Search for dissertations about: "artificial neural network"

Showing result 11 - 15 of 154 swedish dissertations containing the words artificial neural network.

2. 11. On Data Mining and Classification Using a Bayesian Confidence Propagation Neural Network

   Author : Roland Orre; KTH; []
   Keywords : data mining; bcpnn; classification; neural network;

   Abstract : The aim of this thesis is to describe how a statisticallybased neural network technology, here named BCPNN (BayesianConfidence Propagation Neural Network), which may be identifiedby rewriting Bayes' rule, can be used within a fewapplications, data mining and classification with credibilityintervals as well as unsupervised pattern recognition.BCPNN is a neural network model somewhat reminding aboutBayesian decision trees which are often used within artificialintelligence systems. READ MORE

4. 12. High-Performance Network-on-Chip Design for Many-Core Processors

   Author : Boqian Wang; Zhonghai Lu; Kun-Chih Chen; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Network-on-Chip; Chip Multi Many-core Processors; Multiprocessor System-on-Chip; High-Performance Computing; Cache Coherence; Virtual Channel Reservation; Admission Control; Artificial Neural Network; AXI4; Quality of Service; Network-on-Chip; Chip Multi Many-core Processors; Multiprocessor Sys-tem on a Chip; High-Performance Computing; Cache Coherence; Virtual Channel Reser-vation; Admission Control; Artificial Neural Network; AXI4; Quality of Servic; Informations- och kommunikationsteknik; Information and Communication Technology;

   Abstract : With the development of on-chip manufacturing technologies and the requirements of high-performance computing, the core count is growing quickly in Chip Multi/Many-core Processors (CMPs) and Multiprocessor System-on-Chip (MPSoC) to support larger scale parallel execution. Network-on-Chip (NoC) has become the de facto solution for CMPs and MPSoCs in addressing the communication challenge. READ MORE

5. 13. Morphometric and Landscape Feature Analysis with Artificial Neural Networks and SRTM data : Applications in Humid and Arid Environments

   Author : Amir Houshang Ehsani; Friedrich Quiel; Wolfgang Wagner; KTH; []
   Keywords : Self Organizing Map; Neural Network; Morphometric Feature; Landscape; Yardang; Lut Desert; Potential natural vegetation; geoecosystem; Landform; Landsat ETM ; Morphometric Parameters; SRTM; Resolution; Curvatures; DEM.; TECHNOLOGY; TEKNIKVETENSKAP;

   Abstract : This thesis presents a semi-automatic method to analyze morphometric features and landscape elements based on Self Organizing Map (SOM) as an unsupervised Artificial Neural Network algorithm in two completely different environments: 1) the Man and Biosphere Reserve “Eastern Carpathians” (Central Europe) as a complex mountainous humid area and 2) Lut Desert, Iran, a hyper arid region characterized by repetition of wind-eroded features. In 2003, the National Aeronautics and Space Administration (NASA) released the SRTM/ SIR-C band data with 3 arc seconds (approx. READ MORE

6. 14. Utilization of a GSHP System in a DHC Network : modeling and optimization

   Author : Anjan Rao Puttige; Thomas Olofsson; Ronny Östin; Staffan Andersson; Javed Saqib; Umeå universitet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Ground source heat pump; district heating and cooling; optimization; borehole heat exchanger; artificial neural network; hybrid model; field measurements; calibration; heat pumps; prosumer;

   Abstract : The ground source heat pumps (GSHPs) of customers connected to the district heating and cooling (DHC) network can benefit both the customer and the energy company. However, operating the GSHP to minimize the cost of providing heating and cooling to the customer while ensuring the long-term stability of the ground temperature is a challenge. READ MORE

7. 15. Pith location and annual ring detection for modelling of knots and fibre orientation in structural timber : A Deep-Learning-Based Approach

   Author : Tadios Habite; Anders Olsson; Osama Abdeljaber; Jan Oscarsson; Welf Löwe; Julie Cool; Linnéuniversitetet; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sawn timber; Pith location; Deep learning; Artificial neural networks; Convolutional neural network; Conditional generative adversarial network; Knot detection; Knot modelling; Knot reconstruction; Fibre orientation; Annual ring profile; Byggteknik; Civil engineering;

   Abstract : Detection of pith, annual rings and knots in relation to timber board cross-sections is relevant for many purposes, such as for modelling of sawn timber and for real-time assessment of strength, stiffness and shape stability of wood materials. However, the methods that are available and implemented in optical scanners today do not always meet customer accuracy and/or speed requirements. READ MORE