“…Compared with DL algorithms that require a vast of data, one important advantage for SOMs is to conduct steady learning with relatively lower computational resources and calculation costs. Recent research examples of clustering, visualization, recognition, classification, and analyses using SOMs comprise medical system applications [ 28 , 29 , 30 , 31 , 32 ], social infrastructure maintenance [ 33 , 34 , 35 , 36 , 37 , 38 ], consumer products and services [ 39 , 40 , 41 , 42 , 43 ], food and smart farming [ 44 , 45 , 46 ], and recycling and environmental applications [ 47 , 48 , 49 , 50 , 51 , 52 , 53 ]. We employed SOMs and their variants for the task of classification and visualization of mood states.…”