Analysis Hierarchy Process Model for Plain River Reach Health Assessment of the Luanhe River

In light of the ecological health problem occurring between the plain river reach between Daheiting and the estuary of the Luanhe River, three first-level indicators （river physical characteristic, eco-hydrological characteristic and socio-economic features） and corresponding fifteen second-level indicators such as river natural connectivity, water quantity, etc., were employed to establish the analysis hierarchy process （AHP） model. After fitting the AHP model with the data of 2005, the results show that the overall plain river reach health assessment score is 0.698 and the ecology is basically healthy. Moreover, construction of the Panjiakou Reservoir on the river mainstream destroyed the river natural morphologies, and finally contributed to the relatively low scores： 0 and 0.5 for river natural connectivity and river curve degree, respectively. It implicates that measures such as construction of ecological river course and reservoir dispatching should be taken into account in further restoration projects of the Luanhe River.

Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors

Coal burst is a severe hazard that can result in fatalities and damage of facilities in underground coal mines.To address this issue,a robust unascertained combination model is proposed to study the coal burst hazard based on an updated database.Four assessment indexes are used in the model,which are the dynamic failure duration(DT),elastic energy index(WET),impact energy index(KE)and uniaxial compressive strength(RC).Four membership functions,including linear(L),parabolic(P),S and Weibull(W)functions,are proposed to measure the uncertainty level of individual index.The corresponding weights are determined through information entropy(EN),analysis hierarchy process(AHP)and synthetic weights(CW).Simultaneously,the classification criteria,including unascertained cluster(UC)and credible identification principle(CIP),are analyzed.The combination algorithm,consisting of P function,CW and CIP(P-CW-CIP),is selected as the optimal classification model in function of theory analysis and to train the samples.Ultimately,the established ensemble model is further validated through test samples with 100%accuracy.The results reveal that the hybrid model has a great potential in the coal burst hazard evaluation in underground coal mines.