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Detecting anomalies in spatiotemporal data using genetic algorithms with fuzzy community membership
2010
2010 10th International Conference on Intelligent Systems Design and Applications
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The work examines the performance of the genetic algorithm against simulated annealing using both types of fuzzy community membership functions. ...
Rather than use GA to decide community structure that simply maximizes modularity of a network, as is typical, we use two fuzzy community membership functions applied to natural temporal divisions in the ...
ACKNOWLEDGMENT The authors wish to thank Fisheries and Oceans Canada (DFO) for making available the data used in the case study. ...
doi:10.1109/isda.2010.5687285
dblp:conf/isda/WilsonHHDB10
fatcat:pfyuybfqnbgaxph3pbedocdl7a
Short-term traffic flow prediction considering spatio-temporal correlation: a hybrid model combing type-2 fuzzy c-means and artificial neural network
2019
IEEE Access
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Second, in order to improve classifying performance and reliability to anomalous data samples, a type-2 fuzzy c-means (FCM) is adopted to make fuzzification of the membership function. ...
Finally, traffic volume data collected from the highway is used to optimize the parameter in the prediction model combination. ...
[20] used genetic algorithm (GA) to optimize the membership function of adaptive fuzzy rules offline and online, which has a beneficial effect in traffic prediction of urban trunk roads. ...
doi:10.1109/access.2019.2931920
fatcat:uldisdmew5gqre2vdsu5szkqg4
Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs
2012
2012 IEEE Congress on Evolutionary Computation
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The approach systematically produces better results than the used basic genetic algorithm and better or similar results with other heuristic methods. ...
This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm. ...
CONCLUSIONS AND FUTURE WORK In this paper a cellular genetic algorithm with multiple communicating grids for optimizing the variable order for ROBDDs was presented. ...
doi:10.1109/cec.2012.6256590
dblp:conf/cec/RotaruB12
fatcat:4ly3nrktw5habc6lf5err7d5py
Spatial data mining and geographic knowledge discovery—An introduction
2009
Computers, Environment and Urban Systems
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data, as well as by demonstrating applications of genetic algorithms for optimization in the context of image classification and spatial interpolation. ...
The articles included in this special issue contribute to spatial data mining research by developing new techniques for point pattern analysis, prediction in space-time data, and analysis of moving object ...
Acknowledgment We would like to express our thanks to all the authors who submitted papers to the special issue and especially Jean-Claude Thill for his assistance in preparing this special issue. ...
doi:10.1016/j.compenvurbsys.2009.11.001
fatcat:f6uwefuupjfq3kdi7gkvmtgsji
Outlier Detection for Temporal Data: A Survey
2014
IEEE Transactions on Knowledge and Data Engineering
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In the statistics community, outlier detection for time series data has been studied for decades. ...
Recently, with advances in hardware and software technology, there has been a large body of work on temporal outlier detection from a computational perspective within the computer science community. ...
[129] propose a wavelet fuzzy classification approach to detect and track region outliers in meteorological data. ...
doi:10.1109/tkde.2013.184
fatcat:b6nableuvvgthlw3xxj6axabgi
A hybrid mobile call fraud detection model using optimized fuzzy C-means clustering and group method of data handling-based network
2018
Vietnam Journal of Computer Science
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Initially, a genetic algorithm-based optimized fuzzy c-means clustering is applied to the user's historical call records for constructing the calling profile. ...
A novel two-stage fraud detection system in mobile telecom networks has been presented in this paper that identifies the malicious calls among the normal ones in two stages. ...
, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. ...
doi:10.1007/s40595-018-0116-x
fatcat:xgpjbg5ikjconnhfk5zsiwepim
A Spatiotemporal Apriori Approach to Capture Dynamic Associations of Regional Traffic Congestion
2019
IEEE Access
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Case studies are carried out for the urban road network in Tianjin, China, based on empirical data. ...
To this end, this paper proposes a data-driven approach to mine the spatiotemporal associations of regional traffic congestion. ...
CLUSTERING ALGORITHM FOR TRAFFIC STATE RECOGNITION 1) INTEGRATED CLUSTERING ALGORITHM The FCM algorithm can be used to calculate the membership of each sample to all clusters. ...
doi:10.1109/access.2019.2962619
fatcat:c5ewciaf5ffhxiqh4uyhnrd4k4
Discrimination and Prediction of Traffic Congestion States of Urban Road Network Based on Spatio-temporal Correlation
2019
IEEE Access
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In this paper, firstly, we analyze and study the spatio-temporal correlation characteristics of traffic states based on the existing floating car data. ...
characteristics of local Moran's I, a mixed forest prediction method considering the spatio-temporal correlation characteristics of urban road traffic state is constructed by improving the existing random forest algorithm ...
The traffic congestion state will be evaluated by using the fuzzy C-means algorithm. ...
doi:10.1109/access.2019.2959125
fatcat:jxjganhycvcgnjxmdrtqljk3mq
Outlier Detection Strategies for WSNs: A Survey
2021
Journal of King Saud University: Computer and Information Sciences
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Thus, detecting outliers in WSNs using data-driven approaches becomes a novel technique among the Machine Learning (ML) communities. ...
In this scenario, sensor readings that have differed considerably from healthy behaviors will be considered abnormal data or anomalies/outliers. ...
The primary purpose of using fuzzy logic is assigning membership degree to the models that have difficulty in meaning and hard to express (Sangwook et al., 2015; Luo and Sai, 2018) . ...
doi:10.1016/j.jksuci.2021.02.012
fatcat:rpgswasszzbgdbkziskhqrqjam
Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
2019
IEEE Access
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anomaly detection, Internet traffic classification, and quality of service optimization. ...
In addition, unsupervised learning can unconstrain us from the need for labeled data and manual handcrafted feature engineering, thereby facilitating flexible, general, and automated methods of machine ...
One novel way to detect anomaly is proposed in [85] , this approach preprocesses the data using Genetic Algorithm (GA) combined with hierarchical clustering approach called Balanced Iterative Reducing ...
doi:10.1109/access.2019.2916648
fatcat:xutxh3neynh4bgcsmugxsclkna
Change detection of pulmonary embolism using isomeric cluster and computer vision
2022
IAES International Journal of Artificial Intelligence (IJ-AI)
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We present a new feature descriptor called pulmonary embolism detection using isomeric cluster (PEDIC), uses the concept of isomerism. ...
We also proposed inter-PEDIC and intra-PEDIC to identify motion changes in X-ray sequences, which allowed them to extract spatiotemporal characteristics.</p> ...
In addition, the current frame and fuzzy similarity between background models have been assessed using interval similarity and membership values, as well as membership values. P. Rambabu, et al. ...
doi:10.11591/ijai.v11.i2.pp787-798
fatcat:vdbveabwqncixc26mskyhwhmsi
2020 Index IEEE Transactions on Industrial Informatics Vol. 16
2020
IEEE Transactions on Industrial Informatics
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Photovoltaic Arrays Using GBSSL Method and Proposing a Fault Correction System; TII Aug. 2020 5300-5308 ...
Jiang, C., see Qin, Y., TII Jan. 2020 238-247 Jiang, H., see Ruan, J., 1296-1309 Jiang, H., Ren, J., Lui, J.C.S., and Dustdar, S., Guest Editorial:Special Section on End-Edge-Cloud Orchestrated Algorithms ...
., +, TII Sept. 2020 6013-6022
Genetic algorithms
A Novel Approach to Reliable Sensor Selection and Target Tracking in Sen-
sor Networks. ...
doi:10.1109/tii.2021.3053362
fatcat:blfvdtsc3fdstnk6qoaazskd3i
A decision support framework for prediction of avian influenza
2020
Scientific Reports
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The evaluation of the system in detecting events resulted in average sensitivity and specificity of 69.70% and 85.50%, respectively. ...
Risk patterns were driven from pre-built components and combined in a knowledge base. Subsequently, questions were answered by direct queries on the knowledge base or through a built-in algorithm. ...
This research is supported in part by the University of Guelph's Food from Thought initiative, thanks to funding from the Canada First Research Excellence Fund. ...
doi:10.1038/s41598-020-75889-7
pmid:33149144
fatcat:oyzbq6tffnesbfgzrd3nl7xdne
Visual Approaches for Exploratory Data Analysis: A Survey of the Visual Assessment of Clustering Tendency (VAT) Family of Algorithms
2020
IEEE Systems Man and Cybernetics Magazine
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[143] and Su and Havens [144] , [145] used various approaches, such as genetic algorithms and fuzzy modularity maximization for fuzzy community detection in social network graph data. ...
[141] were the first to use the VAT algorithm to detect communities in a graph. ...
doi:10.1109/msmc.2019.2961163
fatcat:jvqnvhjgjndyrn3cx6ehcigueu
A survey on health monitoring systems for health smart homes
2018
International Journal of Industrial Ergonomics
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In this way, elderly people can avoid, for as long as possible, any interaction with healthcare institutions (e.g. nursing homes and hospitals), which in turn reduces pressure on the health system. ...
We review HMS in smart environments from a general perspective and with a particular focus on systems for the elderly and dependent people. ...
The authors in [145] used fuzzy membership functions for movement detection and estimating daily living activity. ...
doi:10.1016/j.ergon.2018.02.002
fatcat:gwkfbryll5c4bntbu6qxm4cknq
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