Abstract
This study aims to investigate the food quality detection using an intelligent method. The machine vision applies image processing softwares to monitor the food quality. The Artificial Neural Network (ANN) in the image processing softwares is crucial for food quality detection precision. However, improper structure parameters of ANN may lead to the low detection performance. In order to overcome this problem, a new detection method based on Genetic Algorithm (GA) -Chaos optimized Radial Basis Function (RBF) neural network is proposed in this study. The GA-Chaos was used to optimize the structure of the RBF as well as its weight values to obtain high generalization ability of the RBF-detection model. Then the RBF model was employed to train and test the food data sets. Experimental results show that the method could enhance the food quality detection rate and outperforms the traditional GA-based methods.
Highlights
In China, the food safety problems are very serious (Li, 2013), for instance, the Sanlu milk powder, Tonyred, etc
In order to investigate the food quality detection using Genetic Algorithm (GA) optimized Artificial Neural Network (ANN), this study proposed a new method based on the Chaos GA and the Radial Basis Function (RBF) neural network
Chromosomes will be coded by hidden nodes number, the base function of central values and the width of the RBF network
Summary
In China, the food safety problems are very serious (Li, 2013), for instance, the Sanlu milk powder, Tonyred, etc. How to guarantee the food safety has attracted extensive attention. The request for safe and high-quality food industry supply chain supervision is still open (Bennedsen and Peterson, 2004). It is imperative to effectively monitor the food quality to guarantee food quality and safety. Machine vision applies computer vision to process monitoring. By the use of machine vision, one could make the food quality management very effective. Machine vision has been widely applied to inspect the quality of produced goods like electronic devices. Some specially designed image processing softwares are necessary for these applications in the machine vision systems. Image processing is very crucial for the food detection performance
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