Titlebook: Human Centred Intelligent Systems; Proceedings of KES-H Alfred Zimmermann,Robert J. Howlett,Rainer Schmidt Conference proceedings 2021 The

說(shuō)明

Crisis Year 2020: Analysis of Finnish Manufacturing Companies’ Twitter Activity 915 tweets and their contents were analyzed. Frequently used words and n-grams are reflected with the financial performance of said companies and developments of Covid-19 pandemic during that year. The overall activity is observed to somewhat correlate with the recorded Covid-19 infections, however

miracle

伸展

Univariate Time Series Forecasting by Investigating Intermittence and Demand Individuallyines, and reassemble both information to generate a prediction which preserves the characteristics of an intermittent time series. We compare the results against Croston’s approach, as well as recent forecast procedures where no split is performed.

BANAL

Univariate Time Series Forecasting: Machine Learning Prediction of the Best Suitable Forecast Model e best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.