{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T04:51:31Z","timestamp":1777956691867,"version":"3.51.4"},"reference-count":89,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Industrial Engineering"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.cie.2026.111977","type":"journal-article","created":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T15:48:32Z","timestamp":1774194512000},"page":"111977","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A three-stage algorithm for E-grocery demand forecasting using metaheuristic-driven high-order fuzzy cognitive maps and fractional brownian motion"],"prefix":"10.1016","volume":"216","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6107-7699","authenticated-orcid":false,"given":"Ali","family":"Nikseresht","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7370-4760","authenticated-orcid":false,"given":"Mohammad","family":"Shokouhifar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3040-1801","authenticated-orcid":false,"given":"Mehdi","family":"Hosseinzadeh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alireza","family":"Goli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank","family":"Werner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"11","key":"10.1016\/j.cie.2026.111977_b0005","article-title":"Measuring and mitigating the costs of stockouts","volume":"52","author":"Andersen","year":"2006","journal-title":"Management Science"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0010","doi-asserted-by":"crossref","DOI":"10.1287\/mksc.17.4.406","article-title":"Estimation of consumer demand with stock-out based substitution: An application to vending machine products","volume":"17","author":"Anupindi","year":"1998","journal-title":"Marketing Science"},{"key":"10.1016\/j.cie.2026.111977_b0015","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018","journal-title":"ArXiv"},{"key":"10.1016\/j.cie.2026.111977_b0020","article-title":"Decoupling the short- and long-term behavior of stochastic volatility","author":"Bennedsen","year":"2021","journal-title":"Journal of Financial Econometrics"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0025","doi-asserted-by":"crossref","DOI":"10.1007\/s11518-015-5270-4","article-title":"Warranty strategy in a supply chain when two retailer\u2019s extended warranties bundled with the products","volume":"24","author":"Bian","year":"2015","journal-title":"Journal of Systems Science and Systems Engineering"},{"key":"10.1016\/j.cie.2026.111977_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2020.116061","article-title":"Short-term CO2 emissions forecasting based on decomposition approaches and its impact on electricity market scheduling","volume":"281","author":"Bokde","year":"2021","journal-title":"Applied Energy"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.jeconom.2015.10.007","article-title":"Exploiting the errors: A simple approach for improved volatility forecasting","volume":"192","author":"Bollerslev","year":"2016","journal-title":"Journal of Econometrics"},{"issue":"12","key":"10.1016\/j.cie.2026.111977_b0040","doi-asserted-by":"crossref","first-page":"1694","DOI":"10.14778\/3137765.3137775","article-title":"Probabilistic demand forecasting at scale","volume":"10","author":"B\u00f6se","year":"2017","journal-title":"Proceedings of the VLDB Endowment"},{"key":"10.1016\/j.cie.2026.111977_b0045","series-title":"Proceedings of the IEEE Conference on Decision and Control","article-title":"On the existence and uniqueness of solutions for the concept values in fuzzy cognitive maps","author":"Boutalis","year":"2008"},{"key":"10.1016\/j.cie.2026.111977_b0050","doi-asserted-by":"crossref","DOI":"10.1109\/TFUZZ.2009.2017519","article-title":"Adaptive estimation of fuzzy cognitive maps with proven stability and parameter convergence","author":"Boutalis","year":"2009","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.cie.2026.111977_b0055","article-title":"The impact of COVID-19 pandemic restrictions on offline and online grocery shopping: New normal or old habits?","author":"Br\u00fcggemann","year":"2022","journal-title":"Electronic Commerce Research"},{"key":"10.1016\/j.cie.2026.111977_b0060","doi-asserted-by":"crossref","DOI":"10.1214\/EJP.v8-125","article-title":"Fractional ornstein-uhlenbeck processes","volume":"8","author":"Cheridito","year":"2003","journal-title":"Electronic Journal of Probability"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0065","doi-asserted-by":"crossref","DOI":"10.1111\/1467-9965.00057","article-title":"Long memory in continuous-time stochastic volatility models","volume":"8","author":"Comte","year":"1998","journal-title":"Mathematical Finance"},{"key":"10.1016\/j.cie.2026.111977_b0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.apenergy.2019.03.163","article-title":"Intelligent load pattern modeling and denoising using improved variational mode decomposition for various calendar periods","volume":"247","author":"Cui","year":"2019","journal-title":"Applied Energy"},{"key":"10.1016\/j.cie.2026.111977_b0075","article-title":"Gate-variants of Gated Recurrent Unit (GRU) neural networks","author":"Dey","year":"2017","journal-title":"Midwest Symposium on Circuits and Systems"},{"key":"10.1016\/j.cie.2026.111977_b0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2023.128256","article-title":"A comprehensive review of machine learning and IoT solutions for demand side energy management, conservation, and resilient operation","volume":"281","author":"Elsisi","year":"2023","journal-title":"Energy"},{"issue":"2","key":"10.1016\/j.cie.2026.111977_b0085","doi-asserted-by":"crossref","DOI":"10.1109\/TSG.2019.2937338","article-title":"Reinforced deterministic and probabilistic load forecasting via q -learning dynamic model selection","volume":"11","author":"Feng","year":"2020","journal-title":"IEEE Transactions on Smart Grid"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0090","article-title":"Retail forecasting: Research and practice","volume":"38","author":"Fildes","year":"2022","journal-title":"International Journal of Forecasting"},{"key":"10.1016\/j.cie.2026.111977_b0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2020.103978","article-title":"Robust empirical wavelet fuzzy cognitive map for time series forecasting","volume":"96","author":"Gao","year":"2020","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"6","key":"10.1016\/j.cie.2026.111977_b0100","doi-asserted-by":"crossref","DOI":"10.1080\/14697688.2017.1393551","article-title":"Volatility is rough","volume":"18","author":"Gatheral","year":"2018","journal-title":"Quantitative Finance"},{"key":"10.1016\/j.cie.2026.111977_b0105","doi-asserted-by":"crossref","DOI":"10.1109\/72.728396","article-title":"ScaleNet - Multiscale neural-network architecture for time series prediction","author":"Geva","year":"1998","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10.1016\/j.cie.2026.111977_b0110","doi-asserted-by":"crossref","DOI":"10.1109\/TSP.2013.2265222","article-title":"Empirical wavelet transform","author":"Gilles","year":"2013","journal-title":"IEEE Transactions on Signal Processing"},{"key":"10.1016\/j.cie.2026.111977_b0115","article-title":"Multiscale transforms for filtering financial data streams","author":"Gonghui","year":"1999","journal-title":"Journal of Computational Intelligence Finance."},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0120","doi-asserted-by":"crossref","DOI":"10.3390\/jtaer17030050","article-title":"Online grocery shopping in Germany: Assessing the impact of COVID-19","volume":"17","author":"Gruntkowski","year":"2022","journal-title":"Journal of Theoretical and Applied Electronic Commerce Research"},{"issue":"6","key":"10.1016\/j.cie.2026.111977_b0125","doi-asserted-by":"crossref","DOI":"10.1002\/jae.2347","article-title":"Smooth quantile-based modeling of brand sales, price and promotional effects from retail scanner panels","volume":"29","author":"Haupt","year":"2014","journal-title":"Journal of Applied Econometrics"},{"key":"10.1016\/j.cie.2026.111977_b0130","article-title":"Online customer engagement in the post-pandemic scenario: A hybrid thematic analysis of the luxury fashion industry","author":"Hoang","year":"2022","journal-title":"Electronic Commerce Research"},{"key":"10.1016\/j.cie.2026.111977_b0135","doi-asserted-by":"crossref","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","author":"Hochreiter","year":"1997","journal-title":"Neural Computation"},{"key":"10.1016\/j.cie.2026.111977_b0140","series-title":"Generalized additive models for location, scale and shape for program evaluation: A guide to practice","author":"Hohberg","year":"2018"},{"key":"10.1016\/j.cie.2026.111977_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2016.07.030","article-title":"An agent-based fuzzy constraint-directed negotiation model for solving supply chain planning and scheduling problems","volume":"48","author":"Hsu","year":"2016","journal-title":"Applied Soft Computing Journal"},{"key":"10.1016\/j.cie.2026.111977_b0150","series-title":"SEST 2021\u20134th International Conference on Smart Energy Systems and Technologies","article-title":"A new ensemble reinforcement learning strategy for solar irradiance forecasting using deep optimized convolutional neural network models","author":"Jalali","year":"2021"},{"key":"10.1016\/j.cie.2026.111977_b0155","doi-asserted-by":"crossref","DOI":"10.1109\/21.256541","article-title":"ANFIS: Adaptive-network-based fuzzy inference system","author":"Jang","year":"1993","journal-title":"IEEE Transactions on Systems, Man and Cybernetics."},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0160","doi-asserted-by":"crossref","DOI":"10.1177\/1471082X13494159","article-title":"Beyond mean regression","volume":"13","author":"Kneib","year":"2013","journal-title":"Statistical Modelling"},{"key":"10.1016\/j.cie.2026.111977_b0170","doi-asserted-by":"crossref","DOI":"10.1016\/S0020-7373(86)80040-2","article-title":"Fuzzy cognitive maps","author":"Kosko","year":"1986","journal-title":"International Journal of Man-Machine Studies"},{"key":"10.1016\/j.cie.2026.111977_b0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2023.110772","article-title":"Subpopulation preference adjective non-dominated sorting genetic algorithm for multi-objective capacity expansion for matured fabs","volume":"147","author":"Kuo","year":"2023","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejor.2015.02.047","article-title":"Accommodating heterogeneity and nonlinearity in price effects for predicting brand sales and profits","volume":"246","author":"Lang","year":"2015","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2021.03.012","article-title":"Temporal Fusion Transformers for interpretable multi-horizon time series forecasting","volume":"37","author":"Lim","year":"2021","journal-title":"International Journal of Forecasting"},{"key":"10.1016\/j.cie.2026.111977_b0190","article-title":"Time-series forecasting with deep learning: A survey philosophical transactions of the royal society a: mathematical","volume":"379","author":"Lim","year":"2021","journal-title":"Physical and Engineering Sciences"},{"key":"10.1016\/j.cie.2026.111977_b0195","article-title":"CNN-FCM: System modeling promotes stability of deep learning in time series prediction","author":"Liu","year":"2020","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.cie.2026.111977_b0200","article-title":"A robust time series prediction method based on empirical mode decomposition and high-order fuzzy cognitive maps","author":"Liu","year":"2020","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejor.2015.08.029","article-title":"Demand forecasting with high dimensional data: The case of SKU retail sales forecasting with intra- and inter-category promotional information","volume":"249","author":"Ma","year":"2016","journal-title":"European Journal of Operational Research"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2014.12.004","article-title":"Probabilistic forecasting of electricity spot prices using factor quantile regression averaging","volume":"32","author":"Maciejowska","year":"2016","journal-title":"International Journal of Forecasting"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0215","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2018.06.001","article-title":"The M4 competition: results, findings, conclusion and way forward","volume":"34","author":"Makridakis","year":"2018","journal-title":"International Journal of Forecasting"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2019.04.014","article-title":"The M4 competition: 100,000 time series and 61 forecasting methods","volume":"36","author":"Makridakis","year":"2020","journal-title":"International Journal of Forecasting"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0225","article-title":"M5 accuracy competition: results, findings, and conclusions","volume":"38","author":"Makridakis","year":"2022","journal-title":"International Journal of Forecasting"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0230","doi-asserted-by":"crossref","DOI":"10.1137\/1010093","article-title":"Fractional brownian motions, fractional noises and applications","volume":"10","author":"Mandelbrot","year":"1968","journal-title":"SIAM Review"},{"key":"10.1016\/j.cie.2026.111977_b0235","article-title":"Quantile regression forests","volume":"7","author":"Meinshausen","year":"2006","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.cie.2026.111977_b0240","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","article-title":"Grey wolf optimizer","volume":"69","author":"Mirjalili","year":"2014","journal-title":"Advances in Engineering Software"},{"key":"10.1016\/j.cie.2026.111977_b0245","article-title":"Using empirical wavelet transform and high-order fuzzy cognitive maps for time series forecasting","volume":"109990","author":"Mohammadi","year":"2023","journal-title":"Applied Soft Computing"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2019.02.011","article-title":"FFORMA: feature-based forecast model averaging","volume":"36","author":"Montero-Manso","year":"2020","journal-title":"International Journal of Forecasting"},{"key":"10.1016\/j.cie.2026.111977_bib448","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/13675567.2025.2517639","article-title":"Machine learning and data-driven models in sustainable supply chain management: a systematic literature review with content analysis","author":"Nikseresht","year":"2025","journal-title":"International Journal of Logistics Research and Applications"},{"key":"10.1016\/j.cie.2026.111977_b0255","article-title":"Time series forecasting using improved empirical fourier decomposition and high-order intuitionistic FCM: applications in smart manufacturing systems","volume":"1\u201313","author":"Nikseresht","year":"2024","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.cie.2026.111977_bib447","doi-asserted-by":"crossref","first-page":"122737","DOI":"10.1016\/j.renene.2025.122737","article-title":"Dynamic hydrogen demand forecasting using hybrid time series models: insights for renewable energy systems","volume":"244","author":"Nikseresht","year":"2025","journal-title":"Renew Energy"},{"issue":"12","key":"10.1016\/j.cie.2026.111977_b0265","doi-asserted-by":"crossref","DOI":"10.1007\/s00477-023-02539-5","article-title":"Hourly solar irradiance forecasting based on statistical methods and a stochastic modeling approach for residual error compensation","volume":"37","author":"Nikseresht","year":"2023","journal-title":"Stochastic Environmental Research and Risk Assessment"},{"key":"10.1016\/j.cie.2026.111977_b0270","article-title":"Proactive product warranty service planning and control: Unravelling the boons of customer-generated content and multi-frequency analyses","volume":"1\u201328","author":"Nikseresht","year":"2024","journal-title":"Production Planning and Control"},{"key":"10.1016\/j.cie.2026.111977_b0275","unstructured":"Oreshkin, B. N., Carpov, D., Chapados, N., & Bengio, Y. (2020). N-BEATS: NEURAL BASIS EXPANSION ANALYSIS FOR INTERPRETABLE TIME SERIES FORECASTING. 8th International Conference on Learning Representations, ICLR 2020."},{"key":"10.1016\/j.cie.2026.111977_b0280","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.111719","article-title":"Integrating reinforcement learning and metaheuristics for safe and sustainable health tourist trip design problem","volume":"161","author":"Pitakaso","year":"2024","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.cie.2026.111977_b0285","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.109586","article-title":"Wind power forecasting based on variational mode decomposition and high-order fuzzy cognitive maps","volume":"129","author":"Qiao","year":"2022","journal-title":"Applied Soft Computing"},{"issue":"4","key":"10.1016\/j.cie.2026.111977_b0290","doi-asserted-by":"crossref","DOI":"10.1504\/EJIE.2008.018441","article-title":"On the choice of a demand distribution for inventory management models","volume":"2","author":"Ramaekers","year":"2008","journal-title":"European Journal of Industrial Engineering"},{"key":"10.1016\/j.cie.2026.111977_b0295","doi-asserted-by":"crossref","DOI":"10.1109\/TSMCB.2005.850182","article-title":"Wavelet-based combined signal filtering and prediction","author":"Renaud","year":"2005","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics."},{"issue":"8","key":"10.1016\/j.cie.2026.111977_b0300","doi-asserted-by":"crossref","DOI":"10.1016\/j.spa.2007.09.004","article-title":"Estimation of the volatility persistence in a discretely observed diffusion model","volume":"118","author":"Rosenbaum","year":"2008","journal-title":"Stochastic Processes and Their Applications"},{"key":"10.1016\/j.cie.2026.111977_b0305","series-title":"Cognitive Science","article-title":"Learning internal representations error propagation","author":"Ruineihart","year":"1986"},{"key":"10.1016\/j.cie.2026.111977_b0310","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijpe.2013.04.039","article-title":"The data-driven newsvendor with censored demand observations","volume":"149","author":"Sachs","year":"2014","journal-title":"International Journal of Production Economics"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0315","doi-asserted-by":"crossref","DOI":"10.1016\/j.ijforecast.2019.07.001","article-title":"DeepAR: Probabilistic forecasting with autoregressive recurrent networks","volume":"36","author":"Salinas","year":"2020","journal-title":"International Journal of Forecasting"},{"key":"10.1016\/j.cie.2026.111977_b0320","series-title":"2019 IEEE 9th International Conference on System Engineering and Technology","article-title":"A review paper on implementing reinforcement learning technique in optimising games performance","author":"Samsuden","year":"2019"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0325","doi-asserted-by":"crossref","DOI":"10.1002\/joom.1071","article-title":"Using transactions data to improve consumer returns forecasting","volume":"66","author":"Shang","year":"2020","journal-title":"Journal of Operations Management"},{"issue":"8","key":"10.1016\/j.cie.2026.111977_b0330","doi-asserted-by":"crossref","DOI":"10.1109\/TFUZZ.2020.2998513","article-title":"Multivariate time series forecasting based on elastic net and high-order fuzzy cognitive maps: A case study on human action prediction through EEG signals","volume":"29","author":"Shen","year":"2021","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.cie.2026.111977_b0335","doi-asserted-by":"crossref","DOI":"10.1016\/j.techfore.2022.121861","article-title":"The role of social factors in purchase journey in the social commerce era","volume":"183","author":"Shirazi","year":"2022","journal-title":"Technological Forecasting and Social Change"},{"key":"10.1016\/j.cie.2026.111977_b0340","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2021.108010","article-title":"Promoting a novel method for warranty claim prediction based on social network data","volume":"216","author":"Shokouhyar","year":"2021","journal-title":"Reliability Engineering and System Safety"},{"issue":"7587","key":"10.1016\/j.cie.2026.111977_b0345","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/nature16961","article-title":"Mastering the game of go with deep neural networks and tree search","volume":"529","author":"Silver","year":"2016","journal-title":"Nature"},{"key":"10.1016\/j.cie.2026.111977_b0350","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2019.124299","article-title":"A comprehensive comparison of four input variable selection methods for artificial neural network flow forecasting models","volume":"583","author":"Snieder","year":"2020","journal-title":"Journal of Hydrology"},{"key":"10.1016\/j.cie.2026.111977_b0355","series-title":"Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS","article-title":"Higher-order fuzzy cognitive maps","author":"Stach","year":"2006"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0360","doi-asserted-by":"crossref","DOI":"10.1007\/s10660-022-09661-6","article-title":"Configuring managerial factors to enhance omnichannel experience and customer engagement behaviors for a solid loyalty loop","volume":"23","author":"Suh","year":"2023","journal-title":"Electronic Commerce Research"},{"key":"10.1016\/j.cie.2026.111977_b0365","doi-asserted-by":"crossref","DOI":"10.1016\/j.renene.2019.11.145","article-title":"Multi-distribution ensemble probabilistic wind power forecasting","volume":"148","author":"Sun","year":"2020","journal-title":"Renewable Energy"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0370","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejor.2006.02.006","article-title":"Forecasting daily supermarket sales using exponentially weighted quantile regression","volume":"178","author":"Taylor","year":"2007","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.cie.2026.111977_b0375","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112038","article-title":"Multi-objective multi-population simplified swarm optimization for container loading optimization with practical constraints","volume":"165","author":"Truong","year":"2024","journal-title":"Applied Soft Computing"},{"issue":"3","key":"10.1016\/j.cie.2026.111977_b0380","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejor.2019.11.029","article-title":"Distributional regression for demand forecasting in e-grocery","volume":"294","author":"Ulrich","year":"2021","journal-title":"European Journal of Operational Research"},{"issue":"6","key":"10.1016\/j.cie.2026.111977_b0385","doi-asserted-by":"crossref","DOI":"10.1080\/17517575.2018.1450998","article-title":"Big data driven cycle time parallel prediction for production planning in wafer manufacturing","volume":"12","author":"Wang","year":"2018","journal-title":"Enterprise Information Systems"},{"issue":"2","key":"10.1016\/j.cie.2026.111977_b0390","doi-asserted-by":"crossref","DOI":"10.1007\/s00291-016-0459-6","article-title":"A comparison of semiparametric and heterogeneous store sales models for optimal category pricing","volume":"39","author":"Weber","year":"2017","journal-title":"OR Spectrum"},{"key":"10.1016\/j.cie.2026.111977_b0395","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2016.09.010","article-title":"Robust learning of large-scale fuzzy cognitive maps via the lasso from noisy time series","author":"Wu","year":"2016","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.cie.2026.111977_b0400","doi-asserted-by":"crossref","DOI":"10.1109\/TFUZZ.2017.2741444","article-title":"Learning large-scale fuzzy cognitive maps based on compressed sensing and application in reconstructing gene regulatory networks","author":"Wu","year":"2017","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.cie.2026.111977_b0405","article-title":"Time series prediction using sparse autoencoder and high-order fuzzy cognitive maps","author":"Wu","year":"2020","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"10.1016\/j.cie.2026.111977_b0410","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2012.12.021","article-title":"A review on coarse warranty data and analysis","volume":"114","author":"Wu","year":"2013","journal-title":"Reliability Engineering and System Safety"},{"issue":"1","key":"10.1016\/j.cie.2026.111977_b0415","doi-asserted-by":"crossref","DOI":"10.1007\/s00500-021-06455-0","article-title":"Time series prediction based on high-order intuitionistic fuzzy cognitive maps with variational mode decomposition","volume":"26","author":"Xixi","year":"2022","journal-title":"Soft Computing"},{"key":"10.1016\/j.cie.2026.111977_b0420","doi-asserted-by":"crossref","DOI":"10.1109\/TFUZZ.2018.2831640","article-title":"Time-series forecasting based on high-order fuzzy cognitive maps and wavelet transform","author":"Yang","year":"2018","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"9","key":"10.1016\/j.cie.2026.111977_b0425","doi-asserted-by":"crossref","DOI":"10.1080\/17517575.2020.1739343","article-title":"Analysing and forecasting the security in supply-demand management of chinese forestry enterprises by linear weighted method and artificial neural network","volume":"15","author":"Zhao","year":"2021","journal-title":"Enterprise Information Systems"},{"key":"10.1016\/j.cie.2026.111977_b0430","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2021.108155","article-title":"Empirical Fourier decomposition: an accurate signal decomposition method for nonlinear and non-stationary time series analysis","volume":"163","author":"Zhou","year":"2022","journal-title":"Mechanical Systems and Signal Processing"},{"key":"10.1016\/j.cie.2026.111977_b0435","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2022.111982","article-title":"Short-term wind power prediction optimized by multi-objective dragonfly algorithm based on variational mode decomposition","volume":"157","author":"Zhou","year":"2022","journal-title":"Chaos, Solitons & Fractals"},{"key":"10.1016\/j.cie.2026.111977_b0440","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1016\/j.asoc.2015.07.002","article-title":"A cloud based architecture capable of perceiving and predicting multiple vessel behaviour","volume":"35","author":"Zissis","year":"2015","journal-title":"Applied Soft Computing Journal"},{"key":"10.1016\/j.cie.2026.111977_b0445","doi-asserted-by":"crossref","DOI":"10.1016\/j.jretconser.2022.103010","article-title":"How did COVID-19 change what people buy: evidence from a supermarket chain","volume":"68","author":"Zuokas","year":"2022","journal-title":"Journal of Retailing and Consumer Services"}],"container-title":["Computers & Industrial Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226001786?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0360835226001786?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T03:31:42Z","timestamp":1777951902000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0360835226001786"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":89,"alternative-id":["S0360835226001786"],"URL":"https:\/\/doi.org\/10.1016\/j.cie.2026.111977","relation":{},"ISSN":["0360-8352"],"issn-type":[{"value":"0360-8352","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A three-stage algorithm for E-grocery demand forecasting using metaheuristic-driven high-order fuzzy cognitive maps and fractional brownian motion","name":"articletitle","label":"Article Title"},{"value":"Computers & Industrial Engineering","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cie.2026.111977","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111977"}}