Developing a fuzzy model based on subtractive clustering for road header performance prediction (original) (raw)
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Clustering Method of Layered Rocks Based on Fuzzy Logic
Mechanical properties of rocks have an important role in planning projects depends on recorgenizing and designing the civil and mining excavations.Existance and establishment of different civil these rocks materials (tunnels, ways, bridges, power plant and these examples are some of) makes knowing the engineering properties of the major important. Therefore; classification of rock with the use of proper and effective parameters which can be determined by simple and accurate experiments is so much important and has an important functional role. Considering this, in this research with preparing an application of MATLAB language, with the use of a data base and the fuzzy analysis as a strong analysis tool in issue uncertainty, with considering the simultaneous effect of parameters of Uniaxial compressive strength, module of elasticity, compressional wave velocity, and point load index of rock with obtaining various graphs and making connection and relationship between the effective parameters in the type of the rock and the results obtained from these experiments, will lead to an acceptable classification and we will obtain a classification (clustering) method.
Computers and Geotechnics, 2011
The rock engineering classification system is based on six parameters defined by Bieniawski [5] , who employed parallel sets of linguistic and numerical criteria that were acknowledged to influence the behaviour of rock masses and the stability of rock structures. Consequently, experts frequently relate rock joints and discontinuities as well as ground water conditions in linguistic terms, with rough calculations. Recently, intelligence system approaches such as artificial neural network (ANN) and neuro-fuzzy methods have been used successfully for time series modelling. Using neuro-fuzzy approaches, which enable the information that is stored in trained networks to be expressed in the form of a fuzzy rule base, would help to overcome this issue. This paper presents the results of a study of the application of neuro-fuzzy methods to predict rock mass rating. We note that the proposed weights technique was applied in this process. We show that neuro-fuzzy methods give better predicti...
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Machinery equipment selection, particularly mechanical excavators in mechanized mining operations, is one of the most important issues through a mine project planning and design, and has a remarkable effect on speed and cost of excavating operation. Therefore, it is an essential matter and needs to be concerned and managed appropriately. Alike other mechanized projects, mechanized coal mining is very machinery-intensive so that appropriate equipment selection plays a key role in project’s success and productivity. In this respect, it is crucial to consider the basic parameters such as geological and geotechnical properties of ore deposit, its surrounding strata, economic and technical parameters, etc through the selection process; hence, choosing the major equipment and mechanical miners such as roadheaders in mechanized coal mining is a multi-criteria decision making problem. A multi-criteria decision making method is used to rank available roadheaders based on a set of criteria, u...