An attribute recognition model for safe thickness assessment between concealed karst cave and tunnel

An attribute recognition model for safe thickness assessment between a concealed karst cave and a tunnel is established based on the attribute mathematic theory.The model can be applied to carrying out risk classification of the safe thickness between a concealed karst cave and a tunnel and to guarantee construction’s safety in tunnel engineering.Firstly,the assessment indicators and classification standard of safe thickness between a concealed karst cave and a tunnel are studied based on the perturbation method.Then some attribute measurement functions are constructed to compute the attribute measurement of each single index and synthetic attribute measurement.Finally,the identification and classification of risk assessment of safe thickness between a concealed karst cave and a tunnel are recognized by the confidence criterion.The results of two engineering application show that the evaluation results agree well with the site situations in construction.The results provide a good guidance for the tunnel construction.

Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment

Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.

A technique for detecting and attributing changes in species distributions to climate change over time

The global climate has changed substantially over the last 100 years,and associated changes in species distribution limits have occurred in recent decades.Climate change presents a challenge for biodiversity conservation on a global scale.The ability to detect changes in species distributions and attribute them to past climate change is crucial for the accurate prediction of future species distributions and for biodiversity conservation.This study proposes a technique for the quantitative detection of species distribution changes and their attribution to past climate change.An attribution value was defined to describe the extent to which the distributional changes for observed species could be attributed to climate change.The calculation thereof involved the following steps:(1)construction of a time series of observed species distributions and climatic factors,(2)estimation of the correlations between changes in species distributions and climatic factors,(3)prediction of changes in species distributions as driven by climatic factors,(4)estimation of the consistency between observed and predicted changes in species distributions,and(5)estimation of the attribution value.Furthermore,using nine snake species found in China as examples,we demonstrated in detail the practical application of this technique.This technique can be used to identify,based on global species distribution and climate data,the effects of climate change on species distributions over the past years on a global scale.