Sökning: "Survival Analysis kth"

Visar resultat 1 - 5 av 37 uppsatser innehållade orden Survival Analysis kth.

  1. 1. Dubbel väsentlighetsanalys i praktiken : En kvalitativ studie om kritiska steg i analysprocessen

    Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknik

    Författare :Sigrid Hjelm Redin; [2024]
    Nyckelord :Sustainability Reporting; Materiality Assessment; Double Materiality; Stakeholder Engagement; CSRD; NFRD; Hållbarhetsrapportering; Väsentlighetsanalys; Dubbel Väsentlighetsanalys; Intressentengagemang; CSRD; NFRD;

    Sammanfattning : Ekonomisk tillväxt kan ge upphov till bland annat klimatförändringar och sociala ojämlikheter, och innebär ett hot mot EU:s och världens fortsatta överlevnad. EU har därav framfört en tydlig strategi för hållbar utveckling i sin så kallade gröna giv, som syftar till att bana väg för en grön omställning i EU och vars slutmål är klimatneutralitet senast år 2050. LÄS MER

  3. 2. Designing learning experiences for collaborative survival : Using stories about biodiversity measures in the construction sector

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jonas Diego van Doorn; [2023]
    Nyckelord :Learning; design; interaction; biodiversity; construction; workshop; Lärande; design; interaktion; biologisk mångfald; konstruktion; verkstad;

    Sammanfattning : Biodiversity loss is increasing at an unprecedented rate, with the construction sector generating significant negative externalities. Developing an educational experience focused on biodiversity within this sector can enhance knowledge and expertise to mitigate such loss by showcasing resilient nature-based solutions. LÄS MER

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

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Luca Colasanti; [2023]
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER

  5. 4. Poggio Aquilone - Survey and Repurposing in a Medieval Italian Village

    Uppsats för yrkesexamina på avancerad nivå, KTH/Arkitektur

    Författare :Philip Reimers; [2023]
    Nyckelord :Italy; Repurposing; Transformation; Refurbishment; Renovation; Survey; Umbria; Ruin; Rural Tourism; Lidar; drone; scanning; photogrammetry;

    Sammanfattning : The site of this diploma project is the small hilltop village of Poggio Aquilone. The village, situated in the region of Umbria in central Italy, lies roughly halfway between Rome and Florence. LÄS MER

  7. 5. Development of a Machine Learning Survival Analysis Pipeline with Explainable AI for Analyzing the Complexity of ED Crowding : Using Real World Data collected from a Swedish Emergency Department

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Tobias Haraldsson; [2023]
    Nyckelord :SHAP; Explainable AI; Survival Analysis; LOS; Machine Learning; ED Crowding; SHAP; Förklarbar AI; Överlevnadsanalys; LOS; Maskininlärning; Överbelastning på Akuten;

    Sammanfattning : One of the biggest challenges in healthcare is Emergency Department (ED)crowding which creates high constraints on the whole healthcare system aswell as the resources within and can be the cause of many adverse events.Is is a well known problem were a lot of research has been done and a lotof solutions has been proposed, yet the problem still stands unsolved. LÄS MER