(20%) A produce dealer has a warehouse that stores a variety of fruits. He wants a machine capable of sorting the fruit according to the type. There is a conveyor belt on which the fruit is loaded. It...

Artifcial Inteligence

Extracted text: (20%) A produce dealer has a warehouse that stores a variety of fruits. He wants a machine capable of sorting the fruit according to the type. There is a conveyor belt on which the fruit is loaded. It is then passed through a set of sensors which measure 3 properties of the fruit: shape, texture, and weight. The sensor system is somehow rather primitive: Shape sensor :-1 if the fruit is round and 1 if it is more elliptical • Texture sensor :-1 if the surface is smooth, 1 if it is rough Weight sensor :-1 if the fruit is > 500g, 1 if is < 500g="" the="" sensor="" output="" will="" then="" be="" input="" to="" a="" neural="" networks="" based="" classifying="" system.="" as="" an="" ai="" engineer="" you="" are="" supposed="" to="" design="" (draw="" the="" architecture="" and="" determine="" the="" optimal="" weight="" w="" and="" bias="" b)="" a="" simple="" neural="" network="" (could="" be="" a="" single="" perceptron)="" that="" can="" be="" used="" to="" recognize="" the="" fruit="" so="" that="" it="" can="" be="" directed="" to="" the="" correct="" storage="" bin.="" as="" a="" startup="" case,="" the="" simple="" network="" will="" only="" be="" used="" for="" two="" type="" of="" fruit="" i.e.="" banana="" and="" apple.="" employ="" initial="" weight="" w="(0.5" -1.0="" -0.5)="" and="" b="0.5." datasets="" from="" the="" sensor="" are="" as="" follows:="" banana="(-1," 1,="" -1);="" apple="(1," 1,="">