Investigation of deposits for traditional extraction activities (metals and coal) has generally been based on determining grade, or content, of the required material. In order to apply the grade concept to an ornamental rock such as slate, it is first necessary to define the variables that determine both the geotechnical recovery rate for the rock mass — which conditions the size of the extracted blocks – and the aesthetic features of the slate — which define the quality of the slabs as potential roofing material.
For this research, geotechnical and aesthetic data for a slate deposit were collected from 16 continuous core borehole samples. A fuzzy expert system was then developed using this data, defining the rock mass recovery rate and slab quality in accordance with the criteria of a slate expert, producing as a final output a zonation of the deposit in terms of top quality slate, medium quality slate or waste.
A mathematical model based on fuzzy logic was chosen due to the fact that the boundaries between different quality groups in a deposit are not clearly distinguished. Moreover, quality also depends on a company's infrastructures for transformation of the blocks, and also on its commercial strategies. 相似文献
A decision support system (DSS) has been developed to assist expert and non-expert users in the evaluation and selection of
eco-engineering strategies for slope protection. This DSS combines a qualitative hazard assessment of erosion and mass movements
with a detailed catalogue of eco-engineering strategies for slope protection of which the suitability is evaluated in relation
to the data entered. The slope decision support system (SDSS) is a knowledge based DSS in which knowledge is stored in frames
containing rules that can evaluate the available information for a project, stored as project specific information (PSI) in
a data file. The advantages of such a system are that it accepts incomplete information and that the qualitative nature of
the information does not instil the user with a sense of unjustified exactitude. By its multidisciplinary and progressive
nature, the DSS will be of value during the initial stages of an eco-engineering project when data collection and the potential
of different eco-engineering strategies are considered. The accent of the output of the DSS is on the application of eco-engineering
strategies for slope protection as an environmentally-friendly solution aiding sustainable development. For its acceptance
within the engineering community, the DSS needs to prove its predictive capacity. Therefore, its performance has been benchmarked
against successful and unsuccessful cases of slope stabilisation using eco-engineering. The target audience and the areas
of application of this DSS are reviewed and the strategies for further development in this area suggested. 相似文献