VANETs, or vehicle impromptu networks, offer an efficient facility for applications requiring transportation systems with intelligence (ITS). In Communication using VANET, roadside units (RSUs) are the primary element...
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Ensemble learning, a technique that combines multiple base models to enhance performance and reduce variance, is a well-established approach in machinelearning. In recent years, quantum machinelearning has emerged a...
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The threat of credit card fraud is high and so there should be efficient ways to combat it. The research is being employed to focus on how to enhance credit card fraud detection, machinelearning methodologies can be ...
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This research paper addresses the critical challenges in agricultural crop recommendation systems through machinelearning approaches. Current systems face significant limitations including limited integration of real...
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A comprehensive analysis was performed using the AIDS Clinical Trials Group 175 dataset to improve the accuracy of predicting AIDS disease progression. The primary objective was to integrate machinelearning technique...
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The use of machinelearning techniques for developing intelligent energy management systems for buildings. Because of the growing emphasis placed on energy efficiency and sustainability, optimizing the amount of energ...
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Social media platforms, such as YouTube, generate an extensive amount of unstructured data, offering valuable insights into user behavior, engagement patterns, and preferences. This project focuses on predictive analy...
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Popularity of Social media sites has been on the rise ever since its invention. Due to the anonymity the social media sites provide to the users, an influx of divergent behavior has also been increasing. Abusive langu...
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Linear systems of equations can be found in various mathematical domains, as well as in the field of machinelearning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate f...
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ISBN:
(纸本)9798331541378
Linear systems of equations can be found in various mathematical domains, as well as in the field of machinelearning. By employing noisy intermediate-scale quantum devices, variational solvers promise to accelerate finding solutions for large systems. Although there is a wealth of theoretical research on these algorithms, only fragmentary implementations exist. To fill this gap, we have developed the variational-lse-solver framework, which realizes existing approaches in literature, and introduces several enhancements. The user-friendly interface is designed for researchers that work at the abstraction level of identifying and developing end-to-end applications.
The most significant creature in the ecology is the butterfly. The relationship between plants and butterflies is essential for supporting many ecosystem processes. They are occasionally referred to as flying flowers ...
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