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Full-Text Articles in Computer Engineering

Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich Dec 2015

Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich

Doctoral Dissertations

Neural networks have had many great successes in recent years, particularly with the advent of deep learning and many novel training techniques. One issue that has affected neural networks and prevented them from performing well in more realistic online environments is that of catastrophic forgetting. Catastrophic forgetting affects supervised learning systems when input samples are temporally correlated or are non-stationary. However, most real-world problems are non-stationary in nature, resulting in prolonged periods of time separating inputs drawn from different regions of the input space.

Reinforcement learning represents a worst-case scenario when it comes to precipitating catastrophic forgetting in neural networks. …


Comparison Of Clustering Techniques For Traffic Accident Detection, Nejdet Doğru, Abdülhami̇t Subaşi Jan 2015

Comparison Of Clustering Techniques For Traffic Accident Detection, Nejdet Doğru, Abdülhami̇t Subaşi

Turkish Journal of Electrical Engineering and Computer Sciences

Transportation infrastructure in intelligent transportation systems (ITSs) is complemented with information and communication technologies to achieve better passenger safety and reduced transportation time, fuel consumption, and vehicle wear and tear. This paper shows how data mining techniques are used in ITSs for accident detection and prevention on motorways. In traffic, vehicles show similar behavior to that of vehicles in closed neighborhoods. Vehicles that show different behaviors than neighbor vehicles in cases like accidents, inappropriate lane changes, and speeding can be considered as anomalies and detected. In this paper, a traffic accident is simulated and the effectiveness of different clustering techniques …