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＜会議発表論文＞
Application of neural networks and fuzzy logic to consumer products
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| 概要 | This paper describes how neural networks and fuzzy logic have been applied to consumer products. First, the background behind why both technologies have been applied to this field is described. Second..., briefly overview of the fusion technology of neural networks and fuzzy logic is given. As a good example of the R&D process, the application of neural nets to the design and tuning of fuzzy system is introduced. In Sections 4 and 5, applications of both technologies are categorized into four cases. They are: (1) neural networks being used to automate the task of designing and fine-tuning the membership functions of fuzzy systems, (2) both fuzzy inference and neural network learning capabilities provided separately, (3) neural networks work as correcting mechanisms for fuzzy system, (4) neural networks cascaded (serially) with fuzzy systems, and (5) neural networks used to customizet he standard system according to each user's preferences and individual needs. Finally, the new trend that aims at the realization of adaptive systems for the user is discussed. As examples of the trend, four consumer products that apply learning capability of neural networks for the user are introduced.続きを見る |
| 目次 | 1 Introduction 2 Status of Fusion Research of Neural Networks and Fuzzy Logic 3 Overview of Applications of Neural Networks and Fuzzy Logic 4 Non-Consumer-Trainable Application 5 Consu1ner-Trainable Neural Network 6 Requirement for Future Systems |
本文ファイル
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IntConf013
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2.38 MB | 429 |
詳細
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| 登録日 | 2021.08.16 |
| 更新日 | 2021.08.24 |