Grade classification model tandem BpNN method with multi-metal sensor for rice eating quality evaluation

Sensors and Actuators, B: Chemical

Volumn 281, Issue , 2019, Pages 22-27

  Lu, Lin ^a,b   Fang, Changyun ^a,b   Hu, Zhanqiang ^a,b   Hu, Xianqiao ^a,b   Zhu, Zhiwei ^a,b  

^a CHINA NATIONAL RICE RESEARCH INSTITUTE   (China)

^b BEIJING HOSPITAL   (China)

Author keywords

BpNN; Grade classification model; Rice quality; Score prediction; Tandem evaluation approach

Indexed keywords

ELECTRONIC TONGUES; FORECASTING;

BPNN; CLASSIFICATION MODELS; CORRELATION COEFFICIENT; DIRECT NEURAL NETWORKS; EVALUATION APPROACH; INPUT VARIABLES; RICE QUALITIES; SENSORY SCORES;

QUALITY CONTROL;

EID: 85055036863     PISSN: 09254005     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.snb.2018.10.062     Document Type: Article

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