Forecasting

2018 - 2025

Current editor(s): Ms. Joss Chen

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Volume 3, issue 4, 2021

Forecasting with Machine Learning Techniques pp. 1-2

Walayat Hussain, Asma Musabah Alkalbani and Honghao Gao

A Deep Learning Model for Forecasting Velocity Structures of the Loop Current System in the Gulf of Mexico pp. 1-20

Ali Muhamed Ali, Hanqi Zhuang, James VanZwieten, Ali K. Ibrahim and Laurent Chérubin

A Real-Time Data Analysis Platform for Short-Term Water Consumption Forecasting with Machine Learning pp. 1-13

Aida Boudhaouia and Patrice Wira

On the Autoregressive Time Series Model Using Real and Complex Analysis pp. 1-13

Torsten Ullrich

Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests pp. 1-36

Ulrich Gunter

Different Forecasting Horizons Based Performance Analysis of Electricity Load Forecasting Using Multilayer Perceptron Neural Network pp. 1-35

Manogaran Madhiarasan and Mohamed Louzazni

COVID-19 and Tourism: Analyzing the Effects of COVID-19 Statistics and Media Coverage on Attitudes toward Tourism pp. 1-14

Maksim Godovykh, Jorge Ridderstaat, Carissa Baker and Alan Fyall

Model-Free Time-Aggregated Predictions for Econometric Datasets pp. 1-14

Kejin Wu and Sayar Karmakar

Battery Sizing for Different Loads and RES Production Scenarios through Unsupervised Clustering Methods pp. 1-19

Alfredo Nespoli, Andrea Matteri, Silvia Pretto, Luca De Ciechi and Emanuele Ogliari

Bayesian Forecasting of Dynamic Extreme Quantiles pp. 1-12

Douglas E. Johnston

Examining Deep Learning Architectures for Crime Classification and Prediction pp. 1-22

Panagiotis Stalidis, Theodoros Semertzidis and Petros Daras

Assessing Goodness of Fit for Verifying Probabilistic Forecasts pp. 1-11

Tae-Ho Kang, Ashish Sharma and Lucy Marshall

Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm pp. 1-11

Eren Bas, Erol Egrioglu and Ufuk Yolcu

Deterministic-Probabilistic Approach to Predict Lightning-Caused Forest Fires in Mounting Areas pp. 1-21

Nikolay Baranovskiy

Landslide Forecast by Time Series Modeling and Analysis of High-Dimensional and Non-Stationary Ground Motion Data pp. 1-18

Guoqi Qian, Antoinette Tordesillas and Hangfei Zheng

Forecasting Internal Migration in Russia Using Google Trends: Evidence from Moscow and Saint Petersburg pp. 1-30

Dean Fantazzini, Julia Pushchelenko, Alexey Mironenkov and Alexey Kurbatskii

Volume 3, issue 3, 2021

Gutenberg–Richter B-Value Time Series Forecasting: A Weighted Likelihood Approach pp. 1-9

Matteo Taroni, Giorgio Vocalelli and Andrea De Polis

Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices pp. 1-19

Lorenzo Menculini, Andrea Marini, Massimiliano Proietti, Alberto Garinei, Alessio Bozza, Cecilia Moretti and Marcello Marconi

The Effect of Lead-Time Weather Forecast Uncertainty on Outage Prediction Modeling pp. 1-16

Feifei Yang, Diego Cerrai and Emmanouil N. Anagnostou

Modeling and Forecasting Daily Hotel Demand: A Comparison Based on SARIMAX, Neural Networks, and GARCH Models pp. 1-16

Apostolos Ampountolas

Attention-Based CNN-RNN Arabic Text Recognition from Natural Scene Images pp. 1-21

Hanan Butt, Muhammad Raheel Raza, Muhammad Javed Ramzan, Muhammad Junaid Ali and Muhammad Haris

Short-Term Electricity Price Forecasting by Employing Ensemble Empirical Mode Decomposition and Extreme Learning Machine pp. 1-18

Sajjad Khan, Shahzad Aslam, Iqra Mustafa and Sheraz Aslam

A Brief Taxonomy of Hybrid Intelligence pp. 1-11

Niccolo Pescetelli

Editorial for Special Issue “New Frontiers in Forecasting the Business Cycle and Financial Markets” pp. 1-3

Alessia Paccagnini

Advances in Hydrological Forecasting pp. 1-3

Minxue He and Haksu Lee

The Wisdom of the Data: Getting the Most Out of Univariate Time Series Forecasting pp. 1-20

Fotios Petropoulos and Evangelos Spiliotis

Influence of the Characteristics of Weather Information in a Thunderstorm-Related Power Outage Prediction System pp. 1-20

Peter L. Watson, Marika Koukoula and Emmanouil Anagnostou

Loop Current SSH Forecasting: A New Domain Partitioning Approach for a Machine Learning Model pp. 1-10

Justin L. Wang, Hanqi Zhuang, Laurent Chérubin, Ali Muhamed Ali and Ali Ibrahim

Probabilistic Day-Ahead Wholesale Price Forecast: A Case Study in Great Britain pp. 1-37

Stephen Haben, Julien Caudron and Jake Verma

Volume 3, issue 2, 2021

Is It Possible to Forecast the Price of Bitcoin? pp. 1-44

Julien Chevallier, Dominique Guégan and Stéphane Goutte

Building Heat Demand Forecasting by Training a Common Machine Learning Model with Physics-Based Simulator pp. 1-13

Lotta Kannari, Jussi Kiljander, Kalevi Piira, Jouko Piippo and Pekka Koponen

Forecasting Commodity Prices: Looking for a Benchmark pp. 1-13

Marek Kwas and Michał Rubaszek

Pre-Operational Application of a WRF-Hydro-Based Fluvial Flood Forecasting System in the Southeast Mediterranean pp. 1-10

Christos Giannaros, Elissavet Galanaki, Vassiliki Kotroni, Konstantinos Lagouvardos, Christina Oikonomou, Haris Haralambous and Theodore M. Giannaros

Visual Analytics for Climate Change Detection in Meteorological Time-Series pp. 1-14

Milena Vuckovic and Johanna Schmidt

Queue Length Forecasting in Complex Manufacturing Job Shops pp. 1-17

Marvin Carl May, Alexander Albers, Marc David Fischer, Florian Mayerhofer, Louis Schäfer and Gisela Lanza

A Stochastic Estimation Framework for Yearly Evolution of Worldwide Electricity Consumption pp. 1-11

Qasem Abu Al-Haija

A New Machine Learning Forecasting Algorithm Based on Bivariate Copula Functions pp. 1-22

J. A. Carrillo, M. Nieto, J. F. Velez and D. Velez

Tobacco Endgame Simulation Modelling: Assessing the Impact of Policy Changes on Smoking Prevalence in 2035 pp. 1-9

Michael Chaiton, Jolene Dubray, G. Emmanuel Guindon and Robert Schwartz

A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements pp. 1-16

Bernardina Algieri, Arturo Leccadito and Pietro Toscano

The Yield Curve as a Leading Indicator: Accuracy and Timing of a Parsimonious Forecasting Model pp. 1-16

Knut Lehre Seip and Dan Zhang

Fighting Deepfakes Using Body Language Analysis pp. 1-19

Robail Yasrab, Wanqi Jiang and Adnan Riaz

Volume 3, issue 1, 2021

Forecasting with Business and Consumer Survey Data pp. 1-22

Oscar Claveria

Modeling Post-Liberalized European Gas Market Concentration—A Game Theory Perspective pp. 1-16

Hassan Hamie, Anis Hoayek and Hans Auer

Trends in Using IoT with Machine Learning in Health Prediction System pp. 1-26

Amani Aldahiri, Bashair Alrashed and Walayat Hussain

Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes pp. 1-15

Alexander Faehnle and Mariangela Guidolin

Editorial for Special Issue: “Feature Papers of Forecasting” pp. 1-3

Sonia Leva

Forecasting Principles from Experience with Forecasting Competitions pp. 1-28

Jennifer Castle, Jurgen Doornik and David Hendry

Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE) pp. 1-17

Rodgers Makwinja, Seyoum Mengistou, Emmanuel Kaunda, Tena Alemiew, Titus Bandulo Phiri, Ishmael Bobby Mphangwe Kosamu and Chikumbusko Chiziwa Kaonga

Electrical Load Forecast by Means of LSTM: The Impact of Data Quality pp. 1-11

Alfredo Nespoli, Emanuele Ogliari, Silvia Pretto, Michele Gavazzeni, Sonia Vigani and Franco Paccanelli

Construction of a Predictive Model for MLB Matches pp. 1-11

Chia-Hao Chang

Robust Non-Parametric Mortality and Fertility Modelling and Forecasting: Gaussian Process Regression Approaches pp. 1-21

Ka Kin Lam and Bo Wang

A Model Predictive Control for the Dynamical Forecast of Operating Reserves in Frequency Regulation Services pp. 1-14

Pavlos Nikolaidis and Harris Partaourides

Load Forecasting in an Office Building with Different Data Structure and Learning Parameters pp. 1-14

Daniel Ramos, Mahsa Khorram, Pedro Faria and Zita Vale

Acknowledgment to Reviewers of Forecasting in 2020 pp. 1-2

Forecasting Editorial Office

Forecasting the Preparatory Phase of Induced Earthquakes by Recurrent Neural Network pp. 1-20

Matteo Picozzi and Antonio Giovanni Iaccarino

Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data pp. 1-35

Monica Defend, Aleksey Min, Lorenzo Portelli, Franz Ramsauer, Francesco Sandrini and Rudi Zagst