A Cloud Model-based Prediction Method for Scientific Cultivation with Smaller Flower Seed Bulbs

A Cloud Model-based Prediction Method for Scientific Cultivation with Smaller Flower Seed Bulbs

Aiming at insensitivity to growth regulators during the cultivation of smaller flower seed bulbs, the cloud model-based prediction method is proposed. Define the growth feature cloud model, replace the intra-class distance calculation with the degree of certainty of the growth parameters on its cloud model, set the feature weight according to the sensitivity of the growth feature to the growth regulator in smaller seed bulbs cultivation, and finally complete the classification prediction by calculating the degree of certainty of all the feature values by weighting. According to the goal of growth, growth regulators are scientifically selected through effectively prediction to control cultivation of smaller seed bulbs. Finally, the experiment of smaller lily bulbs cultivation proves that this method is obviously superior to the traditional conventional classification method and can better control the scientific cultivation of smaller seed bulbs. Next, we will expand the number and variety of experimental data and further adjust the model parameters to make it more universal and accurate.