Agricultural input real-time classification prediction method based on SSDA-HELM-SOFTMAX. The agricultural input real-time classification prediction method is based on SSDA-HELM-SOFTMAX

An SSDA-HELM-SOFTMAX-based agricultural input real-time classification prediction method comprises the following steps of collecting data before and after agricultural input, preprocessing the data, obtaining a classification prediction model from a training sample set, and inputting a test sample to obtain a classification prediction result; the prediction model adopts a self-coding neural network layer-by-layer pre-training and fine adjustment mode to obtain initialization parameters; the method comprises the following steps: extracting a feature value of an SSDA-HELM, removing a decoding part of the SSDA, connecting the SSDA-HELM with a hierarchical structure ELM network, performing initialization setting on the SSDA-HELM by using an initialization weight to obtain an optimal solution,and sending the extracted feature value into an SOFTMAX classifier; according to the method, the SSDA-HELM-SOFTMAX-based agricultural input classification prediction model is constructed, the prediction model has the excellen