Data mining is an iterative progress in which evolution is defined by detection, through usual or manual methods. The discovered knowledge can be used for different applications for example healthcare industry. The heart disease accounts to be the leading cause of death worldwide. It is difficult for medical practitioners to predict the heart attack as it is complex task that requires experienc...

The data mining techniques can extract the hidden information from the large databases. It helps to find the relationships and patterns from the data. Data mining is used for various applications such as business organizations, e-commerce, health care industry, scientific and engineering. In the health care industry the data mining is mainly used for predicting the diseases from the datasets. I...

the first step in mining activities is rock excavation in both mine development and production. constant pressure for cost reduction and creating an improved/safe work environment for personnel has naturally resulted in increased use of mechanical excavation systems in many mining operations. also, mechanical excavation and mining is more compatible with automation, meaning possibility of reduc...

The goal of this manuscript is to provide an efficient approach to the process of the recruitment and selection of candidates in the mining industry. The proposed approach is based on the use of MCDM models for personnel selection in the mining industry; the approach will provide an MCDM model for the personnel selection based on the SWARA ant the MULTIMOORA methods. The efficiency and usabilit...

Data mining is widely used in business applications including market segmentation, fraud detection, credit risk analysis as well as many other applications. In the construction domain however, the use of data mining has been extremely limited. Data mining usually requires the availability of a large database of previous cases to be analyzed. Therefore applications in the construction industry m...