Sökning: "artificiella neuronnät"

Hittade 5 avhandlingar innehållade orden artificiella neuronnät.

1. 1. Development and Application of Uncertainty Analysis Approaches for MELCOR Simulations of Severe Accidents

   Författare :Wanhong Wang; Weimin Ma; Florian Fichot; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Severe accident; MELCOR; uncertainty analysis; Wilks’ method; Bootstrapped artificial neural network; deterministic sampling method; 95 95 tolerance limit.; Svåra haverier; MELCOR; osäkerhetsanalys; Wilks’ metod; artificiella neuronnät; deterministiska urvalsmetoder; 95 95-toleransgränser.;

   Sammanfattning : The contemporary needs in advancing safety analysis methods and the increasing stringency in light water reactor (LWR) safety in the post-Fukushima era require more advanced and systematical approaches for severe accident analyses. The best estimate plus uncertainty (BEPU) methods are among such approaches and have been widely used for deterministic safety analysis (DSA) of design basis accidents (DBAs). LÄS MER

3. 2. Radar Signal Processing using Artificial Neural Networks

   Författare :Alexander Karlsson; Magnus Jansson; Mikael Hämäläinen; Henrik Holter; Maria Sabrina Greco; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; artificial neural networks; classification; deep learning; detection; parameter estimation; radar; artificiella neuronnät; klassificering; djupinlärning; detektion; parameter estimering; radar; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : This thesis combines radar signal processing, with data driven artificial neuralnetwork (ANN) methods. Signal processing algorithms are often based on modelingassumptions of how the data was formed. In some cases, such models are sufficientfor designing good, or even optimal, solutions. LÄS MER

4. 3. Structural Health Monitoring of Bridges : Data-based damage detection method using Machine Learning

   Författare :Ana C. Neves; Raid Karoumi; Elsa Caetano; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Structural Health Monitoring; damage detection; Machine Learning; data-based methods; Artificial Neural Networks; Value of Information; Structural Engineering and Bridges; Bro- och stålbyggnad;

   Sammanfattning : Civil engineering structures built according to modern codes are designed for a service life of normally more than 100 years. At the same time, there is a growing pressure to keep existing aged structures in service despite the fact that they have reached the original designed lifetime, with bridges being a good example of this. LÄS MER

5. 4. Synergies between Chemometrics and Machine Learning

   Författare :Rickard Sjögren; Johan Trygg; Olivier Cloarec; Ola Spjuth; Umeå universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; computational science; machine learning; chemometrics; multivariate data analysis; design of experiments; data science; beräkningsvetenskap; maskininlärning; kemometri; multivariat dataanalys; experimentdesign;

   Sammanfattning : Thanks to digitization and automation, data in all shapes and forms are generated in ever-growing quantities throughout society, industry and science. Data-driven methods, such as machine learning algorithms, are already widely used to benefit from all these data in all kinds of applications, ranging from text suggestion in smartphones to process monitoring in industry. LÄS MER

7. 5. On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

   Författare :Alexander Olsson; Avdelningen för Biomedicinsk teknik; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; EMG; Machine Learning; Deep Learning; Feature Learning; Biosignal Processing; Gesture Recognition; Muscle-Computer Interfaces; Myoelectric Control; Upper-Limb Prosthetics;

   Sammanfattning : Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. LÄS MER