Essays about: "Demand forecasting."
Showing result 1 - 5 of 178 essays containing the words Demand forecasting..
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1. Identifying the Underlying Factors Causing the Changes in the European Container Shipping Market in the Post-COVID-19 Era
University essay from Göteborgs universitet/Graduate SchoolAbstract : The COVID-19 pandemic has disrupted global supply chains and container shipping markets in several ways, leading to changes in demand, supply, and price. Therefore, identifying and understanding the underlying factors that have contributed to these changes is crucial for stakeholders in the industry and policymakers seeking to mitigate the negative effects of the pandemic on global trade, particularly in Europe. READ MORE
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2. Demand Forecasting of Automobile Spare Parts after the End-of-Production - A review of demand forecasting models
University essay from Göteborgs universitet/Graduate SchoolAbstract : Demand forecasting of spare parts plays a crucial role in automobile industry where it generally requires a significant attention in controlling inventory. It is possible to maintain an optimal stock level when there is a continues supply at the Original Equipment Manufacturers (OEMs). READ MORE
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3. Forecasting With Feature-Based Time Series Clustering
University essay from Jönköping University/Tekniska HögskolanAbstract : Time series prediction plays a pivotal role in various areas, including for example finance, weather forecasting, and traffic analysis. In this study, time series of historical sales data from a packaging manufacturer is used to investigate the effects that clustering such data has on forecasting performance. READ MORE
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4. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance
University essay from Uppsala universitet/Avdelningen för beräkningsvetenskapAbstract : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. READ MORE
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5. Improvement of Wind Power Forecasting and Prediction of Production Losses Caused by Ice Formation on Wind Turbine Blades : - A Machine Learning Approach
University essay from Umeå universitet/Institutionen för fysikAbstract : In the ongoing climate crisis, transitioning to renewable energy sources is essential to manage the increasing energy demand. One such renewable energy source is the weather-dependent energy source, wind power. Many wind farms are located in Cold Climate (CC) regions, known for their vast potential for wind power production. READ MORE