Developing Fuzzy Inference Systems (FIS) For The Evaluation Of Multiple-Layer Lignite Deposits

The difficulties that rise during the evaluation of multiple-layer lignite deposits come from the deposit structure (alternating lignite layers with intercalated material of varying thickness), as well as from the limitations of the applied selective mining. Thin layers of lignite and interbedded waste layers are grouped under specified assumptions regarding thickness and ash content, to form the exploitable blocks. However, in practice the decision for excavating a block is made under subjective constraints of different importance or by using uncertain data. Advances in Fuzzy Inference Systems (FIS) have provided a new approach to the evaluation of multiple-layer lignite deposits. FIS have the ability to handle imprecise or incomplete or linguistically ambiguous information and to incorporate them into decision-making processes. In the developed FIS (Mamdani type) new linguistic variables, concerning with working conditions, operators? experience and production were involved. The FIS was used for the estimation of quality characteristics and reserves of the exploitable lignite produced from Southern Field mine, Ptolemais (Greece).