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Our project probes the relationship between temperatures and the blossom dateof cherry trees. Through modeling, future flowering will become predictive,helping the public plan travels and avoid pollen season. To predict the datewhen the cherry trees will blossom exactly could be viewed as a multiclassclassification problem, so we applied the multi-class Support Vector Classifier(SVC) and Recurrent Neural Network (RNN), particularly Long Short-term Memory(LSTM), to formulate the problem. In the end, we evaluate and compare theperformance of these approaches to find out which one might be more applicablein reality.

Predicting Blossom Date of Cherry Tree With Support Vector Machine and Recurrent Neural Network