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Traffic incident detection (TID) is an important part of any modern traffic control because it offers an opportunity to maximise road system performance. For the complexity and the nonlinear characteristics of traffic incidents, this paper proposes a novel fuzzy deep learning based TID method which considers the spatial and temporal correlations of traffic flow inherently. Parameters of the deep network...
In the cities, incidents causes many problems such as congestion, pollution, disrupt the normal flow of traffic and cause motorist delay. This paper introduces a control system developed using the multi agents system (MAS) and Support Vector Machine (SVM) algorithm to detect incidents in signalized urban arterial. The proposed system based on SVM offers a higher correct detection rate, lower false...
Traffic signal operations play an important role in the effective functioning of the urban area. However, due to the increasing number of vehicles and the high dynamic of the traffic network, conventional traffic signal timing methods does not result in an efficient control. One alternative is to let traffic signal controllers learn how to adjust the lights based on the traffic situation. In this...
This paper presents an intelligent multi-agent system based on the law of gravity and fuzzy logic for the optimal management of the intra-MicroGrids energy. The aim is to overcome the weakness of the MicroGrid (MG) regarding the intermittent generation of its renewable source and its dependency to the main grid as the only reliable part in the power exchange. Taking into account that the power loss...
Congestion, accidents, pollution, and many other problems resulting from urban traffic are present every day in most cities around the world. The growing number of traffic lights in intersections needs efficient control, and hence, automatic systems are essential nowadays for optimally tackling this task. Agent based technologies and reinforcements learning are largely used for modelling and controlling...
Various crucial business processes within the enterprise are based on information technology (IT) services and, as consequence, negative IT incidents can interrupt the daily enterprise' activities and cause negative effects such as: a loss of costumers' confidence, loss of productivity and direct financial loss. For that, enterprises look for implementing IT incident management system in order to...
This paper proposes a design and implementation of an autonomous multi agent system (MAS) for optimal micro grid (MG) scheduling energy control based on fuzzy logic decision. The complexity of climate makes renewable energy source included in a micro grid, difficult to be scheduled with traditional energy sources in centralized system. Furthermore the scheduling depend on energy sources constraints...
In this paper, artificial neural network sliding mode (ANNSM) controller is designed for a variable speed wind turbine in order to optimize the energy captured from the wind. Sliding mode control (SMC) approach can be used for a variable speed wind turbine. However, in the presence of large uncertainties, the SMC produces chattering phenomenon due to the higher needed switching gain. In order to reduce...
In this paper a neural network sliding mode controller (NNSM) is designed for a class of nonlinear uncertain systems. Sliding mode control approach (SMC) can be used for nonlinear systems with small uncertainties. However, for nonlinear systems with large uncertainties the SMC produce chattering phenomenon due to the higher switching gain. In order to reduce this gain, neural network with one hidden...
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