基于神经网络和模糊逻辑的食物质地评价系统

S. Kato, N. Wada
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引用次数: 2

摘要

本文讨论了一种基于神经网络和模糊逻辑混合模型的食物质地估计系统。该系统由两个部分组成,一个是获取尖锐探针刺入食物时的载荷变化和声音信号的设备,另一个是估计食物纹理数值程度的计算机系统。首先,神经网络假定食物的数值隶属度。模糊逻辑根据估计的隶属度推断出食物质地的数值程度。实验验证了系统的有效性。最后,对未来的发展进行了展望。
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Estimation system of food texture using neural network and fuzzy logic
This paper discusses on a system which estimates food textures using hybrid model of neural network and fuzzy logic. The system consists of equipment which obtains a load change and a sound signal while a sharp probe is stabbing a food, and a computer system which estimates numerical degrees of the food textures. Firstly, the neural network assumes numerical membership degrees of the food. The fuzzy logic infers a numerical degree of the food texture considering the estimated membership degrees. In the experiment, the validity of our proposed system is discussed. Finally future prospect is mentioned.
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International Journal of Space-Based and Situated Computing
International Journal of Space-Based and Situated Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-
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