Review on the Development of Mining Method Selection to Identify New Techniques Using a Cascade-Forward Backpropagation Neural Network

Table 7

Results of using CFBPNN for MMS with the given parameters.

Mining method	No.			O2	O1	b2	b1	w21 w2	w1	Properties/input
		Rank	2.72904	4.35504	6.128579	8.803278	3.4113	5.4438	0.8
Open-pit mining	1		7.933731	0.01356	4.96736			0.0339	12.4184	0.4
Block caving	2	Method 8		−3.25104	−7.5585			−5.4184	−12.5975	0.6
Sublevel stoping	3	Cut and fill stoping		−0.85974	−0.10926			−1.4329	−0.1821	0.6
Sublevel caving	4			0.0301	1.11132			0.301	11.1132	0.1
Longwall mining	5			0.26115	0.68993			2.6115	6.8993	0.1
Room and pillar	6			0.42414	−13.6415			0.7069	−22.7358	0.6
Shrinkage stoping	7			7.933731	−1.38231			−2.78847
Cut and fill stoping	8				−0.88147
Top slicing	9
Square set stoping	10

The bold value means the optimal selected mining method.