Traffic flow data forecasting based on interval type-2 fuzzy sets theory

Li, Runmei; Jiang, Chaoyang; Zhu, Fenghua; Chen, Xiaolong

doi:10.1109/jas.2016.7451101

Cited by 48 publications

(3 citation statements)

References 14 publications

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“…The necessary in transportation management was information about traffic flow in real-time. In traffic flow forecast, Big Data analytics in ITS would significantly advantage [103]- [105]. Fig.…”

Section: A Application Of Big Data In Itsmentioning

confidence: 99%

Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems

Nguyen

Bui³

2022

JOIV : Int. J. Inform. Visualization

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Big Data technology is emerging as a mass technology that can be applied to many industries in life. Decisions in a wide range of fields may benefit greatly from the information provided by Big Data and Analytics research. One of the areas that have benefited the most from this technology is transportation, which is known as an important field in the development of each nation and possesses a huge treasure of data that traditional technologies cannot handle. Indeed, many countries have applied Big Data-based intelligent transportation systems because it is a traffic system that interacts with vehicles and people on the road, thereby reducing traffic congestion and traffic accidents year by year in many countries. The article presents the applications of Big Data technology in smart traffic systems, thereby providing the perspective of a smart city with a smart traffic system as a critical factor. This paper's analysis indicated that smart cities could be born and further developed through the linkage of Big Data technology and smart traffic systems with smart traffic systems as the core. In addition, the results also showed that the obstacle that needs to be studied at this time is the policy and legal framework for Big Data technology. Therefore, a system managed by the state or shared between the state and the private sector should be studied in the future, aiming to harmonize interests and develop the system extensively.

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Section: A Application Of Big Data In Itsmentioning

confidence: 99%

Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems

Nguyen

Bui³

2022

JOIV : Int. J. Inform. Visualization

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“…P. C. de Lima Silva et al proposed a prediction method based on fuzzy time series, which can predict points, intervals, and distributions by using fuzzy and random patterns of data [7]. R. Li et al proposed a long-term forecasting scheme and implementation method based on the interval type-2 fuzzy sets theory for traffic flow data [8]. H. Jiang et al used an autoregressive model to study the influence of spectrum band-width, peak frequency and hull scale on ship motion prediction [9].…”

Section: Introductionmentioning

confidence: 99%

Ship Roll Prediction Algorithm Based on Bi-LSTM-TPA Combined Model

Wang

Zou

et al. 2021

JMSE

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When ships sail on the sea, the changes of ship motion attitude presents the characteristics of nonlinearity and high randomness. Aiming at the problem of low accuracy of ship roll angle prediction by traditional prediction algorithms and single neural network model, a ship roll angle prediction method based on bidirectional long short-term memory network (Bi-LSTM) and temporal pattern attention mechanism (TPA) combined deep learning model is proposed. Bidirectional long short-term memory network extracts time features from the forward and reverse of the ship roll angle time series, and temporal pattern attention mechanism extracts the time patterns from the deep features of a bidirectional long short-term memory network output state that are beneficial to ship roll angle prediction, ignore other features that contribute less to the prediction. The experimental results of real ship data show that the proposed Bi-LSTM-TPA combined model has a significant reduction in MAPE, MAE, and MSE compared with the LSTM model and the SVM model, which verifies the effectiveness of the proposed algorithm.

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“…According to [9][10][11][12] fuzzy logic type 2 has advantages over fuzzy logic type 1 in handling uncertainties in memberships functions and in unexpected disturbances and is very much used in traffic [13], for power control [14], fault detection [15] and image processing [16] and control for Dual Star Induction Machine [17].…”

Section: Introductionmentioning

confidence: 99%

Sliding Control with Fuzzy Type-2 Controller of Wind Energy System Based on Doubly Fed Induction Generator

Zouggar¹,

Chaouch²,

Abdeslam³

et al. 2019

I2M

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The wind system based on double-fed induction generator (DFIG) has become a very important source of energy. To ensure the proper functioning of this system, many improved control algorithms have been developed for the rotor side converter (RSC). This article presents the analysis and design of a double-fed induction generator (DFIG) control technique based on coupling the type-2 fuzzy logic control with the sliding mode control (SMC). For the design of this technique, a decoupled modeling of the DFIG with the orientation of its stator flow is presented. The main purpose of the proposed technique is to make a control to meter the quantities of the powers produced by DFIG which are injected into the electrical network and to reduce the phenomenon of chattering which depends on control by sliding mode. This command has allowed us to reduce the chattering phenomenon and improve the performance of the system in terms of speed monitoring and stator side powers regulation. Simulations are performed using MATLAB / Simulink to validate the effectiveness of the proposed control algorithm. The simulation results, obtained when applying this control strategy to the system, demonstrated the validity of the results and thus validated the high performance of this control technique.

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Traffic flow data forecasting based on interval type-2 fuzzy sets theory

Cited by 48 publications

References 14 publications

Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems

Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems

Ship Roll Prediction Algorithm Based on Bi-LSTM-TPA Combined Model

Sliding Control with Fuzzy Type-2 Controller of Wind Energy System Based on Doubly Fed Induction Generator

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