ICSEE 2012: Intelligent Computing for Sustainable Energy and Environment pp 257-265 | Cite as
An Intelligent Variable Spraying Decision-Making System Based on Fuzzy Neural Network for Greenhouse Mobile Robot
Abstract
To improve the effective utilization rate of pesticide and reduce the pesticide residues and chemical pollution during spraying process, an intelligent decision-making method for variable spraying based on fuzzy neural network is designed according to the feature of the mobile robot spraying in greenhouse, combined with the spraying principle of variable spraying system for row-walking mobile robot. The decision system of offline training fuzzy neural network is built by integrating the information of the level of plant diseases and insect pests, the distance and area of spraying target. The simulation results show that the fuzzy neural network intelligent decision-making method can realize real-time and quick decisions by off-line training. It has the greater decision accuracy than the fuzzy decision system on the samples not appearing in training because of its strong adaptability and generalization ability and has a good fit for the uncertain work environment in greenhouse.
Keywords
intelligence decision-making fuzzy neural network variable spraying mobile robotPreview
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