Integrating unascertained measurement and information entropy theory to assess blastability of rock mass

Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.

Optimization model of unascertained measurement for underground mining method selection and its application

An optimization model of underground mining method selection was established on the basis of the unascertained measurement theory.Considering the geologic conditions,technology,economy and safety production,ten main factors influencing the selection of mining method were taken into account,and the comprehensive evaluation index system of mining method selection was constructed.The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively.New measurement standards were constructed.Then,the unascertained measurement function of each evaluation index was established.The index weights of the factors were calculated by entropy theory,and credible degree recognition criteria were established according to the unascertained measurement theory.The results of mining method evaluation were obtained using the credible degree criteria,thus the best underground mining method was determined.Furthermore,this model was employed for the comprehensive evaluation and selection of the chosen standard mining methods in Xinli Gold Mine in Sanshandao of China.The results show that the relative superiority degrees of mining methods can be calculated using the unascertained measurement optimization model,so the optimal method can be easily determined.Meanwhile,the proposed method can take into account large amount of uncertain information in mining method selection,which can provide an effective way for selecting the optimal underground mining method.

Safety assessment of platform loadout procedures based on unascertained measures

Safety assessment of offshore platforms is an urgent task. Such assessments are now focusing on the structure, maintenance, and retirement of a platform. Some methods employed have many shortcomings. For example, they cannot make the reliability adequately explicable. Therefore, a mathematical tool, the unascertained measure, was introduced. First, the basic knowledge of the unascertained sets was introduced briefly. Second, the unascertained measure was defined and credible identification was set up. The method has been introduced into the fields for safety assessment of a jacket loadout procedure. Engineering practices showed that it can complete the safety assessment systematically and scientifically without any assumption. The work should have significance in theory and practice for offshore engineering.

Unascertained measurement classifying model of goal collapse prediction

Based on optimized forecast method of unascertained classifying,a unascer- tained measurement classifying model (UMC) to predict mining induced goaf collapse was established,The discriminated factors of the model are influential factors including over- burden layer type,overburden layer thickness,the complex degree of geologic structure, the inclination angle of coal bed,volume rate of the cavity region,the vertical goaf depth from the surface and space superposition layer of the goaf region.Unascertained mea- surement (UM) function of each factor was calculated.The unascertained measurement to indicate the classification center and the grade of waiting forecast sample was determined by the UM distance between the synthesis index of waiting forecast samples and index of every classification.The training samples were tested by the established model,and the correct rate is 100%.Furthermore,the seven waiting forecast samples were predicted by the UMC model.The results show that the forecast results are fully consistent with the ac- tual situation.

Assessment of Traffic Safety State of Ship Based on Unascertained Measure

Using the theory and method of unascertained measure, an unascertained measure model and the related confidence rule are established to assess the safety state of ship. Thus, the dangerous factors in the hull system can be identified, and the accident possibility, loss, and injury degree can be forcasted. An application result shows that the the proposed method is effective in assessment of the traffic safety of ships, and it is more simple in computation than the fuzzy synthetic evaluation method. The proposed method can provide a scientific basis for realizing shipping transportation security and formulating preventive measures.

Evaluation of Organizational Learning Ability Based on Fuzzy C-means and Unascertained Measure

The purpose of objective and quantitative evaluating the organizational learning ability is to make the enterprise have reliable criterions and operable procedures during the process of improving the organizational learning ability and founding learning organization. In this paper, an evaluating indicator system is established by analyzing the whole process of organizational learning; both qualitative and quantitative analyses are used, and a new combined evaluating method is presented. A measurement case involving twenty enterprises is given to prove the validity of this method. In conclusion, learning strategies are presented according to measurement result. This paper applies 4 models synthetically. The evaluating effect is superior to other methods.

Appraisal on the Regional Technological Innovation Ability Based on Unascertained Measure Method

In market economics, the regional technological innovation ability has become an important factor in the sustainable development of this region and important position in the region＇s competition. In this paper, the application of unascertained measure method in the ability of the regional technological innovation is studied. The appraisal index system is setup and the unascertained measure model is given . At last, an example is given to verify the theory model.

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.

Evaluation methods of man-machine-environment system for clean and safe production in phosphorus mines: A case study

Phosphorus is an essential element in agricultural production and chemical industry. However, since the risk of casualties and economic loss by mining accidents, the application of clean and safe production in phosphorus mines encounters great challenges. For this purpose, a man-machine-environment system composed of evaluation indexes was established, and the grading standards of indexes were defined. Firstly, the measurements of 39 qualitative indexes were obtained through the survey data. According to the measured values of 31 quantitative indexes, the measurements of quantitative indexes were calculated by linear measurement function(LM) and other three functions. Then the singleindex measurement evaluation matrixes were established. Secondly, the entropy weight method was used to determine the weights of each index directly. The analytic hierarchy process(AHP) was also applied to calculate the weights of index and index factor hierarchies after the established hierarchical model. The weights of system hierarchies were given by the grid-based fuzzy Borda method(GFB). The comprehensive weights were determined by the combination method of AHP and GFB(CAG). Furthermore, the multi-index comprehensive measurement evaluation vectors were obtained.Thirdly, the vectors were evaluated by the credible degree recognition(CDR) and the maximum membership(TMM)criteria. Based on the above functions, methods, and criteria, 16 combination evaluation methods were recommended.Finally, the clean and safe production grade of Kaiyang phosphate mine in China was evaluated. The results show that the LM-CAG-CDR is the most reasonable method, which can not only determine the clean and safe production grade of phosphorus mines, but also improve the development level of clean and safe mining of phosphorus mines for guidance.In addition, some beneficial suggestions and measures were also proposed to advance the clean and safe production grade of Kaiyang phosphorus mine.