The Prediction of Short-term Traffic Flow Based on the Niche Genetic Algorithm and BP Neural Network

Ren, Chuanxiang; Wang, Chengbao; Yin, Changchang; Chen, Meng; Shen, Xu

doi:10.1007/978-3-642-34522-7_82

Cited by 4 publications

(2 citation statements)

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“…Ren et al carried out a study on the prediction of short-term traffic flow with an Artificial Intelligence-based approach. In this context, they used a prediction approach including the back-propagation neural network-niche genetic algorithm (NGA) [37]. In another study on predicting traffic flow, Ding et al predicted the 'lane-change trajectory by drivers' in urban traffic flow [38].…”

Section: A Brief Review Of the Literaturementioning

confidence: 99%

An Ant-Lion Optimizer-Trained Artificial Neural Network System for Chaotic Electroencephalogram (EEG) Prediction

Köse

2018

Applied Sciences

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The prediction of future events based on available time series measurements is a relevant research area specifically for healthcare, such as prognostics and assessments of intervention applications. A measure of brain dynamics, electroencephalogram time series, are routinely analyzed to obtain information about current, as well as future, mental states, and to detect and diagnose diseases or environmental factors. Due to their chaotic nature, electroencephalogram time series require specialized techniques for effective prediction. The objective of this study was to introduce a hybrid system developed by artificial intelligence techniques to deal with electroencephalogram time series. Both artificial neural networks and the ant-lion optimizer, which is a recent intelligent optimization technique, were employed to comprehend the related system and perform some prediction applications over electroencephalogram time series. According to the obtained findings, the system can successfully predict the future states of target time series and it even outperforms some other hybrid artificial neural network-based systems and alternative time series prediction approaches from the literature.

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Section: A Brief Review Of the Literaturementioning

confidence: 99%

An Ant-Lion Optimizer-Trained Artificial Neural Network System for Chaotic Electroencephalogram (EEG) Prediction

Köse

2018

Applied Sciences

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“…Intelligence-based approach. In this context, they have used a prediction approach including BP Neural Network -Niche Genetic Algorithm (NGA) [37].In another study on predicting traffic-flow, Ding et al have predicted "lane-change trajectory by drivers" in urban traffic flow [38]. In the context of predicting urban traffic-flow, also Yin et al…”

Section: Introductionmentioning

confidence: 99%

Time Series Prediction With a Hybrid System Formed by Artificial Neural Network and Cognitive Development Optimization Algorithm

Köse

Arslan

2018

Scientia Iranica

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Time series prediction is a remarkable research interest, which is widely followed by scientists / researchers. Because many fields include analyzing processes over such time series, different kinds of approaches, methods, and techniques are often employed in order to achieve alternative prediction ways. It seems that Artificial Intelligence oriented solutions have strong potential on providing effective and accurate prediction approaches in even most complicated time series structures. In the sense of the explanations, this study aims to technique introduced by the authors. Here, it has been aimed to predict different kinds of time series, by using the introduced system / approach. In this way it has been possible to discuss about application potential of the hybrid system and report findings related to its success on prediction. The authors believe that the study has been a good chance to support the literature with an alternative solution approach and see potential of a newly developed, Artificial Intelligence oriented optimization algorithm on different applications.

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Nature-Based Algorithms

Majumder

Ghosh²

2013

Decision Making Algorithms for Hydro-Power Plant Location

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The Prediction of Short-term Traffic Flow Based on the Niche Genetic Algorithm and BP Neural Network

Cited by 4 publications

References 1 publication

An Ant-Lion Optimizer-Trained Artificial Neural Network System for Chaotic Electroencephalogram (EEG) Prediction

An Ant-Lion Optimizer-Trained Artificial Neural Network System for Chaotic Electroencephalogram (EEG) Prediction

Time Series Prediction With a Hybrid System Formed by Artificial Neural Network and Cognitive Development Optimization Algorithm

Nature-Based Algorithms

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