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Found 4 essays matching the above criteria.
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1. Warehouse Vehicle Routing using Deep Reinforcement Learning
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : In this study a Deep Reinforcement Learning algorithm, MCTS-CNN, is applied on the Vehicle Routing Problem (VRP) in warehouses. Results in a simulated environment show that a Convolutional Neural Network (CNN) can be pre-trained on VRP transition state features and then effectively used post-training within Monte Carlo Tree Search (MCTS). READ MORE
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2. Estimating Median Visiting Times using Re-identification
University essay from Lunds universitet/Matematik LTHAbstract : Using customer visiting times stores can analyse customer behaviour and gain insights to help improve the store experience. This thesis investigates the possibility of using person re-identification to create a system that can estimate the median visiting time. Neural networks were used to analyse images of persons from two different views. READ MORE
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3. Predicting house prices using Ensemble Learning with Cluster Aggregations
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : The purpose of this investigation, as prescribed by Valueguard AB, was to evaluate the utility of Machine Learning (ML) models to estimate prices on samples of their housing dataset. Specifically,the aim was to minimize the Median Absolute Percent Error (MDAPE) of the predictions. READ MORE
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4. Remote Sensing and Statistical Analysis of Fracture Populations Around Lake Thingvallavatn, SW Iceland
University essay from Uppsala universitet/Institutionen för geovetenskaperAbstract : This study aims at a description and statistical analysis of tectonic and magmatic fractures in the Western Volcanic Zone (WVZ) on Iceland. Two fracture populations are studied with respect to their distance to the Hengill volcano: The southern area is between 0-10 kilometers from the volcano and the northern area is between 16-25 kilometers from the volcano. READ MORE
