Mining method selection is among the most critical and problematic points in mining engineering profession. Choosing a suitable method for a given ore-body is very important for the economics, safety and the productivity of the mining work. In the past studies there are attempts to build up a systematic approach to help the engineers to make this selection. But, these approaches work based on s...

Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteri...

Underground mining method selection is one of the most crucial decisions that should be made by mining engineers. Choosing a suitable underground mining method to carry out extraction from a mineral deposit is very important in terms of the economics, safety and the productivity of mining operations. The aim of this study is developing a fuzzy model to selection the optimum mining method by usi...

Experts in finance and accounting select feature subset for corporate financial distress prediction according to their professional understanding of the characteristics of the features, while researchers in data mining often believe that data alone can tell everything and they use various mining techniques to search the feature subset without considering the financial and accounting meanings of...

objective: diabetes is one of the most common metabolic diseases. earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...

Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two groups of breast cancer patients (malignant and benign). The proposed approach, AP-AMBFA, con...

Background: Breast cancer is the second leading cause of cancer death in women, after lung cancer. Due to the importance of predicting this disease, the use of data mining methods in medical research is more significant than before. Data mining algorithms can be a great help in preventing the development of lymphedema in patients. The aim Of this study was to create a diagnosis system that can ...