Data Stream Mining
نویسندگان
چکیده
منابع مشابه
Application of continuous restricted Boltzmann machine to detect multivariate anomalies from stream sediment geochemical data, Korit, East of Iran
Anomaly separation using stream sediment geochemical data has an essential role in regional exploration. Many different techniques have been proposed to distinguish anomalous from study area. In this research, a continuous restricted Boltzmann machine (CRBM), which is a generative stochastic artificial neural network, was used to recognize the mineral potential area in Korit 1:100000 sheet, loc...
متن کاملSeparation of Geochemical Anomalies Using Factor Analysis and Concentration-Number (C-N) Fractal Modeling Based on Stream Sediments Data in Esfordi 1:100000 Sheet, Central Iran
The aim of this study is separation of Fe2O3, TiO2 and V2O5 anomalies in Esfordi 1:100,000 sheet which is located in Bafq district, Central Iran. The analyzed elements of stream sediment samples taken in the area can be classified into 5 groups (factors) by factor analysis. The Concentration–Number (C-N) fractal model was used for delineation of the Fe2O3, TiO2 and V2O5 thresholds. According to...
متن کاملUsing stream sediment data to determine geochemical anomalies by statistical analysis and fractal modeling in Tafrash Region, Central Iran
Iranian Cenozoic magmatic belt, known as Urumieh-Dokhtar, is recognized as an important polymetallic mineralization which hosts porphyry, epithermal, and polymetallic skarn deposits. In this regard, multivariate analyses are generally used to extract significant anomalous geochemical signature of the mineral deposits. In this study, stepwise factor analysis, cluster analysis, and concentration–...
متن کاملNetwork Big Data: A Literature Survey on Stream Data Mining
With the rapid development of Internet, the internet of things and other information technology, big data usually exists in cyberspace as the form of the data stream. It brings great benefits for information society. Meanwhile, it also brings crucial challenges on big data mining in the data stream. Recently, academic and industrial communities have a widespread concern on massive data mining p...
متن کاملData Stream Mining: the Bounded Rationality
The developments of information and communication technologies dramatically change the data collection and processing methods. Data mining is now moving to the era of bounded rationality. In this work we discuss the implications of the resource constraints impose by the data stream computational model in the design of learning algorithms. We analyze the behavior of stream mining algorithms and ...
متن کاملApplication of Data-Mining Algorithms in the Sensitivity Analysis and Zoning of Areas Prone to Gully Erosion in the Indicator Watersheds of Khorasan Razavi Province
Extended abstract 1- Introduction Gully erosion is one of the most important sources of sediment in the watersheds and a common phenomenon in semi-arid climate that affects vast areas with different morphological, soil and climatic conditions. This type of erosion is very dangerous due to the transfer of fertile soil horizons, and the reduction of water holding capacity also is a factor for s...
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