[PDF] Top 20 Novel applications of Machine Learning to Network Traffic Analysis and Prediction
Has 10000 "Novel applications of Machine Learning to Network Traffic Analysis and Prediction" found on our website. Below are the top 20 most common "Novel applications of Machine Learning to Network Traffic Analysis and Prediction".
Novel applications of Machine Learning to Network Traffic Analysis and Prediction
... A Network Traffic Classifier (NTC) is an important part of current network monitoring systems, being its task to infer the network service that is currently used by a ... See full document
183
An unsupervised clustering methodology by means of an improved dbscan algorithm for operational conditions classification in a structure
... number of newly engineering ...part of SHM for signal processing and anomalies or dam- age detection, assuring structural ...day and more researchers and engineers feel the interest ... See full document
117
Machine learning and statistical techniques : an application to the prediction of insolvency in Spanish non-life insurance companies
... characteristics of the data and variables that will be used to develop our ...sample of Spanish firms used by Sanchís et al. (2003) in the application of the Discriminant Analysis ... See full document
45
Prediction of AR marker's position: A case of study using regression analysis with Machine Learning method
... use of video-projectors, optical ele- ments, holograms, radio frequency tags, and other tracking technologies to display graphical information directly onto physical objects without requiring the ... See full document
144
Prediction of frost location using machine learning and wireless sensor networks
... by learning Markov Network structures from the environmental data corroborating with the opinion of an ...The analysis of the Markov blanket of particular sensors helps to ... See full document
2
Contributions to Bayesian network learning with applications to neuroscience
... Supervised learning tasks are by far the most commonly studied problems in machine ...Supervised learning deals with the problem of learning classifiers when the true class label for ... See full document
346
Visualization and machine learning techniques to support web traffic analysis
... impossible to get knowledge looking directly at raw data, so it must be presented in a way that is easy to understand and ...options to visualize data; specifically, for web analytics, ... See full document
110
Utilising social network analysis to identify the estructural features of teachers´knowledge and resource sharing networks within schools
... social network analysis (SNA) might be used to identify the structural features present in the resource- and knowledge-sharing networks that develop between teachers when they are working ... See full document
27
TítuloNet net Auto machine learning (AutoML) prediction of complex ecosystems
... Table and Logistic Regression provided accuracies lower than the LDA ...racies and AUROC were improved, with values over ...MLP and AdaBoostM1 MLP) could produce slightly better ...H and Deep ... See full document
9
Exploiting web technologies to build autonomic wireless sensor networks
... frequency of use and execution time for every application method; (ii) the usage of memory while the application runs; and (iii) network data transmitted and received by the ... See full document
16
Assessing the suitability of student interactions from Moodle data logs as predictors of cross-curricular competencies
... This study explores the applicability of learning analytics for prediction of development of two cross- curricular competencies - teamwork and commitment - based on the analysis of Moodl[r] ... See full document
9
Current trends in designing metaheuristic algorithms: applications to machine learning
... design of metaheuristic algorithms was focused on any ...design of metaheuristic algorithms (see Wolpert and Macready ...class of problems is offset by performan- ce over another class, ... See full document
234
TítuloNet net Auto machine learning (AutoML) prediction of complex ecosystems
... Amphiprion akindynos Amphiprion frenatus Amphiprion melanopus Entacmaea quadricolor Amphiprion sebae Amphiprion rubrocinctus Amphiprion polymnus Heteractis aurora Amphiprion akindynos He[r] ... See full document
14151
An Adaptive Algorithm to Optimize the Dynamics of IEEE 802.15.4 Networks
... unit of time called the backoff period (time required to transmit 20 symbols: 320 μs when operating in the ...lost and network performance ...number of backoff periods before trying ... See full document
13
Automatic prediction of facial trait judgments: Appearance vs structural models
... study of what the author called ‘‘Physical Personality of the ...aspects of personal appearance that produce an initial impression of personality in an ...used to match human ... See full document
12
The sensitivity of machine learning techniques to variations in sample size : a comparative analysis
... easy to interpret. The outcome of these systems is a set of rules or a classification tree, which can be understood even by people with no specific Artificial Intelligence (AI) ...economic ... See full document
25
Regularization for sparsity in statistical analysis and machine learning
... intend to reach more complex nonlinear relations, which will presumably help to deal with the complex within-neuron ...known to the statistics community, generalize the linear regression setting ... See full document
176
A multi agent system for managing adverse weather situations on the road network
... daily traffic manage- ment but the decisions on the traffic actions to exe- cute are performed by a single agent, usually a manag- er agent which stores a general overview of the ... See full document
11
Application of machine learning techniques to optical communication systems and networks
... A machine learning approach was proposed to solve this binary classification problem the 14-node Deutsch Telekom (DT) ...proposed to replace the CBR trying to classify lightpaths inside ... See full document
59
TítuloRutting prediction of a granular material for base layers of low traffic roads
... proved to be remarkable even when this effect is taken into account, and it is well worth having to manipulate a few more ...contribution to the fitting curves, it becomes apparent that ... See full document
21
Related subjects