In daily lives, people often use translators for cross-language translation, but the current translation system has the problem of translation accuracy, and its translation speed also has some limitations. Artificial ...
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Quasi (pseudo/approximate) periodic signals often occur in natural settings, particularly when a periodic signal is recorded with noise. In this work, we develop a new dynamical equation system to construct a family o...
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Runtime systems are commonly used by parallel applications in order to efficiently exploit the underlying hardware resources. A runtime system hides the complexity of the management of the hardware and exposes a high-...
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ISBN:
(数字)9781665498562
ISBN:
(纸本)9781665498562
Runtime systems are commonly used by parallel applications in order to efficiently exploit the underlying hardware resources. A runtime system hides the complexity of the management of the hardware and exposes a high-level interface to application developers. To this end, it makes decisions by relying on heuristics that estimate the future behavior of the application. In this paper, we propose PYTHIA, a library that serves as an oracle capable of predicting the future behavior of an application, so that the runtime system can make more informed decisions. PYTHIA builds on the deterministic nature of many HPC applications: by recording an execution trace, PYTHIA captures the application main behavior. The trace can be provided for future executions of the application, and a runtime system can ask for predictions of future program behavior. We evaluate PYTHIA on 13 MPI applications and show that PYTHIA can accurately predict the future of most of these applications, even when varying the problem size. We demonstrate how PYTHIA predictions can guide a runtime system optimization by implementing an adaptive thread parallelism strategy in GNU OpenMP runtime system. The evaluation shows that, thanks to PYTHIA prediction, the adaptive strategy reduces the execution time of an application by up to 38 %.
The medical texts contain rich information about the health status of patients, including personal demographic details, examination items, diagnostic narratives, and corresponding outcomes. There is often an underlyin...
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As modern technology continues to evolve, human-computer interaction (HCI) technology is becoming increasingly prevalent in various industries, including entertainment, e-commerce, education, artificial intelligence, ...
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Load forecasting plays an indispensable role in ensuring the stability and economy of power supply. This study aims to deeply analyze the application of soft computing technology and data mining theory in the field of...
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ISBN:
(数字)9798350350760
ISBN:
(纸本)9798350350777
Load forecasting plays an indispensable role in ensuring the stability and economy of power supply. This study aims to deeply analyze the application of soft computing technology and data mining theory in the field of power system load forecasting. By introducing neural networks, especially Kohonen network and BP neural network, this study successfully realizes the robust clustering of load curves, the construction of feature curves, and the identification of abnormal curve patterns. Meanwhile, this paper combines the composite neural network and feature curves to effectively recognize and correct the abnormal data. In the field of fuzzy modeling, this study optimizes the structure of the fuzzy inference system using the CART algorithm and establishes a multi-parameter load forecasting model. Case studies confirm the effectiveness of these methods and highlight the strong potential of soft computing and data mining in improving load forecasting accuracy and data quality.
In recent years, with the continuous increase of renewable energy installation capacity, China has been facing increasingly severe problems of abandoned wind, abandoned light and abandoned water. Hydrogen energy as a ...
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The high-speed power line carrier (HPLC)+ high-speed radio frequency (HRF) dual-mode communication technology can significantly improve the reliability and transmission efficiency of power communication systems. This ...
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Driver fatigue is a significant causative factor to accidents worldwide. To signify this issue, we have created a prototype system for detecting tiredness in drivers. This system monitors the driver's level of dro...
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Classifying an individual with suicidal behavior is a complex problem. A clinical decision support system (CDSS) helps medical experts in their daily work and supports them in effective decision-making. The huge amoun...
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