“…In addition to this, projection neural networks have emerged out as a promising tool in the field of fractional calculus also. Due to wide application in almost all branches of sciences, fractional differential equations have received remarkable attention in the field of mechanics, physics, chemistry, informatics, materials and several other applications [22,23]. To the best of our knowledge, very few results are available in literature for projection neural networks in the field of fractional calculus [24,25].…”