نتایج جستجو برای: means algorithm then
تعداد نتایج: 1703175 فیلتر نتایج به سال:
This study applied a prediction-based portfolio optimization model to explore the results of portfolio predicament in the Tehran Stock Exchange. To this aim, first, the data mining approach was used to predict the petroleum products and chemical industry using clustering stock market data. Then, some effective factors, such as crude oil price, exchange rate, global interest rate, gold price, an...
Abstract: Although all university majors are prominent and the necessity of their presences is of no question, they might not have the same priority basis considering different resources and strategies that could be spotted for a country. This paper focuses on clustering and ranking university majors in Iran. To do so, a model is presented to clarify the procedure. Eight different criteria are ...
Image segmentation is a fundamental step in many of image processing applications. In most cases the image’s pixels are clustered only based on the pixels’ intensity or color information and neither spatial nor neighborhood information of pixels is used in the clustering process. Considering the importance of including spatial information of pixels which improves the quality of image segmentati...
Customer classification using k-means algorithm for optimizing the transportation plans is one of the most interesting subjects in the Customer Relationship Management context. In this paper, the real-world data and information for a spare-parts distribution company (ISACO) during the past 36 months has been investigated and these figures have been evaluated using k-means tool developed for spa...
the subjects of the study are only the tefl teachers and students at gilan university. to obtain the desired data, a questionnaire which was based on the theories and disecussions gathered, was used as the main data gathering instrument. to determine the degree of relationship between variables, covariance and pearson product moment correlation coefficient were the formulas applied. the data we...
Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...
In this paper, we propose a novel hybrid genetic algorithm (GA) that finds a globally optimal partition of a given data into a specified number of clusters. GA's used earlier in clustering employ either an expensive crossover operator to generate valid child chromosomes from parent chromosomes or a costly fitness function or both. To circumvent these expensive operations, we hybridize GA with a...
In this paper we provide a fully distributed implementation of the k-means clustering algorithm, intended for wireless sensor networks where each agent is endowed with a possibly high-dimensional observation (e.g., position, humidity, temperature, etc.). The proposed algorithm, by means of one-hop communication, partitions the agents into measure-dependent groups that have small ingroup and lar...
texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...
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