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A Parallel Weighted Decision Tree Classifier for Complex Spatial Landslide Analysis: Big Data Computation Approach

P. Anbalagan, R.M. Chandrasekaran
2015 International Journal of Computer Applications  
The characteristics of complexity formulate an extreme challenge for discovering useful knowledge from the big data. Spatial data is complex big data.  ...  Keywords Big Data, Classifier, Spatial Data, Map Reduce, Landslide.. HACE theorem [15] has been presented which characterizes the features of the Big Data revolution, and proposes a Big  ...  The data collected from various research institutes related to landslide helped to predict and analyze the landslide susceptibility. The spatial landslide data is one of the complex big data.  ... 
doi:10.5120/ijca2015905346 fatcat:jpabnjsvd5gnpi7fwhrqepykpm

Smart Grid Big Data Analytics: Survey of Technologies, Techniques, and Applications

Dabeeruddin Syed, Ameema Zainab, Shady S. Refaat, Haitham Abu-Rub, Othmane Bouhali
2020 IEEE Access  
This provides various opportunities associated with the collected big data. Hence, the triumph of the smart grid energy paradigm depends on the factor of big data analytics.  ...  This includes the effective acquisition, transmission, processing, visualization, interpretation, and utilization of big data.  ...  One of the earlier practical works on big data analytics was based on the Naive Bayes classification method using the MapReduce paradigm for novel transient power quality assessment [76] .  ... 
doi:10.1109/access.2020.3041178 fatcat:awgtqx6nordadbtjn2a4v4nxe4

FMRI BRAIN IMAGE SEGMENTATION AND CLASSIFIATION USING BIG DATA ANALYTICS

K. Mahadevan, S. parkavi
2020 International Journal of Recent Trends in Engineering and Research  
However, the amount of data is far too much for manual analysis, which has been one of the biggest obstacles in the effective use of MRI.  ...  This is because different processing steps rely on accurate segmentation of anatomical regions.  ...  The first classifier based on feed forward back-propagation artificial neural network (FP-ANN) and 8.HYBRID INTELLIGENT TECHNIQUES FOR MRI BRAIN IMAGES CLASSIFICATION the second classifier is based on  ... 
doi:10.23883/ijrter.conf.20200315.033.snada fatcat:rmsslknwwvaozbn6qt2xirp33a

An Improved Particle Swarm Optimization based classification model for high dimensional medical disease prediction

P R.Sudha Rani, Dr K.Kiran Kumar
2018 International Journal of Engineering & Technology  
The main objective of the feature selection based hybrid classifier is to classify the high dimensional data for large medical feature set.  ...  Proposed filtered based hybrid classifier is usually designed and implemented to improve the medical prediction rate on high dimensional data.  ...  [7] model emphasizes on some commonly implemented gene expression classification schemes based on MapReduce framework.  ... 
doi:10.14419/ijet.v7i2.7.10880 fatcat:edvudekixzcflc2t2jlf4gywby

Vibrating Particles System Algorithm for Solving Classification Problems

Mohammad Wedyan, Omar Elshaweesh, Enas Ramadan, Ryan Alturki
2022 Computer systems science and engineering  
Big data is a term that refers to a set of data that, due to its largeness or complexity, cannot be stored or processed with one of the usual tools or applications for data management, and it has become  ...  Almost immediately thereafter, the term "big data mining" emerged, i.e., mining from big data even as an emerging and interconnected field of research.  ...  Big Data Mining Big data mining approaches aim for more than just retrieving desired data or revealing hidden links and patterns between numerical parameters.  ... 
doi:10.32604/csse.2022.024210 fatcat:szo7fl5qr5b63bfncylvx3fc4i

Big data challenge: a data management perspective

Jinchuan Chen, Yueguo Chen, Xiaoyong Du, Cuiping Li, Jiaheng Lu, Suyun Zhao, Xuan Zhou
2013 Frontiers of Computer Science  
Acknowledgements This work was partially done when the authors worked in SA Center for Big Data Research in Renmin University of China.  ...  This Center is funded by a Chinese National "111" Project "Attracting International Talents in Data Engineering Research".  ...  As a result, some techniques of machine learning may help to understand the trends of data, classify big data into categories, detect similarities and predict the future based on the past.  ... 
doi:10.1007/s11704-013-3903-7 fatcat:iialac4ksbgkthayla4sioxtcq

Editorial

Srikanta Patnaik, Srikanta Patnaik
2018 Journal of Intelligent & Fuzzy Systems  
The next paper entitled "Simplified model for estimating the punching load and deformation of RC flat plate based on big data mining" by Chuanteng Huang and Zhijun Wang), proposed the validation method  ...  The next paper entitled, "An analytical punching shear model of RC slab-column connection based on big data" by Chuanteng Huang, and et al. proposed a theoretical method for analysis the punching shear  ... 
doi:10.3233/jifs-169562 fatcat:2qknpgafxjdaza2ppepzpwxreu

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

Abbas Mardani, Mehrbakhsh Nilashi, Jurgita Antucheviciene, Madjid Tavana, Romualdas Bausys, Othman Ibrahim
2017 Complexity  
Based on the results of this review, we found that there are many challenging issues related to the different application area of fuzzy-rough set theory which can motivate future research studies.  ...  Accordingly, the systematic and meta-analysis approach, which is called "PRISMA," has been proposed and the selected articles were classified based on the author and year of publication, author nationalities  ...  [19] suggested a new kind of classifier for imbalanced multi-instance data based on fuzzy-rough set theory.  ... 
doi:10.1155/2017/1608147 fatcat:o6khgyofg5g55hwgdj2y6angii

A CRACK DETECTION SYSTEM FOR STRUCTURAL HEALTH MONITORING AIDED BY A CONVOLUTIONAL NEURAL NETWORK AND MAPREDUCE FRAMEWORK

Darya Filatova, Charles El-Nouty
2020 International Journal for Computational Civil and Structural Engineering  
In this study, we discuss an automated crack type classification pipeline based on CNN deep learning algorithm and MapReduce framework.  ...  The work is devoted to the development of a computer-vision-based crack detection system capable to process big data related to pathology recognition.  ...  Big data severely impact training processes of CNN. The finalization of the CNN-based predictive model with desired accuracy suitable for the application has very high computational cost.  ... 
doi:10.22337/2587-9618-2020-16-4-38-49 fatcat:3suti2cibzey7doihfn6ya2sue

Uncertainty in big data analytics: survey, opportunities, and challenges

Reihaneh H. Hariri, Erik M. Fredericks, Kate M. Bowers
2019 Journal of Big Data  
Hariri for her assistance with this paper. This research has been supported in part by NSF Grant CNS-1657061, the Michigan Space Grant Consortium, the Comcast Innovation Fund, and Oakland University.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of Oakland University or other research sponsors.  ...  In another study, fuzzy logic-based matching algorithms and MapReduce were used to perform big data analytics for clinical decision support.  ... 
doi:10.1186/s40537-019-0206-3 fatcat:kp5vl4suwvcu5c6iukwa2o33le

Applied machine learning and management of volatility, uncertainty, complexity & ambiguity (V.U.C.A)

Srikanta Patnaik
2020 Journal of Intelligent & Fuzzy Systems  
Wentie WU and Shengchao XU in their paper entitled, "Application of MapReduce Parallel Association Mining on IDS in Cloud Computing Environment", designed an association rule mining algorithm based on  ...  privacy-preserving scheme for vehicular networks based on fuzzy system.  ...  Qinge Wang and Huihua Chen in their paper entitled, "Optimization of Parallel Random forest Algorithm based on Distance Weight", proposed an optimization method based on distance weights for parallel random  ... 
doi:10.3233/jifs-179915 fatcat:njwjogoperg2jggdkyheiibbhi

Mining Chinese social media UGC: a big-data framework for analyzing Douban movie reviews

Jie Yang, Brian Yecies
2016 Journal of Big Data  
In addition, an improved Apriori algorithm based on MapReduce is proposed for content-mining functions.  ...  A novel Big Data processing framework is proposed to investigate a niche subset of user-generated popular culture content on Douban, a well-known Chinese-language online social network.  ...  Acknowledgements This article draws on research currently being conducted in association with an Australian Research Council Discovery project, Willing Collaborators: Negotiating Change in East Asian media  ... 
doi:10.1186/s40537-015-0037-9 fatcat:nkfzzs5k3rhxrpsgt5nnci5lpu

Review on Big Data and Mining Algorithm

Shoban Babu Sriramoju
2017 International Journal for Research in Applied Science and Engineering Technology  
In this paper we will examine future patterns of information digging that are utilized for examination and expectation of big data.  ...  We will talk about difficulties while performing mining on big information. Stream information is likewise alluding as constant information.  ...  Fuzzy-CMeans is a partition based clustering algorithm based on Kmeans to divide big data into several clusters [1] D.  ... 
doi:10.22214/ijraset.2017.11181 fatcat:nh7fanjjnrbuhc6lyaeoupfnru

Big Data and Knowledge Extraction for Cyber-Physical Systems

Xiuzhen Cheng, Yunchuan Sun, Antonio Jara, Houbing Song, Yingjie Tian
2015 International Journal of Distributed Sensor Networks  
Acknowledgments We would like to thank all authors for their valuable contributions to this special issue.  ...  It is also an honor for us to serve as the Guest Editors of this issue. Xiuzhen Cheng Yunchuan Sun Antonio Jara Houbing Song Yingjie Tian  ...  Jiang et al. presents a methodology to predict AHE for ICU patients based on big data time series.  ... 
doi:10.1155/2015/231527 fatcat:qsobptejnfbrteagyzr2xkebea

Real Time Intrusion Detection System for Big Data

Reghunath K
2017 International Journal of Peer to Peer Networks  
The advantage of the system is that it utilize anomaly detection, evaluates data and issue alert message or reports based on abnormal behaviour.  ...  The objective of the proposed system is to integrate the high volume of data along with the important considerations like monitoring a wide array of heterogeneous security.  ...  ACKNOWLEDGEMENTS First of all I express my heartfelt thanks to almighty god for his blessings to complete this paper successfully.  ... 
doi:10.5121/ijp2p.2017.8101 fatcat:4ymhvmhqkjcr7b2koudszsz5t4
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