Essays about: "Sekventiella Modeller"

Showing result 1 - 5 of 27 essays containing the words Sekventiella Modeller.

  1. 1. Computationally Efficient Explainable AI: Bayesian Optimization for Computing Multiple Counterfactual Explanantions

    University essay from KTH/Matematik (Avd.)

    Author : Giorgio Sacchi; [2023]
    Keywords : Explainable AI; Counterfactual Explanations CFEs ; Bayesian Optimization BO ; Black-Box Models; Model-Agnostic; Machine Learning ML ; Efficient Computation; High-Stake Decisions; Förklarbar AI; Kontrafaktuell Förklaring CFE ; Bayesiansk Optimering BO ; Svarta lådmodeller; Modellagnostisk; Maskininlärning; Beräkningsmässigt Effektiv; Beslut med höga insatser;

    Abstract : In recent years, advanced machine learning (ML) models have revolutionized industries ranging from the healthcare sector to retail and E-commerce. However, these models have become increasingly complex, making it difficult for even domain experts to understand and retrace the model's decision-making process. READ MORE

  3. 2. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

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

    Author : Luca Colasanti; [2023]
    Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

    Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE

  4. 3. Managing the procurement process during scale-up: A case study of a European Battery Manufacturer

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

    Author : Lisa Bergqvist; Sofia Holm Öste; [2023]
    Keywords : procurement process; purchasing; expansion framework; battery manufactures; scale-up; ramp-up; Inköpsprocess; expansion ramverk; batteritillverkare;

    Abstract : The European battery market is in rapid growth and the industry actors are ramping up production as well as exploring international expansion opportunities. However, due to the relative novelty of the industry in Europe, there is a lack of benchmark companies and established frameworks for successful expansion. READ MORE

  5. 4. Optimal simultaneous excitation for identification of multivariable systems

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

    Author : Gunnar Sigurðsson; [2023]
    Keywords : System identification; Simultaneous excitation; Experiment design; Model Predictive Control MPC ; Optimization; Multivariable systems; Systemidentifiering; Simultan excitation; Experimentdesign; Modell Predictive Control MPC ; Optimering; Multivariabla system;

    Abstract : Having a accurate model of a system is essential for many applications today, especially those related to advanced process control. When executing a project often a lot of time is spent performing experiments on the real system to estimate a model. READ MORE

  6. 5. Supervised Algorithm for Predictive Maintenance

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

    Author : Haida Lu; [2023]
    Keywords : Long short-term memory; Predictive maintenance; Remaining useful life; Embedded Artificial Intelligence; Långt korttidsminne; förebyggande underhåll; återstående livslängd; inbyggd artificiell intelligens;

    Abstract : Predictive maintenance plays a crucial role in preventing unexpected equipment failures and maintaining assets in good operating conditions in various systems. One such scenario where predictive maintenance has been widely used is in battery management systems for electronic vehicles based on lithium batteries, where the risk of failure can be reduced by predicting the remaining useful life of the lithium battery. READ MORE