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1. 1. Finding Anomalous Energy ConsumersUsing Time Series Clustering in the Swedish Energy Market

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Lukas Tonneman; [2023]
   Nyckelord :time-series analysis; clustering; electricity consumer clustering; anomaly detection; gaussian mixture model; hierarchical clustering;

   Sammanfattning : Improving the energy efficiency of buildings is important for many reasons. There is a large body of data detailing the hourly energy consumption of buildings. This work studies a large data set from the Swedish energy market. LÄS MER

3. 2. Regression with Bayesian Confidence Propagating Neural Networks

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

   Författare :Raghav Rajendran Bongole; [2023]
   Nyckelord :Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

   Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER

4. 3. Industrial Machine Monitoring: Real-Time Anomalous Sound Event Detection on Low-Powered Devices

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Alexander Magnusson; Anton Andersson; [2023]
   Nyckelord :Anomaly Detection; Sound Event Detection; MFCC; GMM; OCSVM; Mathematics and Statistics;

   Sammanfattning : Traditionally fault detection in industrial machinery has been performed manually by experienced machine operators listening to the machines. However, it is desirable to automate this process to increase efficiency and improve the working environment of the operators. LÄS MER

5. 4. Robust Non-Linear State Estimation for Underwater Acoustic Localization : Expanding on Gaussian Mixture Methods

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

   Författare :Diogo Antunes; [2023]
   Nyckelord :Robust state estimation; Underwater localization; Target tracking; Gaussian mixture; AUV; Estimação robusta de estado; Localização subaquática; Rastreamento de alvos; Mistura Gaussiana; AUV; Robust tillståndsuppskattning; Undervattenslokalisering; Målspårning; Gaussisk blandning; AUV;

   Sammanfattning : Robust state estimation solutions must deal with faulty measurements, called outliers, and unknown data associations, which lead to multiple feasible hypotheses. Take, for instance, the scenario of tracking two indistinguishable targets based on position measurements, where each measurement could refer to either of the targets or even be a faulty reading. LÄS MER

7. 5. A Bandit Approach to Indirect Inference

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

   Författare :Erik Ildring; Felix Steinberger Eriksson; [2023]
   Nyckelord :;

   Sammanfattning : We present a novel approach to the family of parameter estimation methods known asindirect inference (II), using results from bandit optimization, a sub-field of reinforcementlearning concerned with stateless Markov decision processes (MDPs). First, we present theproblem of indirect inference and show how it may be cast into the general framework ofMDPs. LÄS MER