As urban traffic pressure continues to increase, existing traffic systems have achieved some success in improving vehicle throughput. However, they commonly face issues such as insufficient precision in visual recogni...
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Indoor positioning systems are now extensively used, enabling the precise localization of a user within a predefined space. The effectiveness of these services, particularly through the use of the geomagnetic field as...
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Solar photovoltaic (PV) systems are at the forefront of the global transition to sustainable energy. However, understanding their performance under diverse real-world conditions remains a challenge. Traditional studie...
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Multi-behavior sequential recommendation aims to predict users' next interested item, by learning dynamic user preferences within their multi-behavior interaction sequences. Users' dynamic preferences are deci...
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In the realm of video processing and analysis, accurate prediction of future frames is crucial in applications like video compression, anomaly detection and augmented reality. This paper introduces a novel approach th...
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Microelectromechanical system (MEMS) based pressure sensors have been utilized for decades;however, new trends in pressure sensors have recently emerged, such as increased sensitivity, a broader range and reduced chip...
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A new era of computational efficacy and problem-solving abilities has begun with the combination of Recurrent Neural Networks (RNNs) and computer science methods. It is crucial in modern computing to combine RNNs with...
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This paper presents an improved tuning fork gyroscope (TFG) structure utilizing two gyroscope drive resonator frames and a diamond-shaped coupling spring mechanism. It explores a two-degree-of-freedom system for the d...
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Agent-based simulation models are an important tool to study the effectiveness of policy interventions on the uptake of residential photovoltaic systems by households, a cornerstone of sustainable energy system transi...
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ISBN:
(数字)9781665408967
ISBN:
(纸本)9781665408967
Agent-based simulation models are an important tool to study the effectiveness of policy interventions on the uptake of residential photovoltaic systems by households, a cornerstone of sustainable energy system transition. In order for these models to be trustworthy, they require rigorous validation. However, the canonical approach of validating emulation models through calibration with parameters that minimize the difference of model results and reference data fails when the model is subject to many stochastic influences. The residential photovoltaic diffusion model PVact features numerous stochastic influences that prevent straightforward optimization-driven calibration. From the analysis of the results of a case-study on the cities Dresden and Leipzig (Germany) based on three error metrics (mean average error, root mean square error and cumulative average error), this research identifies a parameter range where stochastic fluctuations exceed differences between results of different parameterization and a minimization-based calibration approach fails. Based on this observation, an approach is developed that aggregates model behavior across multiple simulation runs and parameter combinations to compare results between scenarios representing different future developments or policy interventions of interest.
To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densel...
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