A generalized linguistic gained and lost dominance score method for landslide hazard treatment

Abstract

Reducing the risk of landslide hazards necessitates a prompt emergency decision regarding landslides, particularly when a hasty investigation lacks abundant data. Thus, the experience and opinions of experts, which are typically expressed in linguistic terms rather than exact values, can be utilized to the fullest extent to facilitate this process. Here I extend the gained and lost dominance score (GLDS) method to a generalized linguistic setting for modeling collective cognition in the selection of landslide treatment schemes for an open-pit mine. To do so, a generalized qualitative scale considering two cognitive bias arguments and one granularity parameter of linguistic term sets (LTS), which constitutes a generalized LTS that allows experts to express their evaluations in a flexible way, is presented to capture precise semantics of linguistic evaluations. Furthermore, several aggregation operators are given to deal with the generalized LTS for information fusion. To promote the application of the GLDS method within the context of multi-expert heterogeneous linguistic environment, I develop the framework of a generalized GLDS method by improving three aspects (i.e., the construction of dominance flow, the computing of lost dominance scores and the establishment of final aggregation function) of the classical one. Lastly, the effectiveness of the proposed method is examined by solving the multiple criteria decision-making problem we encountered as well as comparing with other outranking methods. The lattice anchored technique coupled with real-time monitoring is picked out to treat the landslide, which mitigates the production pressure in this high-slope open-pit mine.