Vision Intelligence for Precision Farming Using Fuzzy Logic Optimized Genetic Algorithm and Artificial Neural Network
نویسندگان
چکیده
The purpose of the study was to develop an intelligent vision system for autonomous vehicle field operations. Fuzzy logic was used to classify the crops and weeds. A Genetic Algorithm (GA) was used to optimize and tune the fuzzy logic membership rules. Field study confirmed that the method developed was able to accurately classify crop and weeds through the entire growing period. After segmenting out the weed, an artificial neural network (ANN) was used to estimate the estimates crop height and width. The r for estimation of the crop height was 0.92 for the training data and 0.83 for the test data. Finally, a geographic information system (GIS) was used to create a crop growth map.
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