Fuzzy Inference Systems to Model Sensory Evaluation
Fuzzy Inference Systems to Model Sensory Evaluation
复制标题
用于模拟感官评估的模糊推理系统
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
B. Charnomordic
中科院分区：
文献类型：
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作者：
S. Guillaume;B. Charnomordic
本章提出了一种模糊方法来模拟专家感官评价和消费者偏好之间的关系。归纳法用于从数据样本中提取定性知识。归纳过程是在可解释性约束下运行的，以确保模糊规则对人类专家有意义。为了获得可解释性，人们应该容忍准确性的损失。将完整的程序应用于食品强调了数据预处理的重要性，并表明定性知识可以帮助将产品属性与消费者评级联系起来。
This chapter proposes a fuzzy approach to model the relationship between expert sensory evaluation and consumer preference. An induction method is used to extract qualitative knowledge from the data sample. The induction process is run under interpretability constraints to ensure the fuzzy rules have a meaning for the human expert. To gain interpretability one should tolerate a loss of accuracy. Applying the complete procedure to a food product underlines the importance of data preprocessing and demonstrates that qualitative knowledge can help to relate product attributes to consumer ratings.