Rice yield classification using backpropagation network

• Main Authors: Saad, P., Jamaludin, N.K., Kamarudin, S. S., Rusli, N.
• Format: Article
• Language: English
• Published: Universiti Utara Malaysia 2004
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/1043/1/P._Saad.pdf; http://repo.uum.edu.my/1043/; http://jict.uum.edu.my
• Institution: Universiti Utara Malaysia

Among factors that affect rice yield are diseases, pests and weeds. It is intractable to model the correlation between plant diseases, pests and weeds on the amount of rice yield statistically and mathematically. In this study, a backpropagation network (BPN) is developed to classify rice yield base...