The Most General Intelligent Architectures of the Hybrid Neuro-Fuzzy Models
Issue:
Volume 2, Issue 1, June 2018
Pages:
1-6
Received:
25 November 2017
Accepted:
12 December 2017
Published:
5 January 2018
Abstract: Hybrid systems of the fuzzy logic and neural networks, are widely spread in real world problems with high effectiveness and versatility for different kinds of applications. The state description of unknown plant by using mathematical models, sometimes, is difficult to obtain. The fuzzy logic systems with their ability of tackling imprecise knowledges, and neural networks with their advantages of establishing a relationship between the inputs and the outputs of the system, are represented as qualified tools for systems of unknown plant. Furthermore, the hybrid systems which utilize the features of the fuzzy logic and Neural networks has been employed for better characteristics. Whilst, there are several different architectures of the neuro-fuzzy system proposed in literature, this article come out to highlight the common known architectures of how these techniques fuse together to build an enhanced system that can complement the lack of each method individually and improve the system performance over all.
Abstract: Hybrid systems of the fuzzy logic and neural networks, are widely spread in real world problems with high effectiveness and versatility for different kinds of applications. The state description of unknown plant by using mathematical models, sometimes, is difficult to obtain. The fuzzy logic systems with their ability of tackling imprecise knowledg...
Show More
Traffic Light Controller Module Based on Particle Swarm Optimization (PSO)
Emad Issa Abdul Kareem,
Ayat Ismail Mejbel
Issue:
Volume 2, Issue 1, June 2018
Pages:
7-15
Received:
22 February 2018
Accepted:
10 March 2018
Published:
12 April 2018
Abstract: A traffic light control module base on PSO algorithm has been presented to find the optimal set of adjacent streets that are the candidate to take the green period time providing the best vehicles flow. In our previous work a visual traffic light monitoring module has been presented. This module able to determine the traffic conditions (crowded, normal and empty). The proposed control module should be able to integrate with the previous monitoring module to develop a new complete intelligent traffic light system. Promising results have been obtained via applying the proposed traffic light controller module. The controller module shows its ability to select a set of streets. The green period time will be given to these selected streets to achieve the optimal vehicle flow through the traffic light’s intersections. The results show that the proposed control module improving the flow ratio about 85% to 96% with a different number of traffic lights.
Abstract: A traffic light control module base on PSO algorithm has been presented to find the optimal set of adjacent streets that are the candidate to take the green period time providing the best vehicles flow. In our previous work a visual traffic light monitoring module has been presented. This module able to determine the traffic conditions (crowded, no...
Show More
