Virtual Machine Failure Prediction Method Based on AdaBoost-Hidden Markov Model

2019 ◽  
Author(s):  
Zhixin Li ◽  
Lei Liu ◽  
Degang Kong
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Virtual Machine ◽  
Hidden Markov ◽  
Failure Prediction ◽  
Prediction Method ◽  
Machine Failure

Detection of machine failure: Hidden Markov Model approach

2009 ◽  
Vol 57 (2) ◽  
pp. 608-619 ◽  
Author(s):  
Allen H. Tai ◽  
Wai-Ki Ching ◽  
L.Y. Chan
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Machine Failure ◽  
Model Approach

scholarly journals A Method for Driving Route Predictions Based on Hidden Markov Model

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Ning Ye ◽  
Zhong-qin Wang ◽  
Reza Malekian ◽  
Qiaomin Lin ◽  
Ru-chuan Wang
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Recommendation System ◽  
Hidden Markov ◽  
Prediction Method ◽  
Prediction Algorithm ◽  
Training Set ◽  
Rectangular Coordinate System ◽  
Route Prediction ◽  
Route Recommendation

We present a driving route prediction method that is based on Hidden Markov Model (HMM). This method can accurately predict a vehicle’s entire route as early in a trip’s lifetime as possible without inputting origins and destinations beforehand. Firstly, we propose the route recommendation system architecture, where route predictions play important role in the system. Secondly, we define a road network model, normalize each of driving routes in the rectangular coordinate system, and build the HMM to make preparation for route predictions using a method of training set extension based onK-means++ and the add-one (Laplace) smoothing technique. Thirdly, we present the route prediction algorithm. Finally, the experimental results of the effectiveness of the route predictions that is based on HMM are shown.

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