Journal ArticleDOI
A seasonal direct optimal hybrid model of computational intelligence and soft computing techniques for electricity load forecasting
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TLDR
A direct optimum parallel hybrid model is proposed based on multilayer perceptrons (MLP) neural network, Adaptive Network-based Fuzzy Inference System (ANFIS), and Seasonal Autoregressive Integrated Moving Average (SARIMA) in order to electricity load forecasting.About:
This article is published in Energy.The article was published on 2017-12-01. It has received 51 citations till now. The article focuses on the topics: Probabilistic forecasting & Computational intelligence.read more
Citations
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Journal ArticleDOI
State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
Amir Mosavi,Amir Mosavi,Amir Mosavi,Mohsen Salimi,Sina Ardabili,Timon Rabczuk,Shahaboddin Shamshirband,Annamária R. Várkonyi-Kóczy +7 more
TL;DR: There is an outstanding rise in the accuracy, robustness, precision and generalization ability of the ML models in energy systems using hybrid ML models.
Journal ArticleDOI
Short term electricity load forecasting using a hybrid model
TL;DR: A new hybrid model based on improved empirical mode decomposition (IEMD), autoregressive integrated moving average (ARIMA) and wavelet neural network (WNN) optimized by fruit fly optimization algorithm (FOA) is proposed and compared with some other models.
Journal ArticleDOI
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
TL;DR: Different sub-models, hybridization strategies, structural designs, screening criteria, and new directions in hybrid modeling are reviewed, with focus on the corresponding applications in chemical, petroleum, and energy systems.
Journal ArticleDOI
Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
Tanveer Ahmad,Tanveer Ahmad,Dongdong Zhang,Chao Huang,Chao Huang,Hongcai Zhang,Ning-Yi Dai,Yonghua Song,Yonghua Song,Huanxin Chen +9 more
TL;DR: How AI techniques outperform traditional models in controllability, big data handling, cyberattack prevention, smart grid, IoT, robotics, energy efficiency optimization, predictive maintenance control, and computational efficiency is explored.
Journal ArticleDOI
Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model
Paul A. Adedeji,Stephen A. Akinlabi,Stephen A. Akinlabi,Nkosinathi Madushele,Obafemi O. Olatunji +4 more
TL;DR: Based on the findings, a hybrid ANFIS model gives better forecast accuracy compared to the standalone model, though with a trade-off in the computational time, this study recommends SC technique for ANfIS modeling at both standalone and hybrid models.
References
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Book
Time series analysis, forecasting and control
TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
Journal ArticleDOI
ANFIS: adaptive-network-based fuzzy inference system
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Journal ArticleDOI
Time Series Analysis: Forecasting and Control
TL;DR: Time Series Analysis and Forecasting: principles and practice as mentioned in this paper The Oxford Handbook of Quantitative Methods, Vol. 3, No. 2: Statistical AnalysisTime-Series ForecastingPractical Time-Series AnalysisApplied Bayesian Forecasting and Time Series AnalysisSAS for Forecasting Time SeriesApplied Time Series analysisTime Series analysisElements of Nonlinear Time Series analyses and forecastingTime series analysis and forecasting by Example.
Journal ArticleDOI
Forecasting with artificial neural networks: the state of the art
TL;DR: In this paper, the authors present a state-of-the-art survey of ANN applications in forecasting and provide a synthesis of published research in this area, insights on ANN modeling issues, and future research directions.
Journal ArticleDOI
Time series forecasting using a hybrid ARIMA and neural network model
TL;DR: Experimental results with real data sets indicate that the combined model can be an effective way to improve forecasting accuracy achieved by either of the models used separately.
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