Type-2 fuzzy multiagent traffic signal control

Sabetghadam, Bahareh; Shabaninia, Faridoon; Vaziri, M.; Vadhava, S.

doi:10.1109/iri.2012.6303051

Cited by 22 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…us, the Type-2 Fuzzy drives interesting works in medical, and several other fields, such as in [23][24][25][26][27][28][29][30][31][32][33].…”

Section: Related Workmentioning

confidence: 99%

“…It is also investigated [29] for designing and implementing an intelligent method for information extraction when information is abundant, vague, or imprecise. Furthermore, the multiagent approach is investigated for solving problems in traffic fields, [30] and for decision making of maintenance [31]in real time, and for effective coordination scheme [32] based on Type-2 Fuzzy decision making. e combination of the two aspects, the Fuzzy logic and multiagent approach, provides promising solutions which lead to extension the standard type-2 Fuzzy logic algorithm to a new distributed one based on the multiagent architecture.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics

Benchara

Youssfi

2020

Advances in Fuzzy Systems

View full text Add to dashboard Cite

The paper aims to propose a distributed method for machine learning models and its application for medical data analysis. The great challenge in the medicine field is to provide a scalable image processing model, which integrates the computing processing requirements and computing-aided medical decision making. The proposed Fuzzy logic method is based on a distributed approach of type-2 Fuzzy logic algorithm and merges the HPC (High Performance Computing) and cognitive aspect on one model. Accordingly, the method is assigned to be implemented on big data analysis and data science prediction models for healthcare applications. The paper focuses on the proposed distributed Type-2 Fuzzy Logic (DT2FL) method and its application for MRI data analysis under a massively parallel and distributed virtual mobile agent architecture. Indeed, the paper presents some experimental results which highlight the accuracy and efficiency of the proposed method.

show abstract

“…us, the Type-2 Fuzzy drives interesting works in medical, and several other fields, such as in [23][24][25][26][27][28][29][30][31][32][33].…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics

Benchara

Youssfi

2020

Advances in Fuzzy Systems

View full text Add to dashboard Cite

show abstract

“…Balaji and Srinivasan (2011) and Sabetghadam, Shabaninia, Vaziri, and Vadhava (2012) used type-2 fuzzy logic in controlling traffic signals. Sabetghadam et al (2012) mentioned that a large training data set needed for computational intelligence based method like NN, with all uncertainties they may contain, make it difficult to obtain a proper controller. In their research they developed a multiagent distributed architecture signal control system based on type-2 fuzzy sets.…”

Section: Intelligent Traffic Signal Controllersmentioning

confidence: 99%

Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network

Araghi

Khosravi

Creighton

2015

Expert Systems with Applications

View full text Add to dashboard Cite

“…Researchers in [27] and [28] used fuzzy type-2 for controlling traffic signal lights. They mentioned that the nature of the traffic signal controlling led to fuzzy type-2 become more appropriate to be employed in designing such controllers.…”

Section: Fuzzy Logic System For Traffic Signal Timingmentioning

confidence: 99%

“…They mentioned that the nature of the traffic signal controlling led to fuzzy type-2 become more appropriate to be employed in designing such controllers. In [28], it was mentioned that although computational intelligence-based method such as neural network have been used for designing signal controller, a large training data set with all uncertainties they may contain make it difficult to obtain a proper controller. They developed a distributed architecture signal timing control system based on type-2 fuzzy sets.…”

Section: Fuzzy Logic System For Traffic Signal Timingmentioning

confidence: 99%

Optimal fuzzy traffic signal controller for an isolated intersection

Araghi

Khosravi

Creighton

et al. 2014

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

View full text Add to dashboard Cite

This paper aims at optimally adjusting a set of green times for traffic lights in a single intersection with the purpose of minimizing travel delay time and traffic congestion. Fuzzy logic system (FLS) is the method applied to develop the intelligent traffic timing controller. For this purpose, an intersection is considered and simulated as an intelligent agent that learns how to set green times in each cycle based on the traffic information. The FLS controller (FLC) uses genetic algorithm to tune its parameters during learning phase. Finally, The performance of the intelligent FLC is compared with the performance of a FLC with predefined parameters and three simple fixed-time controller. Simulation results indicate that intelligent FLC significantly reduces the total delay in the network compared to the fixed-time method and FLC with manual parameter setting.

show abstract

Type-2 fuzzy multiagent traffic signal control

Cited by 22 publications

References 3 publications

A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics

A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics

Intelligent cuckoo search optimized traffic signal controllers for multi-intersection network

Optimal fuzzy traffic signal controller for an isolated intersection

Contact Info

Product

Resources

About