scholarly journals Investigating rare events by transition interface sampling

2004 ◽  
Vol 340 (1-3) ◽  
pp. 395-401 ◽  
Author(s):  
Daniele Moroni ◽  
Titus S. van Erp ◽  
Peter G. Bolhuis
Keyword(s):  
Rare Events ◽  
Transition Interface

Framework for rare event detection using Artificial Neural Network based context free grammar

2020 ◽  
Vol 39 (6) ◽  
pp. 8463-8475
Author(s):  
Palanivel Srinivasan ◽  
Manivannan Doraipandian
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Event Detection ◽  
Performance Metrics ◽  
Rare Events ◽  
Rare Event ◽  
Video Stream ◽  
Context Free Grammar ◽  
Artificial Neural ◽  
Context Free

Rare event detections are performed using spatial domain and frequency domain-based procedures. Omnipresent surveillance camera footages are increasing exponentially due course the time. Monitoring all the events manually is an insignificant and more time-consuming process. Therefore, an automated rare event detection contrivance is required to make this process manageable. In this work, a Context-Free Grammar (CFG) is developed for detecting rare events from a video stream and Artificial Neural Network (ANN) is used to train CFG. A set of dedicated algorithms are used to perform frame split process, edge detection, background subtraction and convert the processed data into CFG. The developed CFG is converted into nodes and edges to form a graph. The graph is given to the input layer of an ANN to classify normal and rare event classes. Graph derived from CFG using input video stream is used to train ANN Further the performance of developed Artificial Neural Network Based Context-Free Grammar – Rare Event Detection (ACFG-RED) is compared with other existing techniques and performance metrics such as accuracy, precision, sensitivity, recall, average processing time and average processing power are used for performance estimation and analyzed. Better performance metrics values have been observed for the ANN-CFG model compared with other techniques. The developed model will provide a better solution in detecting rare events using video streams.

Rare event simulation

2017 ◽  
Author(s):  
Michael P. Allen ◽  
Dominic J. Tildesley
Keyword(s):  
Rare Event ◽  
Path Sampling ◽  
Rapid Progress ◽  
Computationally Efficient ◽  
Transition Path ◽  
Transition Path Sampling ◽  
Event Simulation ◽  
Reaction Coordinates ◽  
Simulation Techniques ◽  
Transition Interface

The development of techniques to simulate infrequent events has been an area of rapid progress in recent years. In this chapter, we shall discuss some of the simulation techniques developed to study the dynamics of rare events. A basic summary of the statistical mechanics of barrier crossing is followed by a discussion of approaches based on the identification of reaction coordinates, and those which seek to avoid prior assumptions about the transition path. The demanding technique of transition path sampling is introduced and forward flux sampling and transition interface sampling are considered as rigorous but computationally efficient approaches.

scholarly journals Wepy: A Flexible Software Framework for Simulating Rare Events with Weighted Ensemble Resampling

ACS Omega ◽  
2020 ◽  
Vol 5 (49) ◽  
pp. 31608-31623
Author(s):  
Samuel D. Lotz ◽  
Alex Dickson
Keyword(s):  
Rare Events ◽  
Software Framework
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