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A new metric of absolute percentage error for intermittent demand forecasts

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  1. Gaetano Perone, 2022. "Using the SARIMA Model to Forecast the Fourth Global Wave of Cumulative Deaths from COVID-19: Evidence from 12 Hard-Hit Big Countries," Econometrics, MDPI, vol. 10(2), pages 1-23, April.
  2. Md Asaduzzaman Shoeb & Farhad Shahnia & GM Shafiullah & Fushuan Wen, 2023. "A Technique to Optimally Prevent the Voltage and Frequency Violation in Renewable Energy Integrated Microgrids," Energies, MDPI, vol. 16(15), pages 1-27, August.
  3. Arthur Novaes de Amorim & Rob Deardon & Vineet Saini, 2021. "A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-15, March.
  4. Mohsen Sadegh Amalnick & Naser Habibifar & Mahdi Hamid & Mahdi Bastan, 2020. "An intelligent algorithm for final product demand forecasting in pharmaceutical units," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 481-493, April.
  5. Li, Johnny Siu-Hang & Liu, Yanxin & Chan, Wai-Sum, 2023. "Hedging longevity risk under non-Gaussian state-space stochastic mortality models: A mean-variance-skewness-kurtosis approach," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 96-121.
  6. Ioannis Badounas & Georgios Pitselis, 2020. "Loss Reserving Estimation With Correlated Run-Off Triangles in a Quantile Longitudinal Model," Risks, MDPI, vol. 8(1), pages 1-26, February.
  7. Pala, Zeydin, 2023. "Comparative study on monthly natural gas vehicle fuel consumption and industrial consumption using multi-hybrid forecast models," Energy, Elsevier, vol. 263(PC).
  8. Jean-François Verne, 2021. "Smooth Threshold Autoregressive models and Markov process: An application to the Lebanese GDP growth rate," International Econometric Review (IER), Econometric Research Association, vol. 13(3), pages 71-88, September.
  9. Lee, Joseph C.Y. & Draxl, Caroline & Berg, Larry K., 2022. "Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework," Renewable Energy, Elsevier, vol. 200(C), pages 457-475.
  10. Shaojun Yang & Hua Wei & Le Zhang & Shengchao Qin, 2021. "Daily Power Generation Forecasting Method for a Group of Small Hydropower Stations Considering the Spatial and Temporal Distribution of Precipitation—South China Case Study," Energies, MDPI, vol. 14(15), pages 1-19, July.
  11. Patryk Hara & Magdalena Piekutowska & Gniewko Niedbała, 2021. "Selection of Independent Variables for Crop Yield Prediction Using Artificial Neural Network Models with Remote Sensing Data," Land, MDPI, vol. 10(6), pages 1-21, June.
  12. Gaetano Perone, 2022. "Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 917-940, August.
  13. Hess, Alexander & Spinler, Stefan & Winkenbach, Matthias, 2021. "Real-time demand forecasting for an urban delivery platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
  14. Hu, Xincheng & Banks, Jonathan & Wu, Linping & Liu, Wei Victor, 2020. "Numerical modeling of a coaxial borehole heat exchanger to exploit geothermal energy from abandoned petroleum wells in Hinton, Alberta," Renewable Energy, Elsevier, vol. 148(C), pages 1110-1123.
  15. Tianxiang Zheng & Shaopeng Liu & Zini Chen & Yuhan Qiao & Rob Law, 2020. "Forecasting Daily Room Rates on the Basis of an LSTM Model in Difficult Times of Hong Kong: Evidence from Online Distribution Channels on the Hotel Industry," Sustainability, MDPI, vol. 12(18), pages 1-17, September.
  16. Corey Ducharme & Bruno Agard & Martin Trépanier, 2024. "Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1661-1681, August.
  17. Li, Chen & Kies, Alexander & Zhou, Kai & Schlott, Markus & Sayed, Omar El & Bilousova, Mariia & Stöcker, Horst, 2024. "Optimal Power Flow in a highly renewable power system based on attention neural networks," Applied Energy, Elsevier, vol. 359(C).
  18. Colin Singleton & Peter Grindrod, 2021. "Forecasting for Battery Storage: Choosing the Error Metric," Energies, MDPI, vol. 14(19), pages 1-11, October.
  19. Apostolos Ampountolas & Mark Legg, 2024. "Predicting daily hotel occupancy: a practical application for independent hotels," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(3), pages 197-205, June.
  20. Sojin Park & Nahyun Kwon & Yonghan Ahn, 2019. "Forecasting Repair Schedule for Building Components Based on Case-Based Reasoning and Fuzzy-AHP," Sustainability, MDPI, vol. 11(24), pages 1-17, December.
  21. Philippe St-Aubin & Bruno Agard, 2022. "Precision and Reliability of Forecasts Performance Metrics," Forecasting, MDPI, vol. 4(4), pages 1-22, October.
  22. Arash YoosefDoost & William David Lubitz, 2021. "Archimedes Screw Design: An Analytical Model for Rapid Estimation of Archimedes Screw Geometry," Energies, MDPI, vol. 14(22), pages 1-14, November.
  23. Khan, Waqas & Somers, Ward & Walker, Shalika & de Bont, Kevin & Van der Velden, Joep & Zeiler, Wim, 2023. "Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation," Energy, Elsevier, vol. 283(C).
  24. Chou, Jui-Sheng & Truong, Dinh-Nhat & Kuo, Ching-Chiun, 2021. "Imaging time-series with features to enable visual recognition of regional energy consumption by bio-inspired optimization of deep learning," Energy, Elsevier, vol. 224(C).
  25. Xiaodong Li & Ai Ren & Qi Li, 2022. "Exploring Patterns of Transportation-Related CO 2 Emissions Using Machine Learning Methods," Sustainability, MDPI, vol. 14(8), pages 1-21, April.
  26. Mostofi Fatemeh & Toğan Vedat & Başağa Hasan Basri, 2022. "Real-estate price prediction with deep neural network and principal component analysis," Organization, Technology and Management in Construction, Sciendo, vol. 14(1), pages 2741-2759, January.
  27. Moting Su & Zongyi Zhang & Ye Zhu & Donglan Zha & Wenying Wen, 2019. "Data Driven Natural Gas Spot Price Prediction Models Using Machine Learning Methods," Energies, MDPI, vol. 12(9), pages 1-17, May.
  28. Dariusz Młyński, 2020. "Analysis of Problems Related to the Calculation of Flood Frequency Using Rainfall-Runoff Models: A Case Study in Poland," Sustainability, MDPI, vol. 12(17), pages 1-17, September.
  29. Zeydin Pala & Fatih Şevgin, 2024. "Statistical modeling for long-term meteorological forecasting: a case study in Van Lake Basin," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(15), pages 14101-14116, December.
  30. Karakurt, Izzet, 2021. "Modelling and forecasting the oil consumptions of the BRICS-T countries," Energy, Elsevier, vol. 220(C).
  31. Andreas Marcus Gohs, 2022. "Forecasting Market Diffusion of Innovative Battery-Electric and Conventional Vehicles in Germany under Model Uncertainty," MAGKS Papers on Economics 202209, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  32. Pawan Kumar Singh & Anushka Chouhan & Rajiv Kumar Bhatt & Ravi Kiran & Ansari Saleh Ahmar, 2022. "Implementation of the SutteARIMA method to predict short-term cases of stock market and COVID-19 pandemic in USA," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2023-2033, August.
  33. Felix Lokin & Fenghui Yu, 2024. "Fill Probabilities in a Limit Order Book with State-Dependent Stochastic Order Flows," Papers 2403.02572, arXiv.org.
  34. Hu, Xincheng & Banks, Jonathan & Guo, Yunting & Liu, Wei Victor, 2022. "Utilizing geothermal energy from enhanced geothermal systems as a heat source for oil sands separation: A numerical evaluation," Energy, Elsevier, vol. 238(PA).
  35. Bhatia, Kushagra & Mittal, Rajat & Varanasi, Jyothi & Tripathi, M.M., 2021. "An ensemble approach for electricity price forecasting in markets with renewable energy resources," Utilities Policy, Elsevier, vol. 70(C).
  36. Apostolos Ampountolas, 2019. "Forecasting hotel demand uncertainty using time series Bayesian VAR models," Tourism Economics, , vol. 25(5), pages 734-756, August.
  37. José Luis Roca-González & Antonio Juan Briones Peñalver & Francisco Campuzano-Bolarín, 2020. "Raptor Feeding Characterization and Dynamic System Simulation Applied to Airport Falconry," Sustainability, MDPI, vol. 12(21), pages 1-21, October.
  38. Stuart J. Fairclough & Danielle L. Christian & Pedro F. Saint-Maurice & Paul R. Hibbing & Robert J. Noonan & Greg J. Welk & Philip M. Dixon & Lynne M. Boddy, 2019. "Calibration and Validation of the Youth Activity Profile as a Physical Activity and Sedentary Behaviour Surveillance Tool for English Youth," IJERPH, MDPI, vol. 16(19), pages 1-17, October.
  39. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
  40. Berta, P. & Lovaglio, P.G. & Paruolo, P. & Verzillo, S., 2020. "Real Time Forecasting of Covid-19 Intensive Care Units demand," Health, Econometrics and Data Group (HEDG) Working Papers 20/16, HEDG, c/o Department of Economics, University of York.
  41. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
  42. Posch, Konstantin & Truden, Christian & Hungerländer, Philipp & Pilz, Jürgen, 2022. "A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants," International Journal of Forecasting, Elsevier, vol. 38(1), pages 321-338.
  43. Anders Nõu & Darya Lapitskaya & Mustafa Hakan Eratalay & Rajesh Sharma, 2021. "Predicting Stock Return And Volatility With Machine Learning And Econometric Models: A Comparative Case Study Of The Baltic Stock Market," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 135, Faculty of Economics and Business Administration, University of Tartu (Estonia).
  44. Marinho G. Andrade & Katiane S. Conceição & Nalini Ravishanker, 2024. "Zero-modified count time series modeling with an application to influenza cases," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 108(3), pages 611-637, September.
  45. Dominik Martin & Philipp Spitzer & Niklas Kuhl, 2020. "A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs," Papers 2004.10537, arXiv.org.
  46. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
  47. Mohammed Bouasabah & Oshamah Ibrahim Khalaf, 2023. "A Technical Indicator for a Short-term Trading Decision in the NASDAQ Market," Advances in Decision Sciences, Asia University, Taiwan, vol. 27(3), pages 1-13, September.
  48. Ozancan Ozdemir & Ceylan Yozgatligil, 2024. "Forecasting performance of machine learning, time series, and hybrid methods for low‐ and high‐frequency time series," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 78(2), pages 441-474, May.
  49. Baker, Rose & Forrest, David & Pérez, Levi, 2020. "Modelling demand for lotto using a novel method of correcting for endogeneity," Economic Modelling, Elsevier, vol. 84(C), pages 302-308.
  50. Ansari Saleh Ahmar & Pawan Kumar Singh & R. Ruliana & Alok Kumar Pandey & Stuti Gupta, 2023. "Comparison of ARIMA, SutteARIMA, and Holt-Winters, and NNAR Models to Predict Food Grain in India," Forecasting, MDPI, vol. 5(1), pages 1-15, January.
  51. Jorge V Pérez-Rodríguez & Juan M Hernández & Julián Andrada-Félix, 2024. "Modelling prices and volatilities in the sharing economy," Tourism Economics, , vol. 30(5), pages 1189-1215, August.
  52. Hoxha, Julian & Çodur, Muhammed Yasin & Mustafaraj, Enea & Kanj, Hassan & El Masri, Ali, 2023. "Prediction of transportation energy demand in Türkiye using stacking ensemble models: Methodology and comparative analysis," Applied Energy, Elsevier, vol. 350(C).
  53. Lydia Simon & Jost Adler, 2022. "Worth the effort? Comparison of different MCMC algorithms for estimating the Pareto/NBD model," Journal of Business Economics, Springer, vol. 92(4), pages 707-733, May.
  54. Karol Pilot & Alicja Ganczarek-Gamrot & Krzysztof Kania, 2024. "Dealing with Anomalies in Day-Ahead Market Prediction Using Machine Learning Hybrid Model," Energies, MDPI, vol. 17(17), pages 1-20, September.
  55. Dong-Her Shih & Ting-Wei Wu & Ming-Hung Shih & Min-Jui Yang & David C. Yen, 2022. "A Novel βSA Ensemble Model for Forecasting the Number of Confirmed COVID-19 Cases in the US," Mathematics, MDPI, vol. 10(5), pages 1-15, March.
  56. Claire Y. T. Chen & Edward W. Sun & Ming-Feng Chang & Yi-Bing Lin, 2024. "Enhancing travel time prediction with deep learning on chronological and retrospective time order information of big traffic data," Annals of Operations Research, Springer, vol. 343(3), pages 1095-1128, December.
  57. Hu, Xincheng & Banks, Jonathan & Guo, Yunting & Huang, Guangping & Liu, Wei Victor, 2021. "Effects of temperature-dependent property variations on the output capacity prediction of a deep coaxial borehole heat exchanger," Renewable Energy, Elsevier, vol. 165(P1), pages 334-349.
  58. Darko B. Vukovic & Lubov Spitsina & Ekaterina Gribanova & Vladislav Spitsin & Ivan Lyzin, 2023. "Predicting the Performance of Retail Market Firms: Regression and Machine Learning Methods," Mathematics, MDPI, vol. 11(8), pages 1-23, April.
  59. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
  60. Hämäläinen, Henri & Ruusunen, Mika, 2022. "Identification of a supercritical fluid extraction process for modelling the energy consumption," Energy, Elsevier, vol. 252(C).
  61. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
  62. Ahmed Gowida & Tamer Moussa & Salaheldin Elkatatny & Abdulwahab Ali, 2019. "A Hybrid Artificial Intelligence Model to Predict the Elastic Behavior of Sandstone Rocks," Sustainability, MDPI, vol. 11(19), pages 1-22, September.
  63. Indy Man Kit Ho & Anthony Weldon & Jason Tze Ho Yong & Candy Tze Tim Lam & Jaime Sampaio, 2023. "Using Machine Learning Algorithms to Pool Data from Meta-Analysis for the Prediction of Countermovement Jump Improvement," IJERPH, MDPI, vol. 20(10), pages 1-15, May.
  64. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
  65. Eren Bas & Erol Egrioglu & Ufuk Yolcu, 2021. "Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm," Forecasting, MDPI, vol. 3(4), pages 1-11, November.
  66. Ducharme, Corey & Agard, Bruno & Trépanier, Martin, 2021. "Forecasting a customer's Next Time Under Safety Stock," International Journal of Production Economics, Elsevier, vol. 234(C).
  67. Yang, Cheng-Hu & Wang, Hai-Tang & Ma, Xin & Talluri, Srinivas, 2023. "A data-driven newsvendor problem: A high-dimensional and mixed-frequency method," International Journal of Production Economics, Elsevier, vol. 266(C).
  68. Apostolos Ampountolas, 2023. "Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models: Evidence from European Financial Markets and Bitcoins," Forecasting, MDPI, vol. 5(2), pages 1-15, June.
  69. González-Sopeña, J.M. & Pakrashi, V. & Ghosh, B., 2021. "An overview of performance evaluation metrics for short-term statistical wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  70. Tascón, Diana C. & Díaz Olariaga, Oscar, 2021. "Air traffic forecast and its impact on runway capacity. A System Dynamics approach," Journal of Air Transport Management, Elsevier, vol. 90(C).
  71. Mohamed Khalil Benzekri & Hatice Şehime Özütler, 2021. "On the Predictability of Bitcoin Price Movements: A Short-term Price Prediction with ARIMA," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 8(2), pages 293-309, July.
  72. Schlaich, Tim & Hoberg, Kai, 2024. "When is the next order? Nowcasting channel inventories with Point-of-Sales data to predict the timing of retail orders," European Journal of Operational Research, Elsevier, vol. 315(1), pages 35-49.
  73. Najla Alemsan & Guilherme Luz Tortorella & Alejandro Francisco Mac Cawley Vergara & Carlos Manuel Taboada Rodriguez & Alberto Portioli Staudacher, 2022. "Implementing a material planning and control method for special nutrition in a Brazilian public hospital," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 202-213, January.
  74. Costa, Guilherme S. & Cota, Wesley & Ferreira, Silvio C., 2022. "Data-driven approach in a compartmental epidemic model to assess undocumented infections," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
  75. Gourav Kumar & Uday Pratap Singh & Sanjeev Jain, 2022. "Swarm Intelligence Based Hybrid Neural Network Approach for Stock Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 991-1039, October.
  76. Apostolos Ampountolas, 2023. "Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models Evidence from European Financial Markets and Bitcoins," Papers 2307.08853, arXiv.org.
  77. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
  78. George P. Papaioannou & Christos Dikaiakos & Anargyros Dramountanis & Panagiotis G. Papaioannou, 2016. "Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoot," Energies, MDPI, vol. 9(8), pages 1-40, August.
  79. Andrea Petroselli & Jacek Florek & Dariusz Młyński & Leszek Książek & Andrzej Wałęga, 2020. "New Insights on Flood Mapping Procedure: Two Case Studies in Poland," Sustainability, MDPI, vol. 12(20), pages 1-17, October.
  80. Karakurt, Izzet & Aydin, Gokhan, 2023. "Development of regression models to forecast the CO2 emissions from fossil fuels in the BRICS and MINT countries," Energy, Elsevier, vol. 263(PA).
  81. Jose Manuel Barrera & Alejandro Reina & Alejandro Maté & Juan Carlos Trujillo, 2020. "Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
  82. Wang, Yi & Gan, Dahua & Sun, Mingyang & Zhang, Ning & Lu, Zongxiang & Kang, Chongqing, 2019. "Probabilistic individual load forecasting using pinball loss guided LSTM," Applied Energy, Elsevier, vol. 235(C), pages 10-20.
  83. Jennifer L. Castle & Jurgen A. Doornik & David Hendry, 2019. "Some forecasting principles from the M4 competition," Economics Papers 2019-W01, Economics Group, Nuffield College, University of Oxford.
  84. Montero-Sousa, Juan Aurelio & Aláiz-Moretón, Héctor & Quintián, Héctor & González-Ayuso, Tomás & Novais, Paulo & Calvo-Rolle, José Luis, 2020. "Hydrogen consumption prediction of a fuel cell based system with a hybrid intelligent approach," Energy, Elsevier, vol. 205(C).
  85. Karime Chahuán-Jiménez, 2024. "Neural Network-Based Predictive Models for Stock Market Index Forecasting," JRFM, MDPI, vol. 17(6), pages 1-18, June.
  86. Ke Xu & Junli Zhang & Junhao Huang & Hongbo Tan & Xiuli Jing & Tianxiang Zheng, 2024. "Forecasting Visitor Arrivals at Tourist Attractions: A Time Series Framework with the N-BEATS for Sustainable Tourism," Sustainability, MDPI, vol. 16(18), pages 1-28, September.
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