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Demand forecasting application with regression and artificial intelligence methods in a construction machinery company
9 references·2 citing·54 second hop
Demand forecasting application with regression and artificial intelligence methods in a construction machinery company (2021)Demand forecasting application with regre…An optimized model using LSTM network for demand forecasting (2020)An optimized model using LSTM…Demand forecasting in pharmaceutical supply chains: A case study (2019)Demand forecasting in pharmac…Demand Forecasting for Irregular Demands in Business Aircraft Spare Parts Supply Chains by using Artificial Intelligence (AI) (2017)Demand Forecasting for Irregu…Comparison of fuzzy inference system (FIS), FIS with artificial neural networks (FIS + ANN) and FIS with adaptive neuro-fuzzy inference system (FIS + ANFIS) for inventory control (2015)Comparison of fuzzy inference…Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice (2011)Spare parts classification an…A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts (2006)A hybrid support vector machi…Forecasting women's apparel sales using mathematical modeling (2003)Forecasting women's apparel s…Forecasting aggregate retail sales: (2001)Forecasting aggregate retail …A Parametric Approach to Flexible Nonlinear Inference (2001)A Parametric Approach to Flex…Data Analytics in Supply Chain Management: A State-of-the-Art Literature Review (2024)Data Analytics in Supply Chai…Demand forecasting of spare parts with regression and machine learning methods: Application in a bus fleet (2023)Demand forecasting of spare p…Dynamic Version of the Economic Lot Size Model (1958)Production and inventory management (1983)Dynamic Version of the Economic Lot Size Model (2004)Applications of Artificial Intelligence in Supply Chain Management and Logistics: Focusing Onto Recognition for Supply Chain Execution (2019)Prediction of B2C e-commerce order arrival using hybrid autoregressive-adaptive neuro-fuzzy inference system (AR-ANFIS) for managing fluctuation of throughput in e-fulfilment centres (2019)A fuzzy inference based scenario building in two-stage optimization framework for sustainable recycling supply chain redesign (2020)Application of support vector machines in financial time series forecasting (2001)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)Revenue forecasting using a least-squares support vector regression model in a fuzzy environment (2011)Intermittent demand forecasting for spare parts in the heavy-duty vehicle industry: a support vector machine model (2020)Case Study Research: Design and Methods (1984)How to make a decision: The analytic hierarchy process (1990)Qualitative Data Analysis: An Expanded Sourcebook (1994)‘Horses for Courses’ in demand forecasting (2014)Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty (2016)OR in spare parts management: A review (2017)The Utility Analysis of Choices Involving Risk (1948)Business Cycles, Indicators, and Forecasting (1993)The Time-Varying NAIRU and its Implications for Economic Policy (1997)Oil Price Shocks and the Macroeconomy: What Has Been Learned Since 1996 (2004)Environmental Kuznets curve for CO2 in Canada (2010)Modelling Nonlinear Economic Time Series (2010)Time Series Analysis: Forecasting and Control (1977)Comparing Predictive Accuracy (1994)Forecasting with artificial neural networks: (1998)A comparative study of linear and nonlinear models for aggregate retail sales forecasting (2003)Performance of state space and ARIMA models for consumer retail sales forecasting (2015)Time-series forecasting of seasonal items sales using machine learning – A comparative analysis (2022)Forecasting methods for management (1990)Forecasting Principles and Applications (1998)Principles of Forecasting (2001)A two-stage dynamic sales forecasting model for the fashion retail (2010)Application of Facebook's Prophet Algorithm for Successful Sales Forecasting Based on Real-world Data (2020)Demand forecasting for fashion products: A systematic review (2023)On the bias of intermittent demand estimates (2001)Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model (2003)On the categorization of demand patterns (2004)Impact of Digital Technology on Supply Chain Efficiency in Manufacturing Industry (2022)AI Applications in Supply Chain Management: A Survey (2025)Supply Chain Management: Strategy, Planning, and Operation (2003)A hybrid demand forecasting model for greater forecasting accuracy: the case of the pharmaceutical industry (2021)A multi-objective model for optimizing the socio-economic performance of a pharmaceutical supply chain (2021)Demand forecasting model for time-series pharmaceutical data using shallow and deep neural network model (2022)Time Series Analysis, Forecasting and Control. 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this work references cited by second hop

References

  • 2020An optimized model using LSTM network for demand forecasting538 cited
  • 2001Forecasting aggregate retail sales:258 cited
  • 2011Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice249 cited
  • 2001A Parametric Approach to Flexible Nonlinear Inference202 cited
  • 2019Demand forecasting in pharmaceutical supply chains: A case study142 cited
  • 2006A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts101 cited
  • 2003Forecasting women's apparel sales using mathematical modeling94 cited
  • 2017Demand Forecasting for Irregular Demands in Business Aircraft Spare Parts Supply Chains by using Artificial Intelligence (AI)84 cited
  • 2015Comparison of fuzzy inference system (FIS), FIS with artificial neural networks (FIS + ANN) and FIS with adaptive neuro-fuzzy inference system (FIS + ANFIS) for inventory control54 cited

Cited by

  • 2023Demand forecasting of spare parts with regression and machine learning methods: Application in a bus fleet55 cited
  • 2024Data Analytics in Supply Chain Management: A State-of-the-Art Literature Review18 cited

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