• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.38-42
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• 2002

A fast iterative solving method of fuzzy relational equation is proposed. It is derived by eliminating a redundant comparison process in the conventional iterative solving method (Pedrycz, 1983). The proposed method is applied to image reconstruction, and confirmed that the computation time is decreased to 1 / 40 with the compression rate of 0.0625. Furthermore, in order to make any initial solution converge on a reconstructed image with a good quality, a new cost function is proposed. Under the condition that the compression rate is 0.0625, it is confirmed that the root mean square error of the proposed method decreases to 27.34% and 86.27% compared with those of the conventional iterative method and a non iterative image reconstruction method, respectively.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.62-73
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• 2020

In this paper, we present electronic acupuncture needles we have developed using intelligence technology based on Bluetooth in order to allow anyone to simply receive customized remote diagnosis and treatment by clicking on the menu of the smartphone regardless of time and place. In order to determine the health condition and disease of patients, we have developed a software and a hardware of electronic acupuncture needles, operating on Bluetooth which transmits biometric data to oriental medical doctors using the functions of automatically determining pulse diagnosis, tongue diagnosis, and oxygen saturation; the functions are most commonly used in herbal treatment. In addition, using fuzzy logic and reasoning based on smartphones, we present in this paper an algorithm and the results of completion of hardware implementation for electronic acupuncture needles, appropriate for the body conditions of patients; the algorithm and the hardware implementation are for a treatment time duration by electronic acupuncture needles, an automatic determinations of pulse diagnosis, tongue diagnosis, and oxygen saturation, a function implementation for automatic display of acupuncture point, and a strength adjustment of electronic acupuncture needles. As a result of our simulation, we have shown that the treatment of patients, performed using an Electronic Acupuncture Needles based on intelligence, is more efficient compared to the treatment that was performed before.

• ETRI Journal
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• v.45 no.6
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• pp.996-1006
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• 2023

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high-gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step-size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step-size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.

• Journal of Digital Contents Society
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• v.2 no.1
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• pp.51-61
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• 2001

The FLC(Fuzzy Logic Controller) is stronger to the disturbance and has the excellent characteristic to the overshoot of the initialized value than the classical controller, and also can carry out the proper control being out of all relation to the mathematical model and parameter value of the system. But it has the restriction which can't adopt the environment changes of the control system because of generating the fuzzy control rule through an expert's experience and the fixed value of the once determined control rule, and also can't converge correctly to the desired value because of haying the minute error of the controller output value. Now there are many suggested methods to eliminate the minute error, we also suggest the GA-FNNIC(Genetic Algorithm Fuzzy Neural Network Intelligence Controller) combined FLC with NN(Neural Network) and GA(Genetic Algorithm). In this paper, we compare the suggested GA-FNNIC with FLC and analyze the output characteristics, convergence speed, overshoot and rising time. Finally we show that the GA-FNNIC converge correctly to the desirable value without any error.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.1-13
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• 2010

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.

• Explosives and Blasting
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• v.39 no.3
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• pp.44-64
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• 2021

With the upcoming 4^th industrial revolution era, the applications of artificial intelligence(AI) and big data in engineering are increasing. In the field of blasting, there have been various reported cases of the application of AI. In this paper, AI techniques, such as artificial neural network, fuzzy logic, generic algorithm, swarm intelligence, and support vector machine, which are widely applied in blasting area, are introduced, The studies about the application of AI for the prediction of ground vibration, rock fragmentation, fly rock, air overpressure, and back break are surveyed and summarized. It is for providing starting points for the discussion of active application of AI on effective and safe blasting design, enhancing blasting performance, and minimizing the environmental impact due to blasting.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.65-72
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• 2000

In this paper we propose the new binary image matching algorithm called the Fuzzy logic induced Hausdorff Distance(FHD) for finding the maximally matched image with the query image. The membership histogram is obtained by normalizing the cardinality of the subset with the corresponding radius after obtaining the distribution of the minimum distance computed by the Hausdroff distance between two binary images. in the proposed algorithm, The fuzzy influence method Center of Gravity(COG) is applied to calculate the best matching candidate in the membership function described above. The proposed algorithm shows the excellent results for the face image recognition when the noise is added to the query image as well as for the character recognition.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.206-209
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• 1999

Conventional target tracking techniques are primarily based on Kalman filtering or probabilistic data association(PDA). But it is difficult to perform well under a high cluttered tracking environment because of the difficulty of measurement, the problem of mathematical simplification and the difficulty of combined target detection for tracking association problem. This paper deals with an analysis of target tracking problem using fuzzy-logic theory, and determines fuzzy rules used by a fuzzy tracker, and designs the fuzzy tracker by using fuzzy rules and Kalman filtering.

• Smart Media Journal
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• v.12 no.1
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• pp.54-61
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• 2023

Pricing, as one of the most important aspects of a business, should be taken seriously. Whatever affects a company's pricing system tends to affect its profits and losses as well. Currently, many manufacturing companies fix product prices manually by members of an organization's management team. However, due to the imperfect nature of humans, an extremely low or high price may be fixed, which is detrimental to the company in either case. This paper proposes the development of a fuzzy-based price expert system (Expert Fuzzy Price (EFP)) for manufacturing companies. This system will be able to recommend appropriate prices for products in manufacturing companies based on four major pricing strategic goals, namely: Product Demand, Price Skimming, Competition Price, and Target population.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.1-11
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• 1998

In this work, we propose a modeling method based on an artifical intelligence technique for a stem generator in a nuclear power plant. Modeling the steam generator is known to be difficult due to several facts; especially, the dynamics of the steam generator is nonminimum phase which is mainly caused by the swell and shrink phenomena from thermal effects. In order to overcome this difficulty, we adopt so-called logic processor whose structure itself has a logical meaning to be easily established and also efficiently learned. Such a manner, we could derive an useful model simulating the dynamics of the steam generator in a nuclear power plant.