A Hybrid ANFIS- PSO Model for Scour Depth Prediction

Jannaty, Mohammad Heman; Eghbalzadeh, Afshin; Hosseini, SeyedAbbas

Document Type : Research Paper

Authors

¹ Ph.D. Scholar, Department of Civil Engineering, Faculty of Civil Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran

² Assist. Professor, Department of Civil Engineering, Faculty of Civil Engineering, University of Razi, Kermanshah, Iran

³ Assist. Professor, Department of Civil Engineering, Faculty of Civil Engineering, Islamic Azad University, Science and Research Branch, Tehran, iran

Abstract

In recent years, newly-developed data mining and machine learning techniques have been applied in various ﬁelds to build intelligent information systems. However, few of these approaches offer online support or are ﬂexibleto be adapted to large and complex datasets. Therefore, the present research work adopts Particle Swarm Optimization (PSO) techniques to obtain appropriate parameter settings for membership function and integrates the Adaptive-Network-based Fuzzy Inference System (ANFIS) model to make the model fit for predicting scour depth. A dataset of 188 scour depths for single piers presented by the USGS was used. Results of the model prediction show that the derived model is best fitted to the field data. The proposed one-order momentum method is able to learn quickly through one-pass training and provides high-accuracy short-term predictions. Moreover, this method is suitable for online learning but the two-order momentum method is appropriate for incremental learning. The PSO-ANFIS approach could provide better results in predicting scour depths compared with other models.

Keywords

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Environment and Water Engineering

A Hybrid ANFIS- PSO Model for Scour Depth Prediction

References

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Volume 1, Issue 1 - Serial Number 1
December 2015
Pages 81-94

A Hybrid ANFIS- PSO Model for Scour Depth Prediction

References

References

Volume 1, Issue 1 - Serial Number 1December 2015Pages 81-94

Volume 1, Issue 1 - Serial Number 1
December 2015
Pages 81-94