Methods of predicting reliability information of storage devices and methods of operating storage devices

A method of operating a storage device including a plurality of nonvolatile memories, the method comprising:

• predicting reliability information of the storage device;
• and
• performing a read operation on the storage device based on a result of predicting the reliability information,
• wherein the predicting the reliability information of the storage device comprises:
• outputting a model request signal corresponding to an optimal machine learning model by selecting one of a plurality of machine learning models as the optimal machine learning model, with each of the plurality of machine learning models configured to generate first reliability information related to the plurality of nonvolatile memories and the selecting of the one of the plurality of machine learning models based on deterioration characteristic information obtained by accumulating deterioration information related to the plurality of nonvolatile memories and deterioration phase information representing a degree of deterioration of the plurality of nonvolatile memories;
• receiving first parameters of the optimal machine learning model based on the model request signal;
• and
• generating the first reliability information based on the deterioration characteristic information and the first parameters.

A method of predicting reliability information of a storage device including a plurality of nonvolatile memories, the method comprising:

• collecting deterioration characteristic information by accumulating deterioration information of the plurality of nonvolatile memories;
• generating deterioration phase information based on the deterioration characteristic information, wherein the deterioration phase information represents a degree of the deterioration of the plurality of nonvolatile memories as one of a plurality of deterioration phases;
• selecting one of a plurality of machine learning models as an optimal machine learning model based on the deterioration phase information and the deterioration phase information;
• outputting a model request signal corresponding to the optimal machine learning model;
• receiving first parameters of the optimal machine learning model based on the model request signal;
• and
• generating first reliability information based on the deterioration characteristic information and the first parameters;
• wherein:
• selecting the one of the plurality of machine learning models comprises selecting a first machine learning model from among the plurality of machine learning models as the optimal machine learning model when the deterioration phase information corresponds to an early deterioration phase, and selecting a second machine learning model different from the first machine learning model from among the plurality of machine learning models as the optimal machine learning model when the deterioration phase information corresponds to a middle deterioration phase that is subsequent to the early deterioration phase.