I
Ioannis P. Panapakidis
Researcher at University of Thessaly
Publications - 84
Citations - 1434
Ioannis P. Panapakidis is an academic researcher from University of Thessaly. The author has contributed to research in topics: Cluster analysis & Renewable energy. The author has an hindex of 15, co-authored 77 publications receiving 1021 citations. Previous affiliations of Ioannis P. Panapakidis include Aristotle University of Thessaloniki & Technological Educational Institute of Western Macedonia.
Papers
More filters
Journal ArticleDOI
Day-ahead electricity price forecasting via the application of artificial neural network based models
TL;DR: In this article, the authors examined artificial neural network (ANN) based models for day-ahead price forecasting, where the training data are clustered in homogenous groups and for each cluster, a dedicated forecaster is employed.
Journal ArticleDOI
Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model
TL;DR: In this paper, a hybrid computational intelligence model combining the Wavelet Transform (WT), GA, Adaptive Neuro-Fuzzy Inference System (ANFIS), and feed-forward neural network (FFNN) is proposed for day-ahead natural gas demand prediction.
Repository
Forecasting: theory and practice
Fotios Petropoulos,Daniele Apiletti,Vassilios Assimakopoulos,Mohamed Zied Babai,Devon K. Barrow,Souhaib Ben Taieb,Christoph Bergmeir,Ricardo J. Bessa,Jakub Bijak,John E. Boylan,Jethro Browell,Claudio Carnevale,Jennifer L. Castle,Pasquale Cirillo,Michael P. Clements,Clara Cordeiro,Clara Cordeiro,Fernando Luiz Cyrino Oliveira,Shari De Baets,Alexander Dokumentov,Joanne Ellison,Piotr Fiszeder,Philip Hans Franses,David T. Frazier,Michael Gilliland,M. Sinan Gönül,Paul Goodwin,Luigi Grossi,Yael Grushka-Cockayne,Mariangela Guidolin,Massimo Guidolin,Ulrich Gunter,Xiaojia Guo,Renato Guseo,Nigel Harvey,David F. Hendry,Ross Hollyman,Tim Januschowski,Jooyoung Jeon,Victor Richmond R. Jose,Yanfei Kang,Anne B. Koehler,Stephan Kolassa,Nikolaos Kourentzes,Nikolaos Kourentzes,Sonia Leva,Feng Li,Konstantia Litsiou,Spyros Makridakis,Gael M. Martin,Andrew B. Martinez,Andrew B. Martinez,Sheik Meeran,Theodore Modis,Konstantinos Nikolopoulos,Dilek Önkal,Alessia Paccagnini,Alessia Paccagnini,Anastasios Panagiotelis,Ioannis P. Panapakidis,Jose M. Pavía,Manuela Pedio,Manuela Pedio,Diego J. Pedregal,Pierre Pinson,Patrícia Ramos,David E. Rapach,J. James Reade,Bahman Rostami-Tabar,Michał Rubaszek,Georgios Sermpinis,Han Lin Shang,Evangelos Spiliotis,Aris A. Syntetos,Priyanga Dilini Talagala,Thiyanga S. Talagala,Len Tashman,Dimitrios D. Thomakos,Thordis L. Thorarinsdottir,Ezio Todini,Juan Ramón Trapero Arenas,Xiaoqian Wang,Robert L. Winkler,Alisa Yusupova,Florian Ziel +84 more
TL;DR: A non-systematic review of the theory and the practice of forecasting, offering a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts.
Journal ArticleDOI
Pattern recognition algorithms for electricity load curve analysis of buildings
Ioannis P. Panapakidis,Theofilos A. Papadopoulos,Georgios C. Christoforidis,Grigoris K. Papagiannis +3 more
TL;DR: In this paper, a comprehensive methodology for the investigation of the electricity behavior of buildings, using clustering techniques, is proposed, which is applied to the load curves of different buildings leading to the determination of an optimum clustering procedure.
Journal ArticleDOI
Clustering based day-ahead and hour-ahead bus load forecasting models
TL;DR: In this paper, the authors developed bus forecasting models for day-ahead and hour-ahead load predictions based on Artificial Neural Networks (ANNs) using a clustering methodology, the forecasting accuracy of the ANNs is enhanced leading to the formulation of hybrid forecasting models that are characterized by high level of parameterization and efficiency.