New Method of Internal Type-2 Fuzzy-Based CNN for Image Classification

P. Murugeswari,S. Vijayalakshmi 한국지능시스템학회 2020 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.20 No.4

In the last two decades, neural networks and fuzzy logic have been successfully implemented in intelligent systems. The fuzzy neural network (FNN) system framework infers the union of fuzzy logic and neural network system framework thoughts, which consolidates their advantages. The FNN system is applied in several scientific and engineering areas. Wherever there is uncertainty associated with the data, fuzzy logic places a vital rule. The fuzzy set can effectively represent and handle uncertain information. The main objective of the FNN system is to achieve a high level of accuracy by including the fuzzy logic in either the neural network structures, activation functions, or learning algorithms. In computer vision and intelligent systems, convolutional neural networks (CNNs) have more popular architectures, and their performance is excellent in many applications. In this paper, fuzzy-based CNN image classification methods are analyzed, and an interval type-2 fuzzy-based CNN is proposed. The experimental results indicated that the performance of the proposed method was good.

계층적 Fuzzy 감지기에 대한 연구

서영수,백동현 (社團法人)韓國火災·消防學會 1997 한국화재소방학회논문지 Vol.11 No.2

본 논문은 화재 감지기의 화재판정을 결정하는 방법으로 화재의 정도를 Fuzzy화 한다음 Fuzzy Logic을 적용하여 화재와 비화재를 판별할 수 있는 새로운 기능의 Fuzzy감지기를 제안한 것이다. Fuzzy 감지기의 입력요소는 화재의 정확한 판단을 위하여 온도센서, 연기센서, 광센서를 이용하였으며 센서출력 신호를 디지털화 하여 적용하였다. 그 결과 기존의 화재 감지기보다 화재감지 능력은 우수하였으나 정확한 화재 판단을 위해서는 보다 많은 Rule을 생성할 수 있는 지식이 필요 하였으며 Fuzzy 감지기를 실제 적용할 경우 그 가능성을 보였다. In this article, the Fuzzy Logic as the principle of the multcriteria fire detector is used to determine whether the fire takes out or not. The main contents of this method as follows ; most of all, the degree of the fire is represented as the type of the Fuzzy, and then it is possible to examine whether the fire takes out or not by the principle of the Fuzzy Logic. The input fators of the fuzzy fire detector are temperature sensor, smoke sensor, light sensor applied to digital type. On the result of this study, the first, the number of the case of the nonfire alarm which is represented in the existing fire detector is reduced, and the second, the applicability of the fuzzy fire detector is demonstrated by the test.

Application of Fuzzy Logic for Grinding Conditions

Gun-hoi Kim 한국정밀공학회 2005 International Journal of Precision Engineering and Vol.6 No.2

This paper has presented an application of an optimum grinding conditions based on the fuzzy logic. Fuzzy logic can handle vague and uncertain knowledge, and presents a scheme for integrating data with various kinds of grinding data. Especial1y, this research is capable of determining the grinding conditions taking into account some fuzzy membership function represented for trapezoidal form such as hardness and surface roughness of workpiece, material tensile strength and elongation, and requirement of grinding method. Larsen's fuzzy production method utilizing the fuzzy production rule can be applied on the establishment of grinding conditions, and also the output value obtained by the center of gravity method can effectively utilize the optimum grinding conditions.

나이브 베이지안과 데이터 마이닝을 이용한 FHIDS(Fuzzy Logic based Hybrid Intrusion Detection System) 설계

이병관(Lee, Byung-Kwan),정은희(Jeong, Eun-Hee) 한국정보전자통신기술학회 2012 한국정보전자통신기술학회논문지 Vol.5 No.3

본 논문에서 나이브 베이지안 알고리즘, 데이터 마이닝, Fuzzy logic을 이용하여 이상 공격과 오용 공격을 탐지하는 하이브리드 침입탐지시스템인 FHIDS(Fuzzy logic based Hybrid Intrusion Detection System)을 설계하였다. 본 논문에서 설계한 FHIDS의 NB-AAD(Naive Bayesian based Anomaly Attack Detection)기법은 나이브 베이지안 알고리즘을 이용해 이상 공격을 탐지하고, DM-MAD(Data Mining based Misuse Attack Detection)기법은 데이터 마이닝 알고리즘을 이용하여 패킷들의 연관 규칙을 분석하여 새로운 규칙기반 패턴을 생성하거나 변형된 규칙 기반 패턴을 추출함으로써, 새로운 공격이나 변형된 공격을 탐지한다. 그리고 FLD(Fuzzy Logic based Decision)은 NB-AAD과 DM-MAD의 결과를 이용하여 정상인지 공격인지를 판별한다. 즉, FHIDS는 이상과 오용공격을 탐지 가능하며 False Positive 비율을 감소시키고, 변형 공격 탐지율을 개선한 하이브리드 공격탐지시스템이다. This paper proposes an FHIDS(Fuzzy logic based Hybrid Intrusion Detection System) design that detects anomaly and misuse attacks by using a Naive Bayesian algorithm, Data Mining, and Fuzzy Logic. The NB-AAD(Naive Bayesian based Anomaly Attack Detection) technique using a Naive Bayesian algorithm within the FHIDS detects anomaly attacks. The DM-MAD(Data Mining based Misuse Attack Detection) technique using Data Mining within it analyzes the correlation rules among packets and detects new attacks or transformed attacks by generating the new rule-based patterns or by extracting the transformed rule-based patterns. The FLD(Fuzzy Logic based Decision) technique within it judges the attacks by using the result of the NB-AAD and DM-MAD. Therefore, the FHIDS is the hybrid attack detection system that improves a transformed attack detection ratio, and reduces False Positive ratio by making it possible to detect anomaly and misuse attacks.

퍼지-PID 알고리즘을 이용한 필라멘트 와인딩 장력제어에 관한 연구

이승호(Seung-Ho Lee),이용재(Yong-Jae Lee),오재윤(Chae-Youn Oh) Korean Society for Precision Engineering 2004 한국정밀공학회지 Vol.21 No.3

This thesis develops a fuzzy-PID control algorithm for control the filament winding tension. It is developed by applying classical PID control technique to a fuzzy logic controller. It is composed of a fuzzy-PI controller and a fuzzy-D controller. The fuzzy-PI controller uses error and integrated error as inputs, and the fuzzy-D controller uses derivative of error as input. The fuzzy-PI controller uses Takagi-Sugeno fuzzy inference system, and the fuzzy-D controller uses Mamdani fuzzy inference system. The fuzzy rule base for the fuzzy-PI controller is designed using 19 rules, and the fuzzy rule base for the fuzzy-D controller is designed using 5 rules. A test-bed is set-up for verifying the effectiveness of the developing control algorithm in control the filament winding tension. It is composed of a mandrel, a carriage, a force sensor, a driving roller, nip rollers, a creel, and a real-time control system. Nip rollers apply a vertical force to a filament, and the driving roller drives it. The real-time control system is developed by using MATLAB/xPC Target. First, experiments for showing the inherent problems of an open-loop control scheme in a filament winding are performed. Then, experiments for showing the robustness of the developing fuzzy-PID control algorithm are performed under various working conditions occurring in a filament winding such as mandrel rotating speed change, carriage traversing, spool radius change, and reference input change.

Cloud-Type Classification by Two-Layered Fuzzy Logic

Kwang Baek Kim 한국지능시스템학회 2013 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.13 No.1

Cloud detection and analysis from satellite images has been a topic of research in many atmospheric and environmental studies; however, it still is a challenging task for many reasons. In this paper, we propose a new method for cloud-type classification using fuzzy logic. Knowing that visible-light images of clouds contain thickness related information, while infrared images haves height-related information, we propose a two-layered fuzzy logic based on the input source to provide us with a relatively clear-cut threshold in classification. Traditional noise-removal methods that use reflection/release characteristics of infrared images often produce false positive cloud areas, such as fog thereby it negatively affecting the classification accuracy. In this study, we used the color information from source images to extract the region of interest while avoiding false positives. The structure of fuzzy inference was also changed, because we utilized three types of source images: visible-light, infrared, and near-infrared images. When a cloud appears in both the visible-light image and the infrared image, the fuzzy membership function has a different form. Therefore we designed two sets of fuzzy inference rules and related classification rules. In our experiment, the proposed method was verified to be efficient and more accurate than the previous fuzzy logic attempt that used infrared image features.

Lotfi A. Zadeh

이승온(Seung-On Lee),김진태(Jin-Tae Kim) 한국지능시스템학회 2008 한국지능시스템학회 학술발표 논문집 Vol.18 No.1

퍼지 논리는 1965년 Zadeh[13]에 의하여 소개된 이후 꾸준히 확장, 발전하였다. 퍼지 논리와 관련된 수학사 및 수학교육 논문[1, 2, 3, 4, 5, 7]들이 많이 발표 되었지만 정작 퍼지 논리의 창시자인 Zadeh에 대한 연구 논문은 아직까지 나오지 않았다. 본 논문에서는 Zadeh의 생애와 업적을 알아보고 이를 통해 우리가 배워야 할 점들에 대해 논의한다. 또한 이가 논리, 다가 논리, 퍼지 논리, 직관주의 논리 및 직관적 퍼지 집합을 비교, 분석해보고 직관적 퍼지 집합에서 ‘직관적(intuitionistic)’이라는 용어의 부적절성에 대해 논의한다. Fuzzy logic is introduced by Zadeh in 1965. It has been continuously developed by many mathematicians and knowledge engineers all lover the world. A lot of papers concerning with the history of mathematics and the mathematical education related with fuzzy logic, but there is no paper concerning with Zadeh. In this article, we investigate his life and papers about fuzzy logic. We also compare two-valued logic, three-valued logic, fuzzy logic, intuisionistic logic and intuitionistic fuzzy sets. Finally we discuss about the expression of intuitionistic fuzzy sets.

Propose of Fuzzy Logic-Based Students’ Learning Assessment

Rungaroon Sripan,Bandit Suksawat 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

This paper proposes the students’ learning assessment by using fuzzy logic. The framework of practical learning system for computer discipline is also presented to explain a conceptual design of an intelligent tutorial system. The proposed framework composes of six components including interface module, domain knowledge, inference engine, student module, mentor module and pedagogical module. The inference engine performed students’ group classification form on-line pre-test examination before starting the practical worksheet application. Two input parameters consisting of percentage of score and time were established as inputs for membership functions of fuzzy logic system. The twenty-five fuzzy rules were created for the proposed method by experts. The defuzzification of output membership functions, including good, fair and improve were performed by using the centroid method. In this paper, 26 students were tested in order to compare the students’ learning performance, assessed by fuzzy logic and t-score method. The results revealed that the proposed method was a flexible process to classify students’ learning group based on the objectives of subject and the real time performance comparing with t-score method.

An Application of Fuzzy Logic with Desirability Functions to Multi-response Optimization in the Taguchi Method

Kim Seong-Jun Korean Institute of Intelligent Systems 2005 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.5 No.3

Although it is widely used to find an optimum setting of manufacturing process parameters in a variety of engineering fields, the Taguchi method has a difficulty in dealing with multi-response situations in which several response variables should be considered at the same time. For example, electrode wear, surface roughness, and material removal rate are important process response variables in an electrical discharge machining (EDM) process. A simultaneous optimization should be accomplished. Many researches from various disciplines have been conducted for such multi-response optimizations. One of them is a fuzzy logic approach presented by Lin et al. [1]. They showed that two response characteristics are converted into a single performance index based upon fuzzy logic. However, it is pointed out that information regarding relative importance of response variables is not considered in that method. In order to overcome this problem, a desirability function can be adopted, which frequently appears in the statistical literature. In this paper, we propose a novel approach for the multi-response optimization by incorporating fuzzy logic into desirability function. The present method is illustrated by an EDM data of Lin and Lin [2].

Application of Fuzzy Logic for Grinding Conditions

Kim Gun-hoi Korean Society for Precision Engineering 2005 International Journal of Precision Engineering and Vol.6 No.2

This paper has presented an application of an optimum grinding conditions based on the fuzzy logic. Fuzzy logic can handle vague and uncertain knowledge, and presents a scheme for integrating data with various kinds of grinding data. Especially, this research is capable of determining the grinding conditions taking into account some fuzzy membership function represented for trapezoidal form such as hardness and surface roughness of workpiece, material tensile strength and elongation, and requirement of grinding method. Larsen's fuzzy production method utilizing the fuzzy production rule can be applied on the establishment of grinding conditions, and also the output value obtained by the center of gravity method can effectively utilize the optimum grinding conditions.