# Bayesian Network Demand-Forecasting Model Based on Modified Particle Swarm Optimization
## 2 Bayesian Network Model Construction
### Model Prediction Process
In _The Twelfth International Conference on Advanced Engineering Computing and Applications in Sciences_; International Academy, Research and Industry Association (IARIA): Wilmington, NC, USA, 2018. * [10] [PERSON]; [PERSON] A fuzzy seasonal ARIMA model for forecasting. _Fuzzy Set Syst._**2002**, _126_, 367-376. [CrossRef]
* [11] [PERSON]; [PERSON] Modelling tourism demand volatility using a seasonal autoregressive integrated moving average autoregressive conditional heteroscedasticity model for Victoria Falls Rainforest arrivals in Zimbabwe. _JEFS_**2018**, _11_, 1-9. [CrossRef]
* [12] [PERSON]; [PERSON]; [PERSON] Short-term office building elevator energy consumption forecast using SARIMA. _J. Build Perform Simu._**2020**, _13_, 69-78. [CrossRef]
* [13] [PERSON]; [PERSON]; [PERSON] Combining seasonal ARIMA models with computational intelligence techniques for time series forecasting. _Soft Comput._**2012**, _16_, 1091-1105. [CrossRef]
* [14] [PERSON]; [PERSON] A hybrid fuzzy time series forecasting model based on granular computing and bio-inspired optimization approaches. _J. Comput. Sci.-Neth._**2018**, _27_, 370-385. [CrossRef]* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON] Intuitionistic time series fuzzy inference system. _Eng. Appl. Artif. Intel._**2019**, _82_, 175-183. [CrossRef]
* _[PERSON] et al. (2016)_ [PERSON]; [PERSON]; [PERSON] Demand forecasting with four-parameter exponential smoothing. _Int. J. Prod. Econ._**2016**, _181_, 162-173. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON] Random switching exponential smoothing: A new estimation approach. _Int. J. Prod. Econ._**2019**, _211_, 211-220. [CrossRef]
* _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON] Short-term PM2.5 forecasting using exponential smoothing method: A comparative analysis. _Sensors_**2018**, _18_, 3223. [CrossRef] [PubMed]
* _[PERSON] et al. (2023)_ [PERSON]; [PERSON]; [PERSON] Basket data-driven approach for omnichannel demand forecasting. _IJPE_**2023**, _257_, 108748. [CrossRef]
* _[PERSON] et al. (1960)_ [PERSON] Forecasting Sales by Exponentially Weighted Moving Averages. _Manag. Sci._**1960**, \(6\), 324-342. [CrossRef]
* _[PERSON] (1996)_ [PERSON]; [PERSON] Forecasting for items with intermittent demand. _J. Oper. Res. Soc._**1996**, _47_, 113-121. [CrossRef]
* _Croston and Stock Control for Intermittent Demands. _J. Oper. Res. Soc._**1972**, _23_, 289-303. [CrossRef]
* _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON] Dynamic learning and pricing with model misspecification. _Manag. Sci._**2019**, _65_, 4980-5000. [CrossRef]
* _[PERSON] (2020)_ [PERSON]; [PERSON] Model misspecification, Bayesian versus credibility estimation, and Gibbs posteriors. _Scand. Actuar. J_**2020**, _2020_, 634-649. [CrossRef]
* _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON] Model misspecification in approximate Bayesian computation: Consequences and diagnostics. _J. R. Stat. Soc. B._**2020**, _82_, 421-444. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON] A compound-Poisson Bayesian approach for spare parts inventory forecasting. _IJPE_**2021**, _232_, 107954. [CrossRef]
* _[PERSON] et al. (2012)_ [PERSON]; [PERSON]; [PERSON] Forecasting the intermittent demand for slow-moving inventories: A modelling approach. _Int. J. Forecast._**2012**, _28_, 485-496. [CrossRef]
* _[PERSON] (2014)_ [PERSON] Effective Bayesian Modeling of Groups of Related Count Time Series. In Proceedings of the 31 st International Conference on Machine Learning, Beijing, China, 21-26 June 2014. * _[PERSON] et al. (2019)_ [PERSON]; [PERSON]; [PERSON] Bayesian functional forecasting with locally-autoregressive dependent processes. _Bayesian Anal._**2019**, _14_, 1121-1141. [CrossRef]
* _[PERSON] et al. (2022)_ [PERSON]; [PERSON]; [PERSON] An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control. _Eur. J. Oper. Res._**2022**, _303_, 255-272. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON] [PERSON]; [PERSON] A model for port throughput forecasting using Bayesian estimation.