fuzzy cognitive maps (fcms) have successfully been applied in numerous domains to show the relations between essential components in complex systems. in this paper, a novel learning method is proposed to construct fcms based on historical data and by using meta-heuristic: genetic algorithm (ga), simulated annealing (sa), and tabu search (ts). implementation of the proposed method has demonstrat...

in today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. in respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. commercial organiza...

introduction: the aim of this study was to determine the performance of data mining techniques for predicting the causes of traumatic brain injuries in khatamolanbya hospital, zahdan city. method: in this cross–sectional, the study population included all patients who died of brain injury. data were collected by the use of a researcher- made check list, provided under the direct observation of ...

basically, medical diagnosis problems are the most effective component of treatment policies. recently, significant advances have been formed in medical diagnosis fields using data mining techniques. data mining or knowledge discovery is searching large databases to discover patterns and evaluate the probability of next occurrences. in this paper, bayesian classifier is used as a non-linear dat...

conclusions our study showed that arm is a useful approach in determining which combinations of variables or predictors occur together frequently, in people who will develop diabetes. the arm focuses on joint exposure to different combinations of risk factors, and not the predictors alone. background type 2 diabetes, common and serious global health concern, had an estimated worldwide prevalenc...

background : data mining has an interdisciplinary field including various scientific disciplines such as: database systems, statistics, machine learning, artificial intelligence and the others. in the field of medical, data mining algorithms can help physicians to diagnose diseases and chose the best type of treatment. hepatocellular carcinoma has the most common type of liver cancer. given the...

The segmentation of the picture (and, implicitly, the segmentation method used) is one of the three important steps in microarray image processing, together with spot gridding and information extraction. It directly affects the accuracy of gene expression analysis in the data mining process that follows. In 2001 a segmentation method for arbitrary pictures using the Active Contours Without Edge...

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptim...

Cluster analysis has been widely used in various disciplines such as pattern recognition, computer vision, and data mining. In this work we investigate the applicability of two spatial clustering algorithms, namely DBSCAN and STING, to a new problem domain: Color segmentation of skin lesion (tumor) images. Automated segmentation is a key step in the computerized analysis of skin lesion images s...