An operation method of a storage device configured to manage a plurality of nonvolatile memories with a plurality of physical streams, the method comprising: receiving an input/output request from an external host device; determining a 0-th virtual stream identifier corresponding to the received input/output request; extracting a 0-th representative value from a 0-th virtual stream feature of a 0-th virtual stream corresponding to the determined 0-th virtual stream identifier; extracting a first representative value and a second representative value respectively corresponding to a first physical stream and a second physical stream of the plurality of physical streams; calculating distance information including a first similarity between the 0-th virtual stream and the first physical stream and a second similarity between the 0-th virtual stream and the second physical stream, based on the extracted 0-th, first, and second representative values; assigning (S170, S180) one of the plurality of physical streams to the 0-th virtual stream, based on the distance information; and performing an operation corresponding to the input/output request, at the assigned physical stream, wherein the extracting of the 0-th representative value, the extracting of the first representative value and the second representative value, and the calculating of the distance information are performed by using a learning model learned in advance through machine learning, characterised in that: the learning model includes: a 0-th extracting model being a 0-th convolution layer configured to extract the 0-th representative value from the 0-th virtual stream feature; a first extracting model being a first convolution layer configured to extract the first representative value, from among the plurality of representative values, from a first virtual stream feature corresponding to the first physical stream of the plurality of physical streams; and a jointed fully-connected layer configured to calculate the distance information including the first similarity between the 0-th virtual stream and the first physical stream based on the 0-th representative value and the first representative value, wherein the 0-th convolution layer and the first convolution layer are further configured to share a plurality of learning parameters. receiving an input/output request from an external host device; determining a 0-th virtual stream identifier corresponding to the received input/output request; extracting a 0-th representative value from a 0-th virtual stream feature of a 0-th virtual stream corresponding to the determined 0-th virtual stream identifier; extracting a first representative value and a second representative value respectively corresponding to a first physical stream and a second physical stream of the plurality of physical streams; calculating distance information including a first similarity between the 0-th virtual stream and the first physical stream and a second similarity between the 0-th virtual stream and the second physical stream, based on the extracted 0-th, first, and second representative values; assigning (S170, S180) one of the plurality of physical streams to the 0-th virtual stream, based on the distance information; and performing an operation corresponding to the input/output request, at the assigned physical stream, wherein the extracting of the 0-th representative value, the extracting of the first representative value and the second representative value, and the calculating of the distance information are performed by using a learning model learned in advance through machine learning, characterised in that: the learning model includes: a 0-th extracting model being a 0-th convolution layer configured to extract the 0-th representative value from the 0-th virtual stream feature; a first extracting model being a first convolution layer configured to extract the first representative value, from among the plurality of representative values, from a first virtual stream feature corresponding to the first physical stream of the plurality of physical streams; and a jointed fully-connected layer configured to calculate the distance information including the first similarity between the 0-th virtual stream and the first physical stream based on the 0-th representative value and the first representative value, wherein the 0-th convolution layer and the first convolution layer are further configured to share a plurality of learning parameters. a 0-th extracting model being a 0-th convolution layer configured to extract the 0-th representative value from the 0-th virtual stream feature; a first extracting model being a first convolution layer configured to extract the first representative value, from among the plurality of representative values, from a first virtual stream feature corresponding to the first physical stream of the plurality of physical streams; and a jointed fully-connected layer configured to calculate the distance information including the first similarity between the 0-th virtual stream and the first physical stream based on the 0-th representative value and the first representative value, wherein the 0-th convolution layer and the first convolution layer are further configured to share a plurality of learning parameters.