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Showing 1 to 11 of 11 for “"Power prediction"”.

  1. Ship Power Prediction Using Machine Learning

    … vessels to optimize a voyage so as to minimize power consumption. The focus of this paper is on building and testing machine learning models that can accurately predict the shaft power of a vessel under different conditions. The models examined include pure theoretical models, pure neural …

    mit Repository record for Ship Power Prediction Using Machine Learning (opens in a new tab)

  2. Historical Consistent Neural Networks for Wind Power Prediction

    Modeling chaotic dynamical systems remains a fundamental challenge due to their inherent non-linearity, sensitivity to initial conditions, and long-range temporal dependencies. While Recurrent Neural Networks (RNNs) are widely used for such tasks, they often suffer from temporal inconsistency: …

    stellenbosch Repository record for Historical Consistent Neural Networks for Wind Power Prediction (opens in a new tab)

  3. Learning-based analytical cross-platform performance and power prediction

    … In order to meet stringent performance and power budgets, hardware and software designers are often required to explore large design spaces. With increasing complexities, fast and accurate performance and power prediction at early design stages thus becomes a key challenge. Existing …

    texas Repository record for Learning-based analytical cross-platform performance and power prediction (opens in a new tab)

  4. ASSESSING THE IMPACT OF TACTICAL MISSION PROFILES ON THE DEVELOPMENT OF POWER PREDICTION SOFTWARE

    … (E2O) needs to conduct an analysis of small unit power requirements. This study assesses both current and future (approx. 2024) small unit configurations, and the impact that operational conditions and tactical scenarios have on power requirements, beyond a straightforward reference to technical …

    nps Repository record for ASSESSING THE IMPACT OF TACTICAL MISSION PROFILES ON THE DEVELOPMENT OF POWER PREDICTION SOFTWARE (opens in a new tab)

  5. Islanded Wind Energy Management System Based on Neural Networks

    <p>Wind power, as the main renewable energy source, is increasingly deployed and connected into electrical networks thanks to the development of wind energy conversion technologies. This dissertation is focusing on research related to wind power system include grid-connected/islanded wind power

    denver Repository record for Islanded Wind Energy Management System Based on Neural Networks (opens in a new tab)

  6. Modeling and prediction of wind power data

    In a power system, supply and demand must be equal at all times. The wind power forecast accuracy is directly connected to the need for balancing energy and hence to the cost of wind power integration. Many ways are used to predict wind power, but the accuracy of the predictions is not as good as …

    ttu Repository record for Modeling and prediction of wind power data (opens in a new tab)

  7. Modeling and design of a MEMS piezoelectric vibration energy harvester

    … by the need for pervasive and limitless power for wireless sensor nodes that have application in structural health monitoring, homeland security, and infrastructure monitoring. A review of prior milli- to micro-scale harvesters is provided. Common ambient low-level vibration sources are …

    mit Repository record for Modeling and design of a MEMS piezoelectric vibration energy harvester (opens in a new tab)

  8. Aerodynamic design and analysis of small horizontal axis wind turbine blades

    … model was proposed to analyse wind turbine power performance. The proposed model shows improvement in power prediction for the validation case, compared with the existing stall correction models. The effects of the key rotor parameters of a small wind turbine as well as the blade chord and …

    cent-lancashire Repository record for Aerodynamic design and analysis of small horizontal axis wind turbine blades (opens in a new tab)

  9. Average-case analysis of power consumption in embedded systems

    Power efficiency is one of the most important constraints in the design of embedded systems since such systems are generally driven by batteries with limited energy budget or restricted power supply. In every embedded system, there are one or more processor cores to run the software and interact …

    cork Repository record for Average-case analysis of power consumption in embedded systems (opens in a new tab)