Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior , Departamento de Tecnología y de las Comunicaciones. Fecha de lectura: 11-04-2018
Este trabajo pretende abordar dos objetivos. El primero sería realizar un estudio de los resultados obtenidos para la predicción del consumo eléctrico a corto plazo en las viviendas con un método de RNN LSTM en comparación con los resultados previamente obteni…
This is an investigation of how the performance on a natural language task, semantic role labeling (SRL), is affected by how the input text is encoded. Four methods for encoding words as dense vectors of floating-point numbers are evaluated: Noisecontrastive e…
The harbour porpoise is a toothed whale whose presence is threatened in Scandinavia. Onestep towards preserving the species in critical areas is to study and observe the harbourporpoise population growth or decline in these areas. Today this is done by using u…
In this master thesis, the problem of tracking humans in video streams by using Deep Learning is examined. We use spatially supervised recurrent convolutional neural networks for visual human tracking. In this method, the recurrent convolutional network uses b…
Forecasting future values of time series has long been a field with many and varied applications, from climate and weather forecasting to stock prediction and economic planning to the control of industrial processes. Many of these problems involve not only a s…
This thesis investigated how machine learning-based anomaly detection can be applied to support predictive maintenance for a radar system using available monitoring data. An LSTM autoencoder was trained on selected healthy running operation and used to detect…
No contexto da Indústria 4.0, a manutenção preditiva desempenha um papel fundamental na otimização do desempenho dos ativos e na redução dos custos operacionais. Esta tese apresenta uma nova estrutura de aprendizagem ativa projetada para melhorar a eficiência…
Smart homes collect continuous sensor data about how people live, including when they sleep, cook, work, and move around the house. Training AI models on this data has traditionally required sending it to a central server, which creates serious privacy risks a…
Reliable autonomous vehicle operation at urban intersections requires competence across the prediction–perception stack, yet current deep learning models underuse the structural priors that govern real-world driving. This thesis argues that incorporating struc…
The prediction of future values from historical time series data is widely applied infields such as industrial monitoring, finance, and decision support systems. Whilemost forecasting approaches operate directly on numerical time series, symbolicrepresentation…
This master's thesis deals with the optimization of building heating control using machine learning methods. Traditional control systems often fail to efficiently respond to the thermal inertia of buildings and variable external influences. Model Predictive Co…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
