지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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In this study, we introduce a new design methodology of a granular-oriented self-organizing polynomial neural networks (GoSOPNNs) that is based on multi-layer perceptron with Context-based Polynomial Neurons (CPNs) or Polynomial Neurons (PNs). In contrast to the typical architectures encountered in polynomial neural networks (PNN), our main objective is to develop a methodological design strategy of GoSOPNNs as follows : (a) The 1st layer of the proposed network consists of Context-based Polynomial Neuron (CPN). In here, CPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Context-based Fuzzy C-Means (C-FCM) clustering method. The context-based clustering supporting the design of information granules is completed in the space of the input data while the build of the clusters is guided by a collection of some predefined fuzzy sets (so-called contexts) defined in the output space. (b) The proposed design procedure being applied at each layer of GoSOPNN leads to the selection of preferred nodes of the network (CPNs or PNs) whose local characteristics (such as the number of contexts, the number of clusters, a collection of the specific subset of input variables, and the order of the polynomial) can be easily adjusted. These options contribute to the flexibility as well as simplicity and compactness of the resulting architecture of the network. For the evaluation of performance of the proposed GoSOPNN network, we describe a detailed characteristic of the proposed model using a well-known learning machine data(Automobile Miles Per Gallon Data, Boston Housing Data, Medical Image System Data).
목차
Abstract
1. 서론
2. 입자화 중심 자기구성 신경 회로망의 구조 및 형태
3. 입자화 중심 자기구성 다항식 신경 회로망 설계
4. 시뮬레이션 및 결과 고찰
5. 결론
감사의 글
참고문헌
저자소개
참고문헌 (16)
참고문헌 신청
1. [학술지(정기간행물)] - K. D. Karatzas / 2007 / Air pollution modelling with the aid of computational intelligence methods in Thessaloniki, Greece / Simulation Modelling Practice and Theory 15 : 1310 ~ 1319
2. [학술지(정기간행물)] - C. Riziotis / 2007 / Computational intelligence in photonics technology and optical networks: A survey and future perspectives / Information Sciences 177 : 5292 ~ 5315
3. [학술지(정기간행물)] - R. del-Hoyo / 2009 / Computational intelligence tools for next generation quality of service management / Neurocomputing 72 : 3631 ~ 3639
4. [학술지(정기간행물)] - D. Srinivasan / 2009 / Computational intelligence-based congestionprediction for a dynamic urban street network / Neurocomputing 72 : 2710 ~ 2716
5. [학술지(정기간행물)] - M. R. AlRashidi / 2009 / Applications of computational intelligence techniques for solving the revived optimal power flow problem / Electric Power Systems Research 79 : 694 ~ 702
2. [학술지(정기간행물)] - C. Riziotis / 2007 / Computational intelligence in photonics technology and optical networks: A survey and future perspectives / Information Sciences 177 : 5292 ~ 5315
3. [학술지(정기간행물)] - R. del-Hoyo / 2009 / Computational intelligence tools for next generation quality of service management / Neurocomputing 72 : 3631 ~ 3639
4. [학술지(정기간행물)] - D. Srinivasan / 2009 / Computational intelligence-based congestionprediction for a dynamic urban street network / Neurocomputing 72 : 2710 ~ 2716
5. [학술지(정기간행물)] - M. R. AlRashidi / 2009 / Applications of computational intelligence techniques for solving the revived optimal power flow problem / Electric Power Systems Research 79 : 694 ~ 702
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UCI(KEPA) : I410-ECN-0101-2013-560-001275307