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Showing result 36 - 40 of 1266 essays matching the above criteria.

  1. 36. Extraction of Global Features for enhancing Machine Learning Performance

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

    Author : Abyel Tesfay; [2023]
    Keywords : Machine Learning; Deep Learning; Feature Extraction; Global Features; Time-series data; Bioprocessing; Maskininlärning; Djupinlärning; Funktionsextraktion; Globala Funktioner; Tidsserie data; Biobearbetning;

    Abstract : Data Science plays an essential role in many organizations and industries to become data-driven in their decision-making and workflow, as models can provide relevant input in areas such as social media, the stock market, and manufacturing industries. To train models of quality, data preparation methods such as feature extraction are used to extract relevant features. READ MORE

  3. 37. Prediction Models for TV Case Resolution Times with Machine Learning

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

    Author : Borja Javierre I Moyano; [2023]
    Keywords : Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

    Abstract : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. READ MORE

  4. 38. Estimating eco-friendly driving behavior in various traffic situations, using machine learning

    University essay from Linköpings universitet/Institutionen för datavetenskap

    Author : Ludvig Fors; [2023]
    Keywords : Machine learning; transformers; neural networks; casual inference; K-Means; driver behavior; fuel consumption;

    Abstract : This thesis investigates how various driver signals, signals that a truck driver can interact with, influences fuel consumption and what are the optimal values of these signals in various traffic conditions. More specifically, the objective is to estimate good driver behavior in various traffic conditions and compare bad driver behavior in similar situations to see how performing a specific driver action, changing a driver signal from the bad driver value to the corresponding good driver value impacts the fuel consumption. READ MORE

  5. 39. Performance Benchmarking and Cost Analysis of Machine Learning Techniques : An Investigation into Traditional and State-Of-The-Art Models in Business Operations

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

    Author : Jacob Lundgren; Sam Taheri; [2023]
    Keywords : Artificial Intelligence AI ; Machine Learning; Big Data; Natural Language Processing NLP ; Pre-Trained BERT; Fine-Tuned BERT; TF-IDF; Logistic Regression; Support Vector Machine SVM ; Cloud GPU; Operating Costs; Performance Efficiency; Business Intelligence;

    Abstract : Eftersom samhället blir allt mer datadrivet revolutionerar användningen av AI och maskininlärning sättet företag fungerar och utvecklas på. Denna studie utforskar användningen av AI, Big Data och Natural Language Processing (NLP) för att förbättra affärsverksamhet och intelligens i företag. READ MORE

  6. 40. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning

    University essay from KTH/Matematisk statistik

    Author : Hannes Andersson; John Sjöberg; [2023]
    Keywords : Supply chain disruption; SMOTE; feature engineering; machine learning; random forest; statistics; applied mathematics; Störning i försörjningskedja; maskininlärning; matematik; statistik;

    Abstract : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. READ MORE