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RS-Forest: A Rapid Density Estimator for Streaming Anomaly Detection

Ke Wu, Kun Zhang, Wei Fan, Andrea Edwards, Philip S. Yu
2014 2014 IEEE International Conference on Data Mining  
Underlying the algorithm is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest.  ...  Anomaly detection in streaming data is of high interest in numerous application domains. In this paper, we propose a novel one-class semi-supervised algorithm to detect anomalies in streaming data.  ...  Acknowledgments This work is supported by a US Dept. of Army grant (W911NF-12-1-0066), an NIH grant (NIMHD RCMI 2G12MD007595) and a seed grant from the Louisiana Cancer Research Consortium (LCRC).  ... 
doi:10.1109/icdm.2014.45 pmid:25685112 pmcid:PMC4324726 dblp:conf/icdm/WuZFEY14 fatcat:hap3pgxrwvgm7j757jrhx2nmiq

A Collective Anomaly Detection Approach for Multidimensional Streams in Mobile Service Security

Yu Weng, Lei Liu
2019 IEEE Access  
In this paper, we consider the statistical features of the subsequence of streams, proposing a novel collective anomaly detection algorithm for multidimensional streams based on iForest in a cloud environment  ...  However, the collective anomaly detection for multidimensional streams exists lots of problems, owing to the differences between the anomaly detection in multidimensional time series and univariate time  ...  In 2014, the algorithm [24] proposed by Wu et al. is a fast and accurate density estimator implemented by multiple fully randomized space trees (RS-Trees), named RS-Forest.  ... 
doi:10.1109/access.2019.2909750 fatcat:jztgb3zuwvhyrgrnuru2n5ak5m

Outlier Detection Methods and the Challenges for their Implementation with Streaming Data

Ankita Karale
2020 Journal of Mobile Multimedia  
Outlier detection has been a generally examined issue and highly used in a varied range of spaces.  ...  This is why the study suggests that there is a need of a hybrid approach that combines classical algorithms and artificial intelligence algorithm to provide efficient solution for outlier detection of  ...  [36] proposed a calculation for the location of anomalies in massive information streams. A quick and precise density calculator called RS-Forest and machine learning are proposed. Bai et al.  ... 
doi:10.13052/jmm1550-4646.1635 fatcat:fnrb55vouba43lszw7mmsrfgp4

Outlier Detection using AI: A Survey [article]

Md Nazmul Kabir Sikder, Feras A. Batarseh
2021 arXiv   pre-print
For instance, an attack on a cyber-physical system such as a microgrid may initiate voltage or frequency instability, thereby damaging a smart inverter which involves very expensive repairing.  ...  Broad range of OD methods are categorized into six major categories: Statistical-based, Distance-based, Density-based, Clustering-based, Learning-based, and Ensemble methods.  ...  scalability for big data.Other Density-Based Algorithms: Tang and He (2017) proposed a method to estimate density using kernel density estimation for measuring local anomalies; a scoring process is introduced  ... 
arXiv:2112.00588v1 fatcat:yonfnhohpnbxxgiwrxon74mcny

Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications

Riccardo Dainelli, Piero Toscano, Salvatore Filippo Di Gennaro, Alessandro Matese
2021 Forests  
Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community.  ...  pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible and open-source tools that can foster researcher  ...  Aboveground biomass/volume estimation: Biomass estimation is a key issue in UAV-RS forest monitoring.  ... 
doi:10.3390/f12040397 fatcat:6mtlejuku5c3xbx2eq7inpdjse

Joints in Random Forests [article]

Alvaro H. C. Correia, Robert Peharz, Cassio de Campos
2020 arXiv   pre-print
Due to their discriminative nature, however, they lack principled methods to process inputs with missing features or to detect outliers, which requires pairing them with imputation techniques or a separate  ...  Under certain assumptions, frequently made for Bayes consistency results, we show that consistency in GeDTs and GeFs extend to any pattern of missing input features, if missing at random.  ...  Acknowledgments and Disclosure of Funding The authors thank the reviewers for their useful insights and suggestions.  ... 
arXiv:2006.14937v3 fatcat:eufbjtjym5ei3axwscowehxe6u

Flood vulnerability analysis in coastal zones: a comparative analysis across five Asia-Pacific countries

Dushmanta Dutta, Wendy Wright, Philip Rayment
2012 APN Science Bulletin  
Key issues of concern for flood impacts for coastal areas in Australia, Japan, Sri Lanka, Thailand and Viet Nam are compared.  ...  The paper presents a systematic approach in which relevant stakeholders in five Asia-Pacific countries were actively engaged in identifying and prioritizing flood impact issues.  ...  Acknowledgements The project received additional funding from the UK Biochar Research Centre at the University of Edinburgh and a travel award from Carbon Captured Limited.  ... 
doi:10.30852/sb.2012.6 fatcat:tor3kejgdrgf7cuho77bpmy2ga