Essays about: "Temporal Analysis"

Showing result 21 - 25 of 498 essays containing the words Temporal Analysis.

1. 21. Spatial and Temporal Dynamics of  Carbon Sequestration in Stockholm  County's Green areas : A GIS-based Analysis

   University essay from KTH/Hållbar utveckling, miljövetenskap och teknik

   Author : Victoria Kareflod; [2023]
   Keywords : Carbon sequestration; carbon dynamics; decarbonization; scenario analysis; Corine land cover analysis; urban vegetation; carbon offset; Paris agreement; koldioxidlagring; koldynamik; dekarbonisering; scenarioanalys; marktäckesanalys; stadsvegetation; koldioxidkompensation; parisavtalet;

   Abstract : The human influence of global climate is an issue currently assessed in various mitigation strategies. Stockholm County has committed to becoming carbon neutral by 2040 and negative by 2045 according to the Paris agreement. READ MORE

3. 22. Methods for local energy and climate planning : A Case stuudy on the Urban Community of Dunkirk

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

   Author : Sacha Thibault; [2023]
   Keywords : Energy transition - Climate and energy policy - Renewable energy - Decision-Support Tools - Local authorities; Energiomställning - Klimat- och energipolitik - Förnybar energi - Verktyg för beslutsstöd - Lokala myndigheter;

   Abstract : Energy management concerns were raised in France after the oil crisis in the 1970s. From then, the local actors developed policies to better control the energy production and consumption on the territories. Climate considerations and the need to limit greenhouse gases (GHG) emissions were then added to these energy issues in the early 2000s. READ MORE

4. 23. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

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

   Author : Love Marcus; [2023]
   Keywords : User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Abstract : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. READ MORE

5. 24. Monitoring deforestation in the Serranía de Chiribiquete in northern Colombian Amazon using time series analysis of satellite data

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Yuyang Qian; [2023]
   Keywords : Physical Geography and Ecosystem analysis; CCDC; Forest loss; Landsat; Sentinel-1; Change detection; NNP; FARC; Earth and Environmental Sciences;

   Abstract : Deforestation monitoring is of significant importance for the ecosystem, climate change,and policy-making. The availability of optical and synthetic aperture radar (SAR) satellite remote sensing images, along with the development of time series change detection methods, has contributed to the increasing popularity of time series analysis in forest disturbance monitoring. READ MORE

6. 25. 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