Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 146 for “"ANNs"”.
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Epistemic opacity: a feature not a bug: an exploration into the relationship between brains and ANNs
AI in the 21st century has come to be dominated by one school in particular, connectionism. And its successes are all around us – in the media we consume, in the music we listen to, in the cold calls we receive, etc. While this school was founded by psychologists, logicians, and philosophers with …
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Application of artificial neural networks in breast and colorectal surgery
… to happen to them. Artificial neural networks (ANNs) are a nonlinear regression method capable of accurately predicting outcome in an individual patient. We identified two scenarios where accurate prediction in individual patient can greatly influence their management.In the first study, we …
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Graph-based Vector Search Algorithms for Retrieval-Augmented AI Systems
… leveraging approximate nearest neighbor search (ANNS) have thus become an important data processing primitive in AI systems following the introduction of retrievel-augmented generation (RAG). However, the complexity of tasks these AI systems aim to solve introduces challenges for existing ANNS …
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An Application of Artificial Neural Networks in Forecasting Future Oil Price Return Volatilities
… novel application of Artificial Neural Networks (ANNs) in Financial Engineering. Here Artificial Neural Networks are applied for simulating both direct and inverse of some financial models. This study comprises of four parts. In first two parts, the ANNs are applied to forecast via forward/direct …
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Input variable selection for time series forecasting with artificial neural networks : an empirical evaluation across varying time series frequencies
… in the research of artificial neural networks (ANNs) to forecasting problems. Both in theoretical and empirical works, ANNs have shown evidence of good performance, in many cases outperforming established statistical benchmarks. This thesis starts by reviewing the advances in ANNs for time …
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Short-term wind power forecasting using artificial neural networks-based ensemble model
… artificial neural network-based approaches (ANNs) have been one of the most effective and popular approaches for short-term wind power forecasting because of the availability of large amounts of historical data and strong computational power. Although ANNs usually perform well for short-term …
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SNP auto-calling using artificial neural networks
… problem of classification. The ability of ANNs to solve this problem is highly germane to making progress in the refinement of DNA microarray analysis and techniques regarding this issue. This study attempts to deal with the classification of microarray data and the comparison and …
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Artificial neural networks for the computation of the inverse kinematics of redundant manipulators
… manipulators, the Artificial Neural Networks (ANNs) toolbox from MATLAB is used. Aiming to obtain manipulators’ joint angles coordinates and solve the IK problem with acceptable accuracy; different scenarios with different training inputs and different training functions are considered to train …
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Analysis and forecast of the capesize bulk carriers shipping market using Artificial Neural Networks
… benefits of using Artificial Neural Networks (ANNs) in forecasting the Capesize Ore Voyage Rates from Tubarao to Rotterdam with a 145,000 dwt Bulk carrier. Initially, market analysis allows the assessment of the relation of some parameters of the dry bulk market with the evolution of freight …
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Deriving statistical inference from the application of artificial neural networks to clinical metabolomics data
… methods, typified by Artificial Neural Networks (ANNs) may be more appropriate to model potential nonlinear latent covariance; however, they are not widely used due to difficulty in deriving statistical inference, and thus biological interpretation. Herein, we illustrate the utility of ANNs for …
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Towards more biologically plausible deep learning and visual processing
… successes of Artificial Neural Networks (ANNs) on solving a wide range of Al tasks. However, there is considerably less development in understanding the biological neural networks in primate cortex. In this thesis, I try to bridge the gap between artificial and biological neural networks. …
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Scalability Analysis of Synchronous Data-Parallel Artificial Neural Network (ANN) Learners
Artificial Neural Networks (ANNs) have been established as one of the most important algorithmic tools in the Machine Learning (ML) toolbox over the past few decades. ANNs' recent rise to widespread acceptance can be attributed to two developments: (1) the availability of large-scale training and …
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Single-Phase, Single-Switch, Sensorless Switched Reluctance Motor Drive Utilizing a Minimal Artificial Neural Net
Artificial Neural Networks (ANNs) have proved to be useful in approximating non- linear systems in many applications including motion control. ANNs advocated in switched reluctance motor (SRM) control typically have a large number of neurons and several layers which impedes their real time …
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Stèidheachadh Ghnàthan-cànain Ùra Cuairteachadh Ideòlais-chànain ann an Trì Gaeltachtaí Nua
… na trì coimhearsnachdan seo coltach ri chèile anns an t-seagh gum biodh iad uile ag iomairt gus làraichean còmhnaidheach a stèidheachadh far an rachadh cleachdadh Gàidhlig na h-Èireann na ghnàths gu ìre no eile. Chaidh gnìomh an<br/>ideòlais-chànain a mheasadh anns na Gaeltachtaí nua, agus gu …
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An Empirical Analysis of Takeover Predictions in the UK: Application of Artificial Neural Networks and Logistic Regression
… Regression (LR) and Artificial Neural Networks (ANNs) have been applied as modelling techniques for predicting target companies in the UK. Hence by applying ANNs in takeover predictions, their prediction ability in target classification is tested and results are compared to the LR results. For …
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Forecasting Chlorine Residual for Water Safety Using Artificial Neural Networks Ensembles in Humanitarian Water Systems
… use of ensembles of artificial neural networks (ANNs) to probabilistically forecast the point-of-consumption free residual chlorine (FRC) concentration using water quality data from six refugee and IDP settlements. These models were then used to generate point-of-distribution FRC targets based on …
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Artificial Neural Network and Dynamic Probabilistic Risk Assessment for passive safety systems
… the application of Artificial Neural Networks (ANNs) and Dynamic Probabilistic Risk Assessment (DPRA) as advanced methodologies for the safety assessment of passive safety systems, particularly in mitigating Loss of Coolant Accidents (LOCAs). While using the BWRX-300 SMR, the study highlights …
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Connectome-Constrained Artificial Neural Networks
… are desirable for artificial neural networks (ANNs), which are, unlike their organic counterparts, practically unbounded, and in many cases, initialized with random weights or arbitrary structural elements. In this dissertation, we consider an inductive base case for imposing BNN constraints …
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The characterisation of multiple defects in components using artificial neural networks
… the use of artificial neural networks (ANNs) as a means of processing signals from non-destructive tests, to characterise defects and provide more information regarding the condition of the component than would otherwise be possible for an operator to obtain from the test data. ANNs are …
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