In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...

This paper deals with the study of how data mining is used in cloud computing. Data Mining is a process of extracting potentially useful information from raw data. State of the art research in data mining is focusing on loosely distributed regionalized large scale databases using cloud computing for business applications. Cloud computing poses a diversity of challenges in data mining operation ...

Outlier detection is an important method in data mining. Although Denclue algorithm particularly good at finding clusters of arbitrary shape and detecting outliers, it does not protect the user's privacy well operation process. In this paper, differential technology introduced into to ensure security application outlier detection. Firstly, used add Laplacian noise density realize sensitive info...

Observers have expressed concern that Chinese mining companies operating in Latin America are more egregious violators of labor and environmental standards than other mining companies. Critics point to the case of one operation in particular—Shougang Hierro Peru—as evidence of China’s threat to Latin American labor and environment. We combine archival research in Peru, personal interviews, and ...

Amankwah, H. (2011). Mathematical Optimization Models and Methods for Open-Pit Mining. Doctoral dissertation. ISBN 978-91-7393-073-4. ISSN 0345-7524. Open-pit mining is an operation in which blocks from the ground are dug to extract the ore contained in them, and in this process a deeper and deeper pit is formed until the mining operation ends. Mining is often a highly complex industrial operat...

Evaluating enterprise quality management system operation effectiveness, mining and extracting the fuzzy rules of affecting factors of enterprise quality management system operation effectiveness are important ways to solve practical quality problems and improve quality performance. This study integrates and combines statistical analysis methods of improved entropy method, catastrophe progressi...

Due to the exponential growth of hardware technology particularly in the field of electronic data storage media and processing such data, has raised serious issues related in order to protect the individual privacy like ethical, philosophical and legal. Data mining techniques are employed to ensure the privacy. Privacy Preserving Data Mining (PPDM) techniques aim at protecting the sensitive dat...

Association rule mining is a fundamental and vital functionality of data mining. Most of the existing real time transactional databases are multidimensional in nature. In this paper, a novel algorithm is proposed for mining hybrid-dimensional association rules which are very useful in business decision making. The proposed algorithm uses multi index structures to store necessary details like it...

Combined with virus evolutionary mechanism, the virus evolutionary genetic model algorithm which oriented workflow mining is put forward. It is based on the original main population that infection the population of individuals. First, in the workflow virus evolutionary mechanism introduction, it needs Petri net and causal relationship with matrix, the population of virus of individuals to chrom...

This paper proposes a new algorithm to find the optimization method of reactive regulation in power system to solve the problem of the var compensation and voltage control in center-substations. Using the daily data collected in power substations, the algorithm is combined with improved ant colony algorithm and Apriori data mining techniques. The mathematic model of var optimization of power sy...