• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.149-153
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• 2012

In this paper, we introduce the concept of fuzzy almost strongly (r, s)-semicontinuous mappings on intuitionistic fuzzy topological spaces in $\check{S}$ostak's sense. The relationships among fuzzy strongly (r, s)-semicontinuous, fuzzy almost (r, s)-continuous, fuzzy almost (r, s)-semicontinuous, and fuzzy almost strongly (r, s)-semicontinuous mappings are discussed. The characterization for the fuzzy almost strongly (r, s)-semicontinuous mappings is obtained.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.202-206
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• 2008

We introduce the concept of interval-valued minimal structure which is an extension of the interval-valued fuzzy topology. And we introduce and study the concepts of IVF m-continuous and several types of compactness on the interval-valued fuzzy m-spaces.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.296-302
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• 2010

This paper considers fuzzifying topologies, a special case of I-fuzzy topologies (bifuzzy topologies) introduced by Ying [16, (I)]. It investigates topological notions defined by means of regular open sets when these are planted into the frame-work of Ying's fuzzifying topological spaces (in ${\L}$ukasiewwicz fuzzy logic). The concept of fuzzifying nearly compact spaces is introduced and some of its properties are obtained. We use the finite intersection property to give a characterization of fuzzifying nearly compact spaces. Furthermore, we study the image of fuzzifying nearly compact spaces under fuzzifying completely continuous functions, fuzzifying almost continuity and fuzzifying R-map.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.113-117
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• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.627-629
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• 1999

The research fields of mobile robot consist of three parts. The first is path planning, the second is the application of new sensors, and the last is a combination of the communication technology and mobile robot. In this paper we treat the path-planning. We use a Bayesian probability map, Distance Transform and Fuzzy logic for a path-planning. DT and Fuzzy logic algorithms search for path in entire, continuous free space and unifies global path planning and local path planning. It is efficient and effective method when compared with navigators using traditional approaches.

• Journal of Korean Society for Quality Management
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• v.11 no.2
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• pp.2-9
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• 1983

As will be seen, this paper is tries that the research on the mathematical structure of Markov process and Markovian sequential decision process (the policy improvement iteration method,) moreover, that it analyze the logic and the characteristic of behavior of mathematical model of Markov process. Therefore firstly, it classify, on research of mathematical structure of Markov process, the forward equation and backward equation of Chapman-kolmogorov equation and of kolmogorov differential equation, and then have survey on logic of equation systems or on the question of uniqueness and existence of solution of the equation. Secondly, it classify, at the Markovian sequential decision process, the case of discrete time parameter and the continuous time parameter, and then it explore the logic system of characteristic of the behavior, the value determination operation and the policy improvement routine.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.36-43
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• 1998

A fuzzy logic filter is constructed from a set of fuzzy IF-THEN rules which change adaptively to minimize some criterion function as new information becomes available. This paper generalizes the fuzzy logic filter and it's adaptive filtering algorithm to include complex parameters and complex signals. Using the complex Stone-Weierstrass theorem, we prove that linear combinations of the fuzzy basis functions are capable of uniformly approximating and complex continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, a complex orthogonal least-squares (COLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs. Also, we propose an adaptive algorithm based on LMS which adjust simultaneously filter parameters and the parameter of the membership function which characterize the fuzzy concepts in the IF-THEN rules. The modeling of a nonlinear communications channel based on a complex fuzzy is used to demonstrate the effectiveness of these algorithm.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• Journal of the Korean earth science society
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• v.26 no.2
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• pp.114-128
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• 2005

Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.