engleski

Advanced Data Analytics in Logistics Demand Forecasting

The logistics demand forecasting is increasingly influenced by digitalization processes in logistics business. Traditional approach to logistics demand forecasting based on human expertise and statistical assessment is still very present, but the use of Big Data, Artificial Intelligence and Machine Learning becomes more prominent. By using these technologies, logistics demand forecasting becomes not only more reliable but also more agile and self-adjusting, with better insight into changing market conditions in the real-time perspective. In this paper, the Authors research the evolution of Data Analytics in logistics demand forecasting. and provide an insight to the features of Big Data, Artificial Intelligence and Machine Learning used for Advanced Data Analytics in logistics demand forecasting.

logistics demand forecasting ; Advanced Data Analytics ; Big Data ; Artificial Intelligence ; Machine Learning

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