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Probabilistic Relational Models [chapter]

2014 Encyclopedia of Social Network Analysis and Mining  
Probabilistic relational models (PRMs) [13, 18] extend Bayesian networks with the concepts of objects, their properties, and relations between them.  ...  They combine a frame-based logical representation with probabilistic semantics based on directed graphical models (Bayesian networks).  ...  Probabilistic relational models (PRMs) [13, 18] extend Bayesian networks with the concepts of objects, their properties, and relations between them.  ... 
doi:10.1007/978-1-4614-6170-8_100531 fatcat:stiptgdqnjcnhbqecb2uzwhgqu

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

Martin Dinov, Robert Leech
2017 Frontiers in Human Neuroscience  
neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.  ...  AUTHOR CONTRIBUTIONS MD and RL both designed and contributed to the research, MD wrote code and analyzed data, MD and RL both wrote the paper.  ...  To simplify analysis and comparison between models, we correlated all templates between models and sorted the maps according to their correlations.  ... 
doi:10.3389/fnhum.2017.00534 pmid:29163110 pmcid:PMC5671986 fatcat:kh6tpqskwbhxpale5cl5xxo4vy

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

C Zhang, T X Qin, B Jiang, C Huang
2018 IOP Conference Series: Earth and Environment  
The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.  ...  This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network.  ...  (Grant No. 512015Y-4002) and the Youth Talent Fund of Beijing (Grant No. 512016Z-4983).  ... 
doi:10.1088/1755-1315/113/1/012083 fatcat:2qa7hnnsvvey5inb754tj3dspi

Steady-State Analysis of Genetic Regulatory Networks Modelled by Probabilistic Boolean Networks

Ilya Shmulevich, Ilya Gluhovsky, Ronaldo F. Hashimoto, Edward R. Dougherty, Wei Zhang
2003 Comparative and Functional Genomics  
Probabilistic Boolean networks (PBNs) have recently been introduced as a promising class of models of genetic regulatory networks.  ...  Using a recently introduced method based on the theory of two-state Markov chains, we illustrate the approach on a sub-network designed from human glioma gene expression data and determine the joint steadystate  ...  Concluding remarks We have focused on the important problem of steady-state analysis of probabilistic Boolean networks.  ... 
doi:10.1002/cfg.342 pmid:18629023 pmcid:PMC2447305 fatcat:73y5zhcw5zgalap6q6bzaxwt5a

Statistical Modeling and Probabilistic Analysis of Cellular Networks With Determinantal Point Processes

Yingzhe Li, Francois Baccelli, Harpreet S. Dhillon, Jeffrey G. Andrews
2015 IEEE Transactions on Communications  
and can be numerically evaluated for cellular networks with DPP configured BSs.  ...  In addition, the modeling accuracy of DPPs is investigated by fitting three DPP models to real BS location data sets from two major U.S. cities.  ...  The Laplace functional provides a strong tool to analyze the shot noise field of a DPP. In particular, it facilitates the analysis of interference and coverage probability in cellular networks. 3.  ... 
doi:10.1109/tcomm.2015.2456016 fatcat:ju2nu6ga2rfkfl7eg3kqk5qoku

Analysis of DNA Sequence Pattern Using Probabilistic Neural Network Model

Xiaoming Wu, Fang Lu, Bo Wang, Jingzhi Cheng
2005 Journal of research and practice in information technology  
A probabilistic neural network model was introduced to represent variable length DNA sequence patterns.  ...  The sensitivity of this method was higher than two compared methods, and regulatory sequences of genes were discovered from real DNA sequences of gene clusters.  ...  In this article, a probabilistic neural network (PNN) model was introduced to extract fixed length as well as variable length motifs from some given DNA sequences.  ... 
dblp:journals/acj/WuLWC05 fatcat:y3m6ulh4mfeyzh3zsfhpvj5xfm

A Network of Dynamic Probabilistic Models for Human Interaction Analysis

Heung-Il Suk, A. K. Jain, Seong-Whan Lee
2011 IEEE transactions on circuits and systems for video technology (Print)  
Index Terms-Dynamic Bayesian network, human interaction analysis, network of dynamic probabilistic models, subinteractions, video surveillance.  ...  a robust model for the analysis of human interactions.  ...  That is, we can build a network of mixture models by linking standard HMMs, variants of HMMs, and other types of dynamic probabilistic models for different sub-interactions.  ... 
doi:10.1109/tcsvt.2011.2133570 fatcat:bqnkcmfsmfeg3jh3z32fhs433e

A probabilistic graphical model for brand reputation assessment in social networks

Kunpeng Zhang, Doug Downey, Zhengzhang Chen, Yusheng Xie, Yu Cheng, Ankit Agrawal, Wei-keng Liao, Alok Choudhary
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
In this paper, we propose a probabilistic graphical model to collectively measure reputations of entities in social networks.  ...  By collecting and analyzing large amount of user activities on Facebook, our model can effectively and efficiently rank entities, such as presidential candidates, professional sport teams, musician bands  ...  , DE-SC0005309, DESC0005340, and DESC0007456; AFOSR award FA9550-12-1-0458.  ... 
doi:10.1145/2492517.2492556 dblp:conf/asunam/ZhangDCXCALC13 fatcat:3fccuczrmnah3pabfpzlkoiiaq

Comparative Performance of Foreign Affiliates of Multinational Enterprises and Domestic Firms in the Indian Non-Electrical Machinery Industry: Applications of Linear Discriminant Analysis Versus Probabilistic Models

Pradeep Kumar Keshari
2010 Social Science Research Network  
The probabilistic models (notable the logit model) are considered as the better substitutes of discriminant analysis.  ...  Comparing the results of univariate analysis and LDA against the results of probabilistic models, we find that: a) GPM and RDI differ significantly between FAs and DFs in univariate analysis, while both  ...  networks for exports.  ... 
doi:10.2139/ssrn.1639371 fatcat:d6dw3k7verghden4eifmfcb77y

Probabilistic Modeling of Crack Networks in Thermal Fatigue

Nicolas Malésys, Ludovic Vincent, François Hild
2008 Volume 3: Design and Analysis   unpublished
The random aspect of initiation led to propose a probabilistic model for the formation and propagation of crack networks in thermal fatigue.  ...  Initiation, propagation and coalescence in a crack network The following model aims at bridging three scales [2] .  ...  Perspectives The probabilistic model was described in the simple case of the initiation of cracks on a surface along two perpendicular directions.  ... 
doi:10.1115/pvp2008-61081 fatcat:t7hqwptlx5b75lnprmzrdlqs2m

Modeling and Simulation of Vote Length Analysis for Probabilistic Voting-based Filtering in Wireless Sensor Networks: Against False report and vote injection attacks

Su Man Nam, Tae Ho Cho
unpublished
These attacks drain their limited energy resources of forwarding nodes and drops important data.  ...  In large-scale wireless sensor networks, sensors are vulnerable to false report and false vote injection attacks since they are deployed in hostile environments.  ...  The remainder of the paper is organized as follows: Section 2 explains a security protocol, DEVS, and motivation. Section 3 shows a simulation model and attacks analysis.  ... 
doi:10.29007/xs1j fatcat:ut5aggnwkzhrlhezkbpkbhvbhq

The development of a short-term liquidity decision model via protocol analysis and probabilistic neural networks

Sheng-Tun Li, Li-Yen Shue, W. Shiue
Proceedings of the 33rd Annual Hawaii International Conference on System Sciences  
The output analysis component applies Probability Neural Network to build a decision model based on the predictions of the initial model.  ...  The scheme consists of process tracing, output analysis, and model review component.  ...  In Section 2, we present some background knowledge on Concurrent Protocol Analysis of the process tracing approach, and Probabilistic Neural Network of the output analysis approach, both are used in this  ... 
doi:10.1109/hicss.2000.926652 dblp:conf/hicss/LiSS00 fatcat:6khqbfqpxrahpes7leekkkg6si

An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs

B. R. Vinay Kumar, Navin Kashyap, D. Yogeshwaran
2021 2021 19th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt)   unpublished
We consider the problem of energy-efficient broadcasting on dense ad-hoc networks. Ad-hoc networks are generally modeled using random geometric graphs (RGGs).  ...  Every other node in the network follows a probabilistic forwarding protocol; upon reception of a previously unreceived packet, the node forwards it with probability p and does nothing with probability  ...  Packet collisions and interference effects are neglected. Random network models have found wide acceptance in modeling wireless ad-hoc networks.  ... 
doi:10.23919/wiopt52861.2021.9589218 fatcat:edbr22ok2vdwjencoch5fkpyb4

Author Index

2020 2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)  
Response and Long-term Restoration CT Gaunt 114 Probabilistic Analysis of Power Network Susceptibility to GICs 140 Practical Probabilistic Design Procedures for Medium Voltage Distribution Systems  ...  Conditions and Fatigue Accu- mulation Douglas Logan 44 A Survey of Industry Practices in Probabilistic Assessment and Composite System Reliability Analysis Stefan Lotz 114 Probabilistic Analysis  ... 
doi:10.1109/pmaps47429.2020.9183572 fatcat:giorqvjqzvhcrlqqmah3jxttfq

Probabilistic Defect Analysis Model for Quantum dot Cellular Automata Design at Analytical Phase

Arijit Dey, Kunal Das, Debashis De, Mallika De
2012 International Journal of Computer Applications  
We proposed a Bayesian network based Probabilistic Defect Analysis Model (PDAM) to analyze the defect at analytical phase of QCA design.  ...  Proposed model is applied over QCA wire, three input Majority voter, Five Input Majority voter and the result is compared with QCADesigner to justify the importance of PDAM approach over exhaustive simulation  ...  The Probabilistic Defect Analysis Model with Bayesian Network is reported.  ... 
doi:10.5120/8768-2693 fatcat:zo6laeldz5eclmd4z25tlj5p5q
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