题目：Intelligent Productivity Transformation:Corporate Market Demand Forecasting

With the Aid of an AI Virtual Assistant

期刊：JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING

摘要：

With the penetration of deep learning technology into forecasting and decision support systems,enterprises have an increasingly urgent need for accurate forecasting of time series data. Especially in fields such as finance, retail, and production, immediate and accurate predictions of market trends are the key to maintaining a competitive advantage. This study aims to address the limitations oftraditional time series forecasting methods, such as the difficulty in adapting to the nonlinearity andnon-stationarity of the data, through an innovative deep learning framework. The authors proposea Prophet model that combines deep learning with LSTNet and statistics. In this way, they combinethe ability of LSTNet to handle complex time dependencies and the flexibility of the Prophet modelto handle trends and periodicity. The particle swarm optimization algorithm (PSO) is responsible fortuning this hybrid model, aiming to improve the accuracy of predictions. Such a strategy not only helpscapture long-term dependencies in time series, but also models seasonality and holiday effects well.

关键词：

AI Virtual Assistants, Business Intelligence, Data Analysis, Deep Learning, Enterprise Collaboration,Forecasting Tools