{"title":"需求预测分析:基于深度学习的决策支持系统","authors":"Saurabh Kumar, Mr. Amar Nayak","doi":"10.18535/ijecs/v13i07.4853","DOIUrl":null,"url":null,"abstract":"Demand forecasting is a critical component of supply chain management and business operations, enabling organizations to make informed decisions about production, inventory management, and resource allocation. In recent years, predictive analytics has emerged as a powerful tool for enhancing the accuracy and efficiency of demand forecasting. This review paper explores the transformative role of predictive analytics and deep learning in demand forecasting. It examines how these advanced techniques have evolved from traditional models based on past sales data, offering nuanced predictions through sophisticated statistical and machine learning methods. Deep learning, with its neural network structures, brings automatic feature learning, complex pattern handling, and scalability, enhancing forecasting in sectors like retail, manufacturing, and healthcare. The paper reviews various deep learning models, compares them with traditional methods, and discusses their impact on business operations and decision-making. It concludes by looking at future trends in predictive analytics and deep learning in demand forecasting.","PeriodicalId":231371,"journal":{"name":"International Journal of Engineering and Computer Science","volume":"31 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive Analytics for Demand Forecasting: A deep Learning-based Decision Support System\",\"authors\":\"Saurabh Kumar, Mr. Amar Nayak\",\"doi\":\"10.18535/ijecs/v13i07.4853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Demand forecasting is a critical component of supply chain management and business operations, enabling organizations to make informed decisions about production, inventory management, and resource allocation. In recent years, predictive analytics has emerged as a powerful tool for enhancing the accuracy and efficiency of demand forecasting. This review paper explores the transformative role of predictive analytics and deep learning in demand forecasting. It examines how these advanced techniques have evolved from traditional models based on past sales data, offering nuanced predictions through sophisticated statistical and machine learning methods. Deep learning, with its neural network structures, brings automatic feature learning, complex pattern handling, and scalability, enhancing forecasting in sectors like retail, manufacturing, and healthcare. The paper reviews various deep learning models, compares them with traditional methods, and discusses their impact on business operations and decision-making. It concludes by looking at future trends in predictive analytics and deep learning in demand forecasting.\",\"PeriodicalId\":231371,\"journal\":{\"name\":\"International Journal of Engineering and Computer Science\",\"volume\":\"31 8\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18535/ijecs/v13i07.4853\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18535/ijecs/v13i07.4853","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive Analytics for Demand Forecasting: A deep Learning-based Decision Support System
Demand forecasting is a critical component of supply chain management and business operations, enabling organizations to make informed decisions about production, inventory management, and resource allocation. In recent years, predictive analytics has emerged as a powerful tool for enhancing the accuracy and efficiency of demand forecasting. This review paper explores the transformative role of predictive analytics and deep learning in demand forecasting. It examines how these advanced techniques have evolved from traditional models based on past sales data, offering nuanced predictions through sophisticated statistical and machine learning methods. Deep learning, with its neural network structures, brings automatic feature learning, complex pattern handling, and scalability, enhancing forecasting in sectors like retail, manufacturing, and healthcare. The paper reviews various deep learning models, compares them with traditional methods, and discusses their impact on business operations and decision-making. It concludes by looking at future trends in predictive analytics and deep learning in demand forecasting.