Fuzzy prediction of maize breakage

Q. Zhang; J. B. Litchfield; J. Bentsman

doi:10.1016/0021-8634(92)80051-S

Fuzzy prediction of maize breakage

Q. Zhang, J. B. Litchfield, J. Bentsman

Research output: Contribution to journal › Article › peer-review

Abstract

Fuzzy sets theory allows uncertain phenomena to be treated mathematically. A fuzzy predictive model was developed to predict the breakage susceptibility of dried maize based on measurable process variables. The model is based on data acquired from nine experiments in a laboratory crossflow dryer with various initial maize moisture contents and drying temperatures. A 2-h verification experiment showed that 28 of the 36 predictions matched measured values of breakage susceptibility. The model can be used to predict maize breakage during drying.

Original language	English (US)
Pages (from-to)	77-90
Number of pages	14
Journal	Journal of Agricultural Engineering Research
Volume	52
Issue number	C
DOIs	https://doi.org/10.1016/0021-8634(92)80051-S
State	Published - Jan 1 1992

ASJC Scopus subject areas

Aquatic Science

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10.1016/0021-8634(92)80051-S

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title = "Fuzzy prediction of maize breakage",

abstract = "Fuzzy sets theory allows uncertain phenomena to be treated mathematically. A fuzzy predictive model was developed to predict the breakage susceptibility of dried maize based on measurable process variables. The model is based on data acquired from nine experiments in a laboratory crossflow dryer with various initial maize moisture contents and drying temperatures. A 2-h verification experiment showed that 28 of the 36 predictions matched measured values of breakage susceptibility. The model can be used to predict maize breakage during drying.",

author = "Q. Zhang and Litchfield, {J. B.} and J. Bentsman",

year = "1992",

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doi = "10.1016/0021-8634(92)80051-S",

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AB - Fuzzy sets theory allows uncertain phenomena to be treated mathematically. A fuzzy predictive model was developed to predict the breakage susceptibility of dried maize based on measurable process variables. The model is based on data acquired from nine experiments in a laboratory crossflow dryer with various initial maize moisture contents and drying temperatures. A 2-h verification experiment showed that 28 of the 36 predictions matched measured values of breakage susceptibility. The model can be used to predict maize breakage during drying.

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Fuzzy prediction of maize breakage

Abstract

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