• 디지털콘텐츠학회 논문지
• /
• 제5권2호
• /
• pp.128-132
• /
• 2004

In this paper, a Fuzzy Inference System(FIS) based watermarking algorithm in Discrete Wavelet Transform(DWT) domain is proposed. A 2D fuzzy inference values, in which the inputs are parameters of the coefficients of the DWT block of the original image and the output is strength of watermark embedded, is devised. The fuzzy inference algorithm guarantees that the watermark to be embedded into the original image adaptively. The experimental results shows that proposed approach is robust to the digital image processing schemes.

• 한국산학기술학회논문지
• /
• 제7권3호
• /
• pp.398-403
• /
• 2006

본 논문에서는 컬러 디지털 영상에서의 특징점 추출을 위한 퍼지 임계치 설정기법을 제안한다. 이를 위하여 두 가지 종류의 퍼지 측정자를 사용하여 임계치를 계산하는 퍼지추론 시스템을 구성한다. 퍼지추론 시스템에 사용된 측정자들은 디지털 영상에서의 국부영역 밝기를 매우 잘 반영할 뿐만 아니라 특징점 추출 성능이 매우 우수함을 보여준다. 또한, 퍼지측정자로 사용되는 비선형 스케치 특징점 추출 필터의 특성을 도식적으로 해석하였고 특징점들의 특성이 반영된 퍼지추론 시스템을 설계하였다. 이와 같이 설계된 퍼지추론 시스템을 통해 디지털 영상에 포함된 특징점의 특성이 반영된 임계치를 선택하였다. 실험결과를 통해 제안된 퍼지 임계치 추론 방법이 매우 유용성을 증명할 수 있었다.

• 대한기계학회논문집A
• /
• 제27권2호
• /
• pp.310-316
• /
• 2003

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in CMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer, etc. and then the bead geometry of each weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments, membership functions and fuzzy rules are tuned and determined by the learning of neural network, and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm, the inference error percent is within -5%∼+4% in case of bead width, -10%∼+10% in bead height, -5%∼+6% in bead area, -10%∼+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the CMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.

• Journal of information and communication convergence engineering
• /
• 제19권4호
• /
• pp.234-240
• /
• 2021

As the number of pet dog-related businesses is rising rapidly, there is an increasing need for reliable pet dog health information systems for casual pet owners, especially those caring for older dogs. Our goal is to implement a mobile pre-diagnosis system that can provide a first-hand pre-diagnosis and an appropriate coping strategy when the pet owner observes abnormal symptoms. Our previous attempt, which is based on the fuzzy C-means family in inference, performs well when only relevant symptoms are provided for the query, but this assumption is not realistic. Thus, in this paper, we propose a hybrid inference structure that combines fuzzy association memory and a double-layered fuzzy C-means algorithm to infer the probable disease with robustness, even when noisy symptoms are present in the query provided by the user. In the experiment, it is verified that our proposed system is more robust when noisy (irrelevant) input symptoms are provided and the inferred results (probable diseases) are more cohesive than those generated by the single-phase fuzzy C-means inference engine.

• 한국정보처리학회논문지
• /
• 제7권5호
• /
• pp.1434-1445
• /
• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
• /
• pp.1274-1276
• /
• 1993

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

• 한국콘텐츠학회논문지
• /
• 제20권10호
• /
• pp.167-176
• /
• 2020

현재 국내에서 활용되고 있는 자동화된 어류 급이 장치는 특정 시간과 일정량의 사료를 시간에 맞추어 수조에 공급하는 방식이다. 이는 고령화되고 고가인 양식장 관리의 인건비는 줄일 수 있으나 양식 생산성에 결정적 요인이 되는 고가의 사료량을 지능적으로 적절히 조절하기는 매우 어렵다. 본 논문에서는 이러한 기존 자동급이 장치의 문제점을 해결하고, 양식장에서 어류의 성장률을 적절하게 유지하면서 사료 공급의 효율성을 극대화할 수 있는 퍼지추론 기반의 지능형 어류 자동 급이 모델인 FIIFF 추론 모델(Fuzzy Inference based Intelligent Fish Feeding Model)을 제안한다. 본 논문에서 제안하는 FIIFF 지능형 급이 추론모델은 양식어류의 현재 생육 환경 정보 및 실시간 활동 상태를 기반으로 급이량을 산출하기 때문에 사료 급이량 적절성이 매우 높다. 본 연구에서 제안한 FIIFF 추론 모델의 급이량 산출 실험 결과에서는 8개월 동안 양식장에서 실제 투입한 급이량보다 14.8%를 절감하는 효과를 보여준다.

• 한국융합학회논문지
• /
• 제5권1호
• /
• pp.35-41
• /
• 2014

An automatic speech recognition system is one of the popular research problems. There are many research groups working in this field for different language including Japanese. Japanese vowel recognition is one of important parts in the Japanese speech recognition system. The vowel classification system with the Mamdani fuzzy inference system was developed in this research. We tested our system on the blind test data set collected from one male native Japanese speaker and four male non-native Japanese speakers. All subjects in the blind test data set were not the same subjects in the training data set. We found out that the classification rate from the training data set is 95.0 %. In the speaker-independent experiments, the classification rate from the native speaker is around 70.0 %, whereas that from the non-native speakers is around 80.5 %.

• Journal of Advanced Marine Engineering and Technology
• /
• 제27권1호
• /
• pp.42-48
• /
• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• 한국산업정보학회논문지
• /
• 제6권1호
• /
• pp.61-69
• /
• 2001

본 연구는 관능검사에서 얻은 결과로 평가규칙을 설계하고 이를 이용하여 추후의 관능평가에 응용할 수 있는 방법을 제안함에 있어서, 퍼지추론의 규칙을 효율적으로 설계하는 것에 관련된 것이다. 퍼지추론 규칙의 수는 규칙의 전건부의 구조와 파라미터를 설계함에 있어서 퍼지분할의 수에 따라 결정되는데, 분할의 수가 많다고 해서 최적은 아니므로 효율적으로 규칙의 수를 축소하는 것이 규칙을 응용할 때의 효율성을 제고하는 동시에 실무에 응용할 때 추론엔진의 속도를 높일 수 있다. 이를 위해 본 연구에서는 선행연구에서 제시된 사례를 이용하여 추론규칙의 수를 축소하여도 대등한 결과를 얻을 수 있음을 수치예를 통하여 증명하였다. 본 연구의 결과는 향후 관능검사를 이용하는 다른 분야에도 유효하게 응용될 수 있을 것이다.