Essays about: "Sales forecast"

Showing result 1 - 5 of 69 essays containing the words Sales forecast.

1. 1. Sales forecasting for supply chain using Artificial Intelligence

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Vaibhav Mittal; [2023]
   Keywords : AI; sales forecasting; supply chain; predictive analytics; AI; försäljningsprognoser; supply chain; predictiv analys;

   Abstract : Supply chain management and logistics are two sectors currently experiencing a transformation thanks to the advent of AI(Artificial Intelligence) technologies. Leveraging predictive analytics powered by AI presents businesses with novel opportunities to streamline their operations effectively. READ MORE

3. 2. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

   University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

   Author : Stella Jarlöv; Anton Svensson Dahl; [2023]
   Keywords : demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

   Abstract : 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

4. 3. Battery storage implementation in Sweden and sizing software development

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : Santiago Moreano Rojas; [2023]
   Keywords : ;

   Abstract : Due to the rampant growth of the penetration of renewables into the electrical grids across the world, more challenges appear in the way to assure the optimal operation of the energy system. More particularly, in the case of Sweden, the nuclear power decommissioning tendency and the 100% renewable energy target by 2040, set two strong additional motivations for the rise of issues regarding variability, uncertainty, stability, balancing and quality in the grid. READ MORE

5. 4. Optimizing within the Supply Chain: A Mathematical Model for Inventory Optimization with respect to Demand Planning

   University essay from KTH/Matematisk statistik

   Author : William Bork; Martynas Giedraitis; [2023]
   Keywords : Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model; Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model;

   Abstract : This thesis examines how to design a mathematical inventory model for a ”Fast Moving Consumer Goods”-company (FMCG-company), which determines the optimal reorder point and order quantity such that the average inventory cost is minimized. The thesis was made in collaboration with a ”Software as a Service”- company which provided the data containing information about the products and inventory management of one of their customers, a FMCG-company. READ MORE

6. 5. Portfolio Risk Modelling in Venture Debt

   University essay from KTH/Matematisk statistik

   Author : John Eriksson; Jacob Holmberg; [2023]
   Keywords : Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

   Abstract : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. READ MORE