Fault diagnosis on wireless sensor network using the neighborhood kernel density estimation
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3342-3
Abstract: Wireless sensor network (WSN) has become one of the most important technologies because of its reliable remote monitoring ability. As sensors are often deployed at remote and/or hazardous environments, it is important to be able… read more here.
Keywords: kernel density; density estimation; wireless sensor; sensor network ... See more keywords
Conditional density estimation using the local Gaussian correlation
Sign Up to like & getrecommendations! Published in 2018 at "Statistics and Computing"
DOI: 10.1007/s11222-017-9732-z
Abstract: Let $$\mathbf {X} = (X_1,\ldots ,X_p)$$X=(X1,…,Xp) be a stochastic vector having joint density function $$f_{\mathbf {X}}(\mathbf {x})$$fX(x) with partitions $$\mathbf {X}_1 = (X_1,\ldots ,X_k)$$X1=(X1,…,Xk) and $$\mathbf {X}_2 = (X_{k+1},\ldots ,X_p)$$X2=(Xk+1,…,Xp). A new method for estimating… read more here.
Keywords: estimation using; density estimation; density; mathbf ldots ... See more keywords
Fast feature selection for interval-valued data through kernel density estimation entropy
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-020-01131-5
Abstract: Kernel density estimation, which is a non-parametric method about estimating probability density distribution of random variables, has been used in feature selection. However, existing feature selection methods based on kernel density estimation seldom consider interval-valued… read more here.
Keywords: kernel density; feature selection; density estimation; interval valued ... See more keywords
Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python
Sign Up to like & getrecommendations! Published in 2018 at "Epidemics"
DOI: 10.1016/j.epidem.2018.05.009
Abstract: Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a… read more here.
Keywords: kernel density; density estimation; bayesian computation; approximate bayesian ... See more keywords
A novel density estimation based intrusion detection technique with Pearson's divergence for Wireless Sensor Networks.
Sign Up to like & getrecommendations! Published in 2020 at "ISA transactions"
DOI: 10.1016/j.isatra.2020.11.016
Abstract: We present a novel technique to detect an intrusive attack that occurs in the network due to the presence of a compromised node. These intrusive attacks last for a long time in the network due… read more here.
Keywords: technique; divergence; density estimation; pearson divergence ... See more keywords
Density estimation of a mixture distribution with unknown point-mass and normal error
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Statistical Planning and Inference"
DOI: 10.1016/j.jspi.2021.04.002
Abstract: Abstract We consider the model Y = X + ξ where Y is observable, ξ is a noise random variable with density f ξ , X has an unknown mixed density such that P (… read more here.
Keywords: density estimation; distribution unknown; density; estimation mixture ... See more keywords
Nonparametric Density Estimation of Hierarchical Probabilistic Graph Models for Assumption-Free Monitoring
Sign Up to like & getrecommendations! Published in 2017 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.6b04068
Abstract: Probabilistic graphical models, such as Bayesian networks, have recently gained attention in process monitoring and fault diagnosis. Their application, however, is limited to discrete or continuous Gaussian distributed variables, which results from the difficulty in… read more here.
Keywords: estimation; hierarchical probabilistic; density estimation; density ... See more keywords
Subsampling-extrapolation bandwidth selection in bivariate kernel density estimation
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2019.1597099
Abstract: ABSTRACT This paper focuses on bivariate kernel density estimation that bridges the gap between univariate and multivariate applications. We propose a subsampling-extrapolation bandwidth matrix selector that improves the reliability of the conventional cross-validation method. The… read more here.
Keywords: kernel density; density estimation; extrapolation; bandwidth matrix ... See more keywords
Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data
Sign Up to like & getrecommendations! Published in 2018 at "Transportation Planning and Technology"
DOI: 10.1080/03081060.2018.1488929
Abstract: ABSTRACT We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object… read more here.
Keywords: density estimation; geographic density; time; gps ... See more keywords
Traffic accident hotspot identification by integrating kernel density estimation and spatial autocorrelation analysis: a case study
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Crashworthiness"
DOI: 10.1080/13588265.2020.1826800
Abstract: The study presented an approach that integrated kernel density estimation (KDE) algorithm and spatial autocorrelation analysis, which helped to determine traffic accident (TA) hotspot locations and... read more here.
Keywords: kernel density; density estimation; spatial autocorrelation; accident hotspot ... See more keywords
Detection of hyperspectral anomalies using density estimation and collaborative representation
Sign Up to like & getrecommendations! Published in 2017 at "Remote Sensing Letters"
DOI: 10.1080/2150704x.2017.1346396
Abstract: ABSTRACT The collaborative-representation-based detector (CRD) will misjudge the anomaly pixel under test as a background pixel if there are a few anomalies similar to the pixel under test in the original background. In order to… read more here.
Keywords: density estimation; density; background; original background ... See more keywords