Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization
- https://doi.org/10.2991/ijcis.d.190930.003How to use a DOI?
- Meta-heuristics, Coral reefs optimization, Opposition-based learning, Neural networks, Time series forecasting, Nature-inspired algorithms, Distributed systems
In this paper, a novel algorithm called opposition-based coral reefs optimization (OCRO) is introduced. The algorithm is built as an improvement for coral reefs optimization (CRO) using opposition-based learning (OBL). For efficient modeling as the main part of this work, a novel time series forecasting model called OCRO-multi-layer neural network (MLNN) is proposed to explore hidden relationships in the non-linear time series data. The model thus combines OCRO with MLNN for data processing, which enables reducing the model complexity by faster convergence than the traditional back-propagation algorithm. For validation of the proposed model, three real-world datasets are used, including Internet traffic collected from a private internet service provider (ISP) with distributed centers in 11 European cities, WorldCup 98 contains request numbers to the server in football world cup season in 1998, and Google cluster log dataset gathered from its data center. Through the carried out experiments, we demonstrated that with both univariate and multivariate data, the proposed prediction model gains good performance in accuracy, run time and model stability aspects as compared with other modern learning techniques like recurrent neural network (RNN) and long short-term memory (LSTM). In addition, with used real datasets, we intend to concentrate on applying OCRO-MLNN to distributed systems in order to enable the proactive resource allocation capability for e-infrastructures (e.g. clouds services, Internet of Things systems, or blockchain networks).
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Thieu Nguyen AU - Tu Nguyen AU - Binh Minh Nguyen AU - Giang Nguyen PY - 2019 DA - 2019/11 TI - Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization JO - International Journal of Computational Intelligence Systems SP - 1144 EP - 1161 VL - 12 IS - 2 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.190930.003 DO - https://doi.org/10.2991/ijcis.d.190930.003 ID - Nguyen2019 ER -