Another look at measures of forecast accuracy

Cited by (1,003)

Items 101–200 of 1,003

1. Design of an automatic apple sorting system using machine vision
   Mehmet Mahir Sofu, O. Er, Mehmet Cengiz Kayacan, Bayram Çetişli · 2016 · Computers and Electronics in Agriculture
2. Hybrid methodologies for electricity load forecasting: Entropy-based feature selection with machine learning and soft computing techniques
   Sergio Jurado, Àngela Nebot B, Francisco Mugica, Narcís Avellana · 2015 · Energy
3. Performance evaluation of low-cost air quality sensors: A review
   Ye Kang, Lu Aye, Tuan Ngo, Jin Zhi Zhou · 2021 · The Science of The Total Environment
4. Short-term load forecasting in smart grid: A combined CNN and K-means clustering approach
   Xishuang Dong, Lijun Qian, Lei Huang · 2017 · IEEE International Conference on Big Data and Smart Computing (BigComp)
5. A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods
   Jesse Thé, Hesheng Yu · 2017 · Energy
6. Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts
   Andrey Davydenko, Robert A. Fildes · 2013 · International Journal of Forecasting
7. Applying artificial neural networks (ANNs) to solve solid waste-related issues: A critical review
   Ankun Xu, Huimin Chang, Yingjie Xu, Rong Li, Xiang Li, Yan Zhao · 2021 · Waste Management
8. A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm
   Wai Keung Wong, Zhaolu Guo · 2010 · International Journal of Production Economics
9. On the accuracy of the Head Impact Telemetry (HIT) System used in football helmets
   Ron Jadischke, David C. Viano, Nathan Z. Dau, Albert I. King, Joe McCarthy · 2013 · Journal of Biomechanics
10. Improving forecasting by estimating time series structural components across multiple frequencies
    Nikolaos Kourentzes, Fotios Petropoulos, Juan R. Trapero · 2014 · International Journal of Forecasting
11. Studying the relationship between economic growth, CO2 emissions, and the environmental Kuznets curve in Venezuela (1980–2025)
    Andrés Robalino-López, Ángel Isidro Mena Nieto, J. E. García-Ramos, Antonio Aníbal Golpe · 2014 · Renewable and Sustainable Energy Reviews
12. Prevalence and number of children living in institutional care: global, regional, and country estimates
    Desmond, Chris, Watt, Kathryn, Saha, Anamika, Huang, Jialin, Lu, Chunling · 2020 · The Lancet Child & Adolescent Health
13. Toward Automatic Time-Series Forecasting Using Neural Networks
    Weizhong Yan · 2012 · IEEE Transactions on Neural Networks and Learning Systems
14. Machine learning for ecosystem services
    Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad, Stefano Balbi, Alessia Marzo, Carlo Prato, Saverio Sciandrello, Giovanni Signorello, Brian Voigt et al. · 2018 · Ecosystem Services
15. An overview of performance evaluation metrics for short-term statistical wind power forecasting
    Juan Manuel González Sopeña, Vikram Pakrashi, Bidisha Ghosh · 2020 · Renewable and Sustainable Energy Reviews
16. Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic
    Yi Luo, Xiaowei Xu · 2021 · International Journal of Hospitality Management
17. A novel hybrid surrogate intelligent model for creep index prediction based on particle swarm optimization and random forest
    Pin Zhang, Zhen‐Yu Yin, Yin‐Fu Jin, Tommy H.T. Chan · 2019 · Engineering Geology
18. Daily retail demand forecasting using machine learning with emphasis on calendric special days
    Jakob Huber, Heiner Stuckenschmidt · 2020 · International Journal of Forecasting
19. Metrics for evaluating the performance of machine learning based automated valuation models
    Miriam Steurer, Robert Hill, Norbert Pfeifer · 2021 · Journal of Property Research
20. Super ensemble learning for daily streamflow forecasting: large-scale demonstration and comparison with multiple machine learning algorithms
    Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis · 2020 · Neural Computing and Applications
21. Prediction of permeability and unconfined compressive strength of pervious concrete using evolved support vector regression
    Junbo Sun, Junfei Zhang, Yunfan Gu, Yimiao Huang, Yuantian Sun, Guowei Ma · 2019 · Construction and Building Materials
22. A review of predictive uncertainty estimation with machine learning
    Hristos Tyralis, Georgia Papacharalampous · 2024 · Artificial Intelligence Review
23. Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information
    Shaohui Ma, Robert A. Fildes, Tao Huang · 2015 · European Journal of Operational Research
24. Multi-step short-term wind speed forecasting approach based on multi-scale dominant ingredient chaotic analysis, improved hybrid GWO-SCA optimization and ELM
    Wenlong Fu, Kai Wang, Chaoshun Li, Jiawen Tan · 2019 · Energy Conversion and Management
25. Demand Forecasting with Supply‐Chain Information and Machine Learning: Evidence in the Pharmaceutical Industry
    Xiaodan Zhu, Anh Ninh, Hui Zhao, Zhenming Liu · 2021 · Production and Operations Management
26. A methodology for applying k-nearest neighbor to time series forecasting
    Francisco Martínez, María Pilar Frías, María Dolores Pérez-Godoy, Antonio J. Rivera · 2017 · Artificial Intelligence Review
27. Improving the accuracy of global forecasting models using time series data augmentation
    Kasun Bandara, Hansika Hewamalage, Yuanhao Liu, Yanfei Kang, Christoph Bergmeir · 2021 · Pattern Recognition
28. An optimum multi-level image thresholding segmentation using non-local means 2D histogram and exponential Kbest gravitational search algorithm
    Himanshu Mittal, Mukesh Saraswat · 2018 · Engineering Applications of Artificial Intelligence
29. Bibliometric overview of the Technological Forecasting and Social Change journal: Analysis from 1970 to 2018
    Shiwangi Singh, Sanjay Dhir, Vellupillai Mukunda Das, Anuj Sharma · 2020 · Technological Forecasting and Social Change
30. To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)
    Patrick Omoumi, Alexis Ducarouge, Antoine Tournier, Hugh Harvey, Charles E. Kahn, Fanny Louvet-de Verchère, Daniel Pinto dos Santos, Tobias Kober, Jonas Richiardi · 2021 · European Radiology
31. Automatically detecting pig position and posture by 2D camera imaging and deep learning
    Martin Riekert, Achim Klein, Felix Adrion, Christa Hoffmann, Eva Gallmann · 2020 · Computers and Electronics in Agriculture
32. Comparative study of machine learning methods for COVID-19 transmission forecasting
    Abdelkader Dairi, Fouzi Harrou, Abdelhafid Zeroual, Mohamad Mazen Hittawe, Ying Sun · 2021 · Journal of Biomedical Informatics
33. Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices
    Tao Xiong, Yukun Bao, Zhongyi Hu · 2013 · Energy Economics
34. Real-Time Control based on NARX Neural Network of Hexarotor UAV with Load Transporting System for Path Tracking
    Aytaç Altan, Özgür Aslan, Rıfat Hacıoğlu · 2018 · International Conference on Control, Engineering & Information Technology
35. Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques
    Samiul Islam, Saman Hassanzadeh Amin · 2020 · Journal Of Big Data
36. Judgmental selection of forecasting models
    Fotios Petropoulos, Nikolaos Kourentzes, Konstantinos I. Nikolopoulos, Enno Siemsen · 2018 · Journal of Operations Management
37. Image Analysis and Computer Vision Applications in Animal Sciences: An Overview
    Arthur Fernandes, J.R.R. Dórea, Guilherme J. M. Rosa · 2020 · Frontiers in Veterinary Science
38. SSIM—A Deep Learning Approach for Recovering Missing Time Series Sensor Data
    Yifan Zhang, Peter J. Thorburn, Wei Xiang, Peter Fitch · 2019 · IEEE Internet of Things Journal
39. Electric power demand forecasting using interval time series: A comparison between VAR and iMLP
    Carolina García-Ascanio, Carlos G. Maté · 2009 · Energy Policy
40. Probabilistic forecasting of electricity consumption, photovoltaic power generation and net demand of an individual building using Gaussian Processes
    D.W. van der Meer, Mahmoud Shepero, Andreas Svensson, Joakim Widén, Joakim Munkhammar · 2018 · Applied Energy
41. The comparison of Holt–Winters method and Multiple regression method: A case study
    Liljana Ferbar Tratar, Ervin Strmčnik · 2016 · Energy
42. Exploring the sources of uncertainty: Why does bagging for time series forecasting work?
    Fotios Petropoulos, Rob J. Hyndman, Christoph Bergmeir · 2018 · European Journal of Operational Research
43. A Two-Staged SEM-Artificial Neural Network Approach to Analyze the Impact of FinTech Adoption on the Sustainability Performance of Banking Firms: The Mediating Effect of Green Finance and Innovation
    Chen Yan, Abu Bakkar Siddik, Yong Li, Qianli Dong, Guang-Wen Zheng, Md Nafizur Rahman · 2022 · Systems
44. Artificial intelligence and machine learning applications in biopharmaceutical manufacturing
    Anurag Singh Rathore, Saxena Nikita, Garima Thakur, Somesh Mishra · 2022 · Trends in biotechnology
45. Du-Bus: A Realtime Bus Waiting Time Estimation System Based On Multi-Source Data
    Yuecheng Rong, Zhimian Xu, Jun Liu, Hao Liu, Jian Ding, Xuanyu Liu, Wei Luo, Chuanming Zhang, Jiaxiang Gao · 2022 · IEEE Transactions on Intelligent Transportation Systems
46. A Survey on Data Mining Techniques Applied to Electricity-Related Time Series Forecasting
    Francisco Martinez Alvarez, Alicia Troncoso, Gualberto Asencio Cortés, José C. Riquelme · 2015 · Energies
47. Visualising forecasting algorithm performance using time series instance spaces
    Yanfei Kang, Rob J. Hyndman, Kate Smith‐Miles · 2017 · International Journal of Forecasting
48. A new error measure for forecasts of household-level, high resolution electrical energy consumption
    Stephen Haben, Jonathan Ward, Danica Vukadinović Greetham, Colin Singleton, Peter Grindrod · 2013 · International Journal of Forecasting
49. Compressive strength prediction of basalt fiber reinforced concrete via random forest algorithm
    Hong Li, Jiajian Lin, Xiaobao Lei, Tianxia Wei · 2022 · Materials Today Communications
50. Evaluating predictive count data distributions in retail sales forecasting
    S. Kolassa · 2016 · International Journal of Forecasting
51. Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions
    Halit Apaydın, Mohammad Taghi Sattari, Kambiz Falsafian, Ramendra Prasad · 2021 · Journal of Hydrology
52. An aggregate–disaggregate intermittent demand approach (ADIDA) to forecasting: an empirical proposition and analysis
    Konstantinos I. Nikolopoulos, Aris A Syntetos, John E. Boylan, Fotios Petropoulos, Vassilios Assimakopoulos · 2010 · Journal of the Operational Research Society
53. Combination of long term and short term forecasts, with application to tourism demand forecasting
    Robert R. Andrawis, Amir F. Atiya, Hisham El‐Shishiny · 2010 · International Journal of Forecasting
54. Characterization and prediction of deep learning workloads in large-scale GPU datacenters
    Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang · 2021 · International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
55. Short-Term Load Forecasting with Neural Network Ensembles: A Comparative Study [Application Notes]
    Matteo De Felice, Xin Yao · 2011 · IEEE Computational Intelligence Magazine
56. A data-driven newsvendor problem: From data to decision
    Jakob Huber, Sebastian Müller, Moritz Fleischmann, Heiner Stuckenschmidt · 2019 · European Journal of Operational Research
57. Weighted Broad Learning System and Its Application in Nonlinear Industrial Process Modeling
    Fei Chu, Tao Liang, C. L. Philip Chen, Xuesong Wang, Xiaoping Ma · 2019 · IEEE Transactions on Neural Networks and Learning Systems
58. Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes
    Georgia Papacharalampous, Hristos Tyralis, Demetris Koutsoyiannis · 2018 · Stochastic Environmental Research and Risk Assessment
59. Chemometric classification and quantification of olive oil in blends with any edible vegetable oils using FTIR-ATR and Raman spectroscopy
    Ana María Jiménez-Carvelo, María Teresa Osorio, Anastasios Koidis, Antonio González‐Casado, Luis Cuadros-Rodrı́guez · 2017 · LWT
60. Forest Fire Risk Prediction: A Spatial Deep Neural Network-Based Framework
    Mohsen Naderpour, Hossein Mojaddadi Rizeei, Fahimeh Ramezani · 2021 · Remote Sensing
61. On Accurate and Reliable Anomaly Detection for Gas Turbine Combustors: A Deep Learning Approach
    Weizhong Yan, Lijie Yu · 2015 · Annual Conference of the PHM Society
62. The human factor in supply chain forecasting: A systematic review
    H. Niles Perera, Jason Hurley, Behnam Fahimnia, Mohsen Reisi · 2018 · European Journal of Operational Research
63. A guideline to solar forecasting research practice: Reproducible, operational, probabilistic or physically-based, ensemble, and skill (ROPES)
    Dazhi Yang · 2019 · Journal of Renewable and Sustainable Energy
64. Forecasting in social settings: The state of the art
    Spyros Makridakis, Rob J. Hyndman, Fotios Petropoulos · 2019 · International Journal of Forecasting
65. CORDIC-SNN: On-FPGA STDP Learning With Izhikevich Neurons
    Moslem Heidarpur, Arash Ahmadi, Majid Ahmadi, Mostafa Rahimi Azghadi · 2019 · IEEE Transactions on Circuits and Systems I Regular Papers
66. Non-linear numerical modeling and experimental testing of a point absorber wave energy converter
    Andrew Stephen Zurkinden, Francesco Ferri, Scott J. Beatty, Jens Peter Kofoed, Morten Kramer · 2014 · Ocean Engineering
67. Forecasting Demand Flexibility of Aggregated Residential Load Using Smart Meter Data
    Jelena Ponoćko, Jovica V. Milanović · 2018 · IEEE Transactions on Power Systems
68. ANCFIS: A Neurofuzzy Architecture Employing Complex Fuzzy Sets
    Zhifei Chen, Sara Aghakhani, James Man, Scott Dick · 2010 · IEEE Transactions on Fuzzy Systems
69. Multi-zone indoor temperature prediction with LSTM-based sequence to sequence model
    Zhen Fang, Nicolas Crimier, Lisa Scanu, Alphanie Midelet, Amr Alzouhri Alyafi, Benoit DELINCHANT · 2021 · Energy and Buildings
70. A note on the Mean Absolute Scaled Error
    Philip Hans Franses · 2015 · International Journal of Forecasting
71. A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
    Catherine Leigh, Omar Alsibai, Rob J. Hyndman, Sevvandi Kandanaarachchi, Olivia C. King, James M. McGree, Catherine Neelamraju, Jennifer Strauss, Priyanga Dilini Talagala, Ryan D. R. Turner et al. · 2019 · The Science of The Total Environment
72. A Hybrid Method for Short-Term Traffic Congestion Forecasting Using Genetic Algorithms and Cross Entropy
    Pedro López-García, Enrique Onieva, Eneko Osaba, Antonio David Masegosa, Asier Perallos · 2015 · IEEE Transactions on Intelligent Transportation Systems
73. On the selection of forecasting accuracy measures
    Diamantis Koutsandreas, Evangelos Spiliotis, Fotios Petropoulos, Vassilios Assimakopoulos · 2021 · Journal of the Operational Research Society
74. A composite framework coupling multiple feature selection, compound prediction models and novel hybrid swarm optimizer-based synchronization optimization strategy for multi-step ahead short-term wind speed forecasting
    Wenlong Fu, Kai Wang, Jiawen Tan, Kai Zhang · 2020 · Energy Conversion and Management
75. AI-based forecasting for optimised solar energy management and smart grid efficiency
    Pierre Bouquet, Ilya Jackson, Mostafa Nick, Amin Kaboli · 2023 · International Journal of Production Research
76. Adaptive modelling and forecasting of offshore wind power fluctuations with Markov‐switching autoregressive models
    Pierre Pinson, Henrik Madsen · 2010 · Journal of Forecasting
77. MAPE-R: a rescaled measure of accuracy for cross-sectional subnational population forecasts
    David A. Swanson, Jeff Tayman, Thomas M. Bryan · 2011 · Journal of Population Research
78. Data-driven building archetypes for urban building energy modelling
    Oleksii Pasichnyi, Jörgen Wallin, Olga Kordas · 2019 · Energy
79. Mixture optimization for environmental, economical and mechanical objectives in silica fume concrete: A novel frame-work based on machine learning and a new meta-heuristic algorithm
    Junfei Zhang, Yimiao Huang, Guowei Ma, Brett Nener · 2021 · Resources Conservation and Recycling
80. Predicting porosity, permeability and water saturation applying an optimized nearest-neighbour, machine-learning and data-mining network of well-log data
    David A. Wood · 2019 · Journal of Petroleum Science and Engineering
81. A hybrid intelligent system for designing optimal proportions of recycled aggregate concrete
    Junfei Zhang, Yimiao Huang, Farhad Aslani, Guowei Ma, Brett Nener · 2020 · Journal of Cleaner Production
82. Statistical, machine learning and deep learning forecasting methods: Comparisons and ways forward
    Spyros Makridakis, Evangelos Spiliotis, Vassilios Assimakopoulos, Artemios-Anargyros Semenoglou, Gary Mulder, Konstantinos I. Nikolopoulos · 2022 · Journal of the Operational Research Society
83. Forecasting the intermittent demand for slow-moving inventories: A modelling approach
    Ralph D. Snyder, J. Keith Ord, Adrian N. Beaumont · 2011 · International Journal of Forecasting
84. A brief history of forecasting competitions
    Rob J. Hyndman · 2019 · International Journal of Forecasting
85. Collaborative QoS prediction with context-sensitive matrix factorization
    Hao Wu, Kun Yue, Bo Li, Binbin Zhang, Ching‐Hsien Hsu · 2017 · Future Generation Computer Systems
86. Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study
    Josh Michael Colston, Tahmeed Ahmed, Tjale Cloupas Mahopo, Gagandeep Kang, Margaret N. Kosek, Francisco de Sousa Junior, Prakash Sunder Shrestha, Erling Svensen, Ali Turab, Benjamin F. Zaitchik · 2018 · Environmental Research
87. Forecasting daily meteorological time series using ARIMA and regression models
    Małgorzata Murat, Iwona Malinowska, Magdalena Gos, Jaromir Krzyszczak · 2018 · International Agrophysics
88. The intrinsic predictability of ecological time series and its potential to guide forecasting
    Frank Pennekamp, Alison C. Iles, Joshua Garland, Georgina L. Brennan, Ulrich Brose, Ursula Gaedke, Ute Jacob, Pavel Kratina, Blake Matthews, Stephan B. Munch et al. · 2019 · Ecological Monographs
89. Intelligent Asset Allocation via Market Sentiment Views
    Frank Xing, Erik Cambria, Roy E. Welsch · 2018 · IEEE Computational Intelligence Magazine
90. Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy
    Gaetano Perone · 2021 · The European Journal of Health Economics
91. Short-term electricity load forecasting—A systematic approach from system level to secondary substations
    Pinheiro, Marco G., Madeira, Sara C., Francisco, Alexandre P. · 2023 · Applied Energy
92. Eliciting improved quantitative judgements using the IDEA protocol: A case study in natural resource management
    Victoria Hemming, Terry V. Walshe, Anca Maria Hanea, Fiona M. Fidler, Mark A. Burgman · 2018 · PLoS ONE
93. Implementing transfer learning across different datasets for time series forecasting
    Rui Ye, Qun Dai · 2020 · Pattern Recognition
94. Decision control and explanations in human-AI collaboration: Improving user perceptions and compliance
    Monika Westphal, Michael Vössing, Gerhard Satzger, Galit B. Yom‐Tov, Anat Rafaeli · 2023 · Computers in Human Behavior
95. Forecasting histogram time series with k-nearest neighbours methods
    Javier Arroyo, Carlos G. Maté · 2008 · International Journal of Forecasting
96. Causal inference for time series analysis: problems, methods and evaluation
    Raha Moraffah, Paras Sheth, Mansooreh Karami, Anchit Bhattacharya, Qianru Wang, Anique Tahir, Adrienne J. Raglin, Huan Liu · 2021 · Knowledge and Information Systems
97. In Validations We Trust? The Impact of Imperfect Human Annotations as a Gold Standard on the Quality of Validation of Automated Content Analysis
    Song, Hyunjin, Tolochko, Petro, Eberl, Jakob-Moritz, Eisele, Olga, Greussing, Esther, Heidenreich, Tobias, Lind, Fabienne, Galyga, Sebastian, Boomgaarden, Hajo G. · 2020 · Political Communication
98. A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks
    Brandon Smith, Nima Pahlevan, John F. Schalles, Steven A. Ruberg, Reagan M. Errera, Ronghua Ma, Claudia Giardino, Mariano Bresciani, Cláudio Clemente Faria Barbosa, Tim Moore et al. · 2021 · Frontiers in Remote Sensing
99. Operational Research: methods and applications
    Fotios Petropoulos, Gilbert Laporte A, Emel Aktaş, Sibel A. Alumur, Claudia Archetti, Hayriye Ayhan, Maria Battarra, Julia A. Bennell, Jean-Marie Bourjolly, John E. Boylan et al. · 2023 · Journal of the Operational Research Society
100. Machine Learning Application in Reservoir Water Level Forecasting for Sustainable Hydropower Generation Strategy
     Michelle Sapitang, Wanie M. Ridwan, Khairul Faizal Kushiar, Ali Najah Ahmed, Ahmed El‐Shafie · 2020 · Sustainability