#Contoh ini menggunakan mesin inferensi Tsukamoto #Dengan operasi-operasi sebagai berikut : #Union = min #Intersection = max #Implikasi = tsukamoto (khusus pada inferensi tsukamoto) #Domain distance = mf.linspace(200, 10000, 98001) area = mf.linspace(4, 20, 16001) facility = mf.linspace(0, 100, 10001) price = mf.linspace(250, 1500, 12501) #Fuzzy Set distanceNear = ["trapmf", -math.inf, -math.inf, 2000, 4000] distanceNearMf = mf.membership(distanceNear, distance) plt.plot(distance, distanceNearMf, label="Near") distanceMid = ["trapmf", 2000, 4000, 6000, 8000] distanceMidMf = mf.membership(distanceMid, distance) plt.plot(distance, distanceMidMf, label="Mid") distanceFar = ["trapmf", 6000, 8000, math.inf, math.inf] distanceFarMf = mf.membership(distanceFar, distance) plt.plot(distance, distanceFarMf, label="Far") plt.xlabel('Distance (m)') plt.ylabel('Membership') plt.title('Distance from Nearby University') plt.legend() plt.show() areaSmall = ["trapmf", -math.inf, -math.inf, 8, 10] areaSmallMf = mf.membership(areaSmall, area)
inpJarak = [500] inpJarakMf = [] inpLuas = [10] inpLuasMf = [] inpFasilitas = [60] inpFasilitasMf = [] #Domain jarak = mf.linspace(0, 10000, 10001) luas = mf.linspace(0, 20, 2001) fasilitas = mf.linspace(0, 100, 101) harga = mf.linspace(250, 1000, 75001) #Fuzzy Set jarakDekat = ["trapmf", -math.inf, -math.inf, 2000, 4000] jarakDekatMf = mf.membership(jarakDekat, jarak) plt.plot(jarak, jarakDekatMf) jarakSedang = ["trapmf", 2000, 4000, 6000, 8000] jarakSedangMf = mf.membership(jarakSedang, jarak) plt.plot(jarak, jarakSedangMf) jarakJauh = ["trapmf", 6000, 8000, math.inf, math.inf] jarakJauhMf = mf.membership(jarakJauh, jarak) plt.plot(jarak, jarakJauhMf) plt.show() luasSempit = ["trapmf", -math.inf, -math.inf, 8, 10] luasSempitMf = mf.membership(luasSempit, luas) plt.plot(luas, luasSempitMf) luasLuas = ["trapmf", 8, 10, math.inf, math.inf] luasLuasMf = mf.membership(luasLuas, luas) plt.plot(luas, luasLuasMf)