• 한국지능시스템학회논문지
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• 제21권6호
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• pp.686-691
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• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.

• 대한치과의사협회지
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• 제15권12호
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• pp.957-962
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• 1977

The author has observed the tissue reaction of the absolute alcohol infection of rat oral mucosa. 0.5ml absolute alcohol was injected subcutaneously on the mucobuccal fold of rat. And the rats were sacrifieced at intervals of one day, 3rd, 1 week, 2 week and 4 week after alcohol injection. The microscopic tissue sections were made and stained with hematoxylin and eosin. The results were are as follows; 1. Degeneration and shrinkage of fibroblasts and coagulative necrosis were observed one day to and three day after alcohol injection. 2. Although coagulative necrosis and tissue degeneration occurred, the inflammatory infiltration was not prominent especially there were scarcely any polymorphonuclear leukocytes in that field. 3. Granulation tissue with moderate small round cell infiltration were replaced the necrotic area at one week after injection and the fibroblast proliferate into the granulation tissue at two week group. 4. At four week after injection, the damaged area recovered by fibroblastic proliferation and collage formation, but there were

• Journal of Pharmaceutical Investigation
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• 제8권1호
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• pp.27-36
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• 1978

Spherical granules of anti-inflammatory enzyme were prepared by mixer granulation and the recovery rate of enzyme activity by processing was compared with tablet ones. In the enteric granule coating .processing, the effect of the amount of coating solution and the conentration of fatty alcohol on disintegration and stabilities on the accelerated conditions were also studied. Being prepared in non-pressure and non-aqueous condition, spherical granules of enzyme made better recovery of enzme activity than tablet ones by 10 times. Combined processing of both mixer granulation and enteric granule film coating provided the noble enteric coated granules, in the sense of disintegration and stabilities, was obtained from using 0.125% fatty alcohol in coating solution.

• 한국문화재보존과학회:학술대회논문집
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• 한국문화재보존과학회 2003년도 제17회 학술대회 발표 논문집
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• pp.8-9
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• 2003

• 한국전기화학회:학술대회논문집
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• 한국전기화학회 2002년도 연료전지심포지움 2002논문집
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• pp.265-270
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• 2002

• Journal of Pharmaceutical Investigation
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• 제20권3호spc1호
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• pp.1-24
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• 1990

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 1999년도 제4차 추계학술대회 초록집
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• pp.85-85
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• 1999

• Journal of Electrical Engineering and Technology
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• 제7권4호
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• pp.636-645
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• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

• 한국토양비료학회지
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• 제35권5호
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• pp.290-295
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• 2002

조립 복합비료의 증량제를 점토광물 대신 인광석분말로 대체하여 연초용 복합비료(10-0-30)조립시험을 수행했다. 황산칼리 60%, 요소 22%, 인광석 18%로 조성된 분말에 10% 인산액을 점결제로 조립한 결과 소량의 점결제로서 양호하게 조립되었으며 입자분포, 입자경도, 수중 붕괴도, 흡습성 등 물리성이 매우 이상적인 입자로 조사되었다. 담배직물을 묘상기, 본포기로 나누어 폿트 비효실험 결과 생육기간이 짧은 묘상에서는 시제품의 생육이 부진하였고 본포기 폿트 재배시험에서도 인산축적이 없는 개간지 토양에서는 생육이 부진하였으나 인산이 축적된 숙전에서는 정상적으로 생육하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.