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Vol. 166, Issue 3, March 2014, pp. 181-189




A Particle Swarm Optimization Algorithm for Neural Networks in Recognition of Maize Leaf Diseases

Zhiyong ZHANG, Yan LI, Fushun WANG and * Xiaoyang HE

College of Information Science and Technology, Agricultural University of Hebei, Lingyusi Street No. 289, Baoding City, Hebei Province, 071001, China
Tel.: 1-393-025-3789

E-mail: zhangzhiyong3789@163.com, hexiaoyang0667@163.com


Received: 20 December 2013 /Accepted: 28 February 2014 /Published: 31 March 2014

Digital Sensors and Sensor Sysstems


Abstract: The neural networks have significance on recognition of crops disease diagnosis? but it has disadvantage of slow convergent speed and shortcoming of local optimum. In order to identify the maize leaf diseases by using machine vision more accurately, we propose an improved particle swarm optimization algorithm for neural networks. With the algorithm, the neural network property is improved. It reasonably confirms threshold and connection weight of neural network, and improves capability of solving problems in the image recognition. At last, an example of the emulation shows that neural network model based on recognizes significantly better than without optimization. Model accuracy has been improved to a certain extent to meet the actual needs of maize leaf diseases recognition.


Keywords: Neural network optimization, Particle swarm optimization, Opposition-based learning, Maize leaf diseases.


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