Results 21 to 30 of about 2,055 (161)

Parallel Computation of Rough Set Approximations in Information Systems with Missing Decision Data

Computers, 2018
The paper discusses the use of parallel computation to obtain rough set approximations from large-scale information systems where missing data exist in both condition and decision attributes.
Thinh Cao, Koichi Yamada, Muneyuki Unehara, Izumi Suzuki, Do Van Nguyen   +4 more
doaj   +1 more source

Computing marginals using MapReduce [PDF]

Journal of Computer and System Sciences, 2018
We consider the problem of computing the data-cube marginals of a fixed order $k$ (i.e., all marginals that aggregate over $k$ dimensions), using a single round of MapReduce. The focus is on the relationship between the reducer size (number of inputs allowed at a single reducer) and the replication rate (number of reducers to which an input is sent ...
Afrati, Foto N., Sharma, Shantanu, Ullman, Jonathan R., Ullman, Jeffrey D.   +3 more
openaire   +3 more sources

Spatial hotspot detection using polygon propagation

International Journal of Digital Earth, 2019
Spatial scan statistics is one of the most important models in order to detect high activity or hotspots in real world applications such as epidemiology, public health, astronomy and criminology applications on geographic data. Traditional scan statistic
Satya Katragadda, Jian Chen, Shaaban Abbady   +2 more
doaj   +1 more source

Evaluating MapReduce for seismic data processing using a practical application

Tongxin xuebao, 2012
Huge amounts of seismic data undergo complex iterative processing in the oil industry to get knowledge of the earth’s subsurface structure to detect where oil can be found and recovered.To evaluate the suitability of MapReduce for seismic processing ...
Chang-hai ZHAO, Hai-hua YAN, Xiao-peng LIU, Deng XIONG, Xiao-hua SHI   +4 more
doaj   +2 more sources

A Distributed Approach for High-Dimensionality Heterogeneous Data Reduction

IEEE Access, 2019
The recent explosion of data size in number of records and attributes has triggered the development of a number of Big Data analytics as well as parallel data processing methods and algorithms.
Rania Mkhinini Gahar, Olfa Arfaoui, Minyar Sassi Hidri, Nejib Ben Hadj-Alouane   +3 more
doaj   +1 more source

An alternative C++-based HPC system for Hadoop MapReduce

Open Computer Science, 2022
MapReduce (MR) is a technique used to improve distributed data processing vastly and can massively speed up computation. Hadoop and MR rely on memory-intensive JVM and Java. A MR framework based on High-Performance Computing (HPC) could be used, which is
Srinivasakumar Vignesh, Vanamoorthy Muthumanikandan, Sairaj Siddarth, Ganesh Sainath   +3 more
doaj   +1 more source

Multithread Approximation: An OpenMP Constructor

Concurrency and Computation: Practice and Experience, Volume 38, Issue 4, February 2026.
ABSTRACT This study introduces an OpenMP construct designed to simplify and unify the integration of approximate computing techniques into shared‐memory parallel programs. Approximate Computing leverages the inherent error tolerance of many applications to trade computational accuracy for gains in performance and energy efficiency.
João Briganti de Oliveira, Rogério Aparecido Gonçalves, João Fabrício Filho   +2 more
wiley   +1 more source

Applying MapReduce to Conformance Checking

Труды Института системного программирования РАН, 2018
Process mining is a relatively new research field, offering methods of business processes analysis and improvement, which are based on studying their execution history (event logs).
I. S. Shugurov, A. A. Mitsyuk
doaj   +1 more source

Neural Network Models for Solar Irradiance Forecasting in Polluted Areas: A Comparative Study

Energy Science &Engineering, Volume 14, Issue 2, Page 935-961, February 2026.
Pollution‐aware hybrid ensemble model is proposed to forecast solar irradiance across eight diverse cities. The model integrates MLP, RNN, and NARX to handle varying atmospheric pollution levels. The model outperforms state‐of‐the‐art methods with enhanced accuracy and interpretability on standard solar irradiance data set.
Mujtaba Ali, Muhammad Yaqoob Javed, Aamer Bilal Asghar, Khurram Hashmi, Abbas Javed, Basem Alamri, Krzysztof Ejsmont   +6 more
wiley   +1 more source

Fast clustering using MapReduce [PDF]

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011
Clustering problems have numerous applications and are becoming more challenging as the size of the data increases. In this paper, we consider designing clustering algorithms that can be used in MapReduce, the most popular programming environment for processing large datasets. We focus on the practical and popular clustering problems, $k$-center and $k$
Ene, Alina, Im, Sungjin, Moseley, Benjamin   +2 more
openaire   +2 more sources