Essays about: "Feedforward Neural Network"
Showing result 11 - 15 of 39 essays containing the words Feedforward Neural Network.
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11. Transformer learning for traffic prediction in mobile networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The resources of mobile networks are expensive and limited, and as demand for mobile data continues to grow, improved resource utilisation is a prioritised issue. Traffic demand at base stations (BSs) vary throughout the day and week, but the capacity remains constant and utilisation could be significantly improved based on precise, robust, and efficient forecasting. READ MORE
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12. Artificial Value-at-Risk : Using Neural Networks to Replicate Filtered Historical Simulation for Value-at-Risk Calculations
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : Since financial markets are considered risky, there is a need to have credible tools that can estimate these risks. For a Central Clearing Counterparty it is of utmost importance to conduct accurate estimations of its members’ risk exposures to deter-mine their margin requirements. READ MORE
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13. The derivation of first- and second-order backpropagation methods for fully-connected and convolutional neural networks
University essay from Lunds universitet/Matematik LTH; Lunds universitet/MatematikcentrumAbstract : We introduce rigorous theory for deriving first and second order backpropagation methods for Deep Neural Networks (DNN) whilst satisfying existing theory in DNN optimization. We begin by formally defining a neural network with its respective components and state the first and second order chain rule with respect to its partial derivatives. READ MORE
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14. A comparative study of Neural Network Forecasting models on the M4 competition data
University essay from Uppsala universitet/Statistiska institutionenAbstract : The development of machine learning research has provided statistical innovations and further developments within the field of time series analysis. This study seeks to investigate two different approaches on artificial neural network models based on different learning techniques, and answering how well the neural network approach compares with a basic autoregressive approach, as well as how the artificial neural network models compare to each other. READ MORE
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15. Development of Neural Networks Using Deterministic Transforms
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Deep neural networks have been a leading research topic within the machine learning field for the past few years. The introduction of graphical processing units (GPUs) and hardware advances made possible the training of deep neural networks. Previously the training procedure was impossible due to the huge amount of training samples required. READ MORE
