data mining techniques have been used widely in the area of customer relationship management (crm). in this study, we have applied data mining techniques to address a problem in business-to-business (b2b) setting. in a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. segmentation is a useful tool for identifying groups...

spike sorting is a class of techniques used in the analysis of electrophysiological data. studying the dynamics of neural activity via electrical recording relies on the ability to detect and sort neural spikes recorded from a number of neurons by the same electrode. this article reviews methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting.

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

The fuzzy c-means clustering algorithm is a useful tool for clustering; but it is convenient only for crisp complete data. In this article, an enhancement of the algorithm is proposed which is suitable for clustering trapezoidal fuzzy data. A linear ranking function is used to define a distance for trapezoidal fuzzy data. Then, as an application, a method based on the proposed algorithm is pres...

due to simple operation and no needs for expensive infrastructure construction to convey water from a source to farm lands, groundwater becomes the most important sources of agricultural water supply in iran. however, the contamination of aquifers is a major concern in many countries, specifically in areas without effective groundwater protection and management. therefore, groundwater vulnerabi...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...