 제34권3호
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• pp.31-40
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• 2006

Companies had to be more intelligent in order to survive in the rapidly changing environments. We need to make a decision to build the Information System to support the managers in their decision making. That is the reason many companies are tend to have Business Intelligence Systems. But, how can we know the new system would be better than the old system in making us intelligent? The answer is we can do it with the concept of Intelligence Density. In this study, Intelligence Density concept will be introduced, and the way how it can be applied to the information system will be presented. I think Intelligence Density should be studied more to help managers make right decisions for the DSS implementation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.283-286
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• 2003

Generally, the repeater in CDMA(Code Division Multiple Access) included HPA(HI-Power Amplifier) to amplifier communication signals. Also, HPA contained PD(Predistortor) to maintain the linearization of amplifier characteristics A configuration component of PD have been used electricity nonlinear devices such that diode. But this diode takes many influences at the circumstance temperature. Consequently, st can't maintain output linearization, and drop the communication Duality. The manufacturer set bias of the circuit to the manual at the first out of ware-house low. But the Q-point changes according to the change of the high temperature or low temperature. Therefore, we designed a system to maintain the Q-point by FDM(Fuzzy Decision Maker) in this paper.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 춘계학술대회 논문집
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.474-478
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• 1998

A new approach for the decision feedback equalizer(DFE) based on the back-propagation neural networks is described. We propose the method of optimal structure for back-propagation neural networks model. In order to construct an the optimal structure, we first prescribe the bounds of learning procedure, and the, we employ the method of incrementing the number of input neuron by utilizing the derivative of the error with respect to an hidden neuron weights. The structure is applied to the problem of adaptive equalization in the presence of inter symbol interference(ISI), additive white Gaussian noise. From the simulation results, it is observed that the performance of the propose neural networks based decision feedback equalizer outperforms the other two in terms of bit-error rate(BER) and attainable MSE level over a signal ratio and channel nonlinearities.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1342-1345
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• 1993

In the cellular mobile communications as decreasing the cell radius to increse the reuse factor of frequencies, the handoff requests are increasing so that the efficient handoff decision making becomes a crucial problem. In this simulation study, we evaluate a set of handoff algorithms based on fuzzy-multicriteria decision making. These algorithms uses the parameters including the received signal strength intensity, the bit error rate and the distance between a mobile station and a base station. We compare the fuzzy algorithms in terms of call block ratio and handoff request ratio and call force ratio, and show the applicability of those algorithms in the cellular mobile communication systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권2호
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• pp.140-145
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• 2008

In this paper, we constructed the advanced cargo monitoring system for liquid cargo tankers which embedded the Decision Support System (DSS) based on the International Ship Management Code (ISM Code). To make this system, we first organized a base of expert's knowledge concerning liquid tanker operations that largely affect ocean accidents. We can find out the knowledge via inference method which simply imitates the fuzzy inference method. Based on this expert's knowledge, we constructed the DSS that provides a code of conduct for operating cargo tanks safely. The proposed monitoring system could eliminate human error when confronting dangerous situations, so the system will help sailors to operate cargo tanks safely.

• 한국지능시스템학회논문지
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• 제20권3호
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• pp.434-440
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• 2010

In this paper, we define generalized induced linguistic aggregation operator called generalized induced linguistic ordered weighted harmonic mean(GILOWHM) operator. Each object processed by this operator consists of three components, where the first component represents the importance degree or character of the second component, and the second component isused to induce an ordering, through the first component, over the third components which are linguistic variables and then aggregated. It is shown that the induced linguistic ordered weighted harmonic mean(ILOWHM) operator and linguistic ordered weighted harmonic mean(LOWHM) operator are the special cases of the GILOWHM operator. Based on the GILOWHM and LWHM operators, we develop an approach to group decision making with linguistic preference relations. Finally, a numerical example is used to illustrate the applicability of the proposed approach.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.2086-2098
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• 2018

Security plays a vital role and is the key challenge in Mobile Ad-hoc Networks (MANET). Infrastructure-less nature of MANET makes it arduous to envisage the genre of topology. Due to its inexhaustible access, information disseminated by roaming nodes to other nodes is susceptible to many hazardous attacks. Intrusion Detection and Prevention System (IDPS) is undoubtedly a defense structure to address threats in MANET. Many IDPS methods have been developed to ascertain the exceptional behavior in these networks. Key issue in such IDPS is lack of fast self-organized learning engine that facilitates comprehensive situation awareness for optimum decision making. Proposed "Intelligent Behavioral Hybridized Intrusion Detection and Prevention System (IBH_IDPS)" is built with computational intelligence to detect complex multistage attacks making the system robust and reliable. The System comprises of an Intelligent Client Agent and a Smart Server empowered with fuzzy inference rule-based service engine to ensure confidentiality and integrity of network. Distributed Intelligent Client Agents incorporated with centralized Smart Server makes it capable of analyzing and categorizing unethical incidents appropriately through unsupervised learning mechanism. Experimental analysis proves the proposed model is highly attack resistant, reliable and secure on devices and shows promising gains with assured delivery ratio, low end-to-end delay compared to existing approach.