the traditional fire warning system with a single threshold value is widely used. However, due to the development process of fire, the variation of parameters in each stage is quite different, so it is difficult to ac...
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Improving the perception of objects for an image through label co-occurrence correlation is shown to improve the hash quality. Existing methods ignore the relationship between different representation regions and lack...
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software-defined networking (SDN) and network functions virtualization (NFV) are two enabling paradigms at the forefront of reshaping the management of smart city core networking. the emergence of these paradigms pres...
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In the transition process of tailrace system of large hydropower station, there may be the phenomenon of free-surface-pressurized flow. In order to obtain the accurate operating state of constant flow in the free-surf...
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Network performance has become a crucial consideration in ensuring a flawless user experience in the era of data-intensive applications and cloud computing. Traditional Networks are not suitable for solving such issue...
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Protocol conformance testing is an indispensable part of the marketization of commercial terminals. this paper elaborates and studies the architecture, test model, and design scheme of the 5G terminal protocol conform...
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Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to explainable classification systems. Classical association rule mining algori...
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ISBN:
(纸本)9783031777301;9783031777318
Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to explainable classification systems. Classical association rule mining algorithms have several limitations, especially with regards to their high execution times and number of rules produced. Over the past decade, neural network solutions have been used to solve various optimization problems, such as classification, regression or clustering. However there is still no efficient way to mine association rules using neural networks. In this paper, we present an auto-encoder solution to mine association rule called ARM-AE. We compare our algorithm to FP-Growth and NSGAII on three categorical datasets, and show that our algorithm discovers high support and confidence rule set and has a better execution time than classical methods while preserving the quality of the rule set produced.
Explainable AI (XAI) methods provide insights into the operation of black-box Deep Neural Network (DNN) models. GradCAM, an XAI algorithm, provides an explanation by highlighting regions in the input feature space tha...
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the high data latency in real-world applications makes the standard online training platform incompatible. As a result, online video-based English teaching system is created using computer algorithms and 5G wireless n...
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Predictive maintenance (PdM) in heating, ventilation, and air conditioning (HVAC) systems improves energy efficiency and extends equipment lifespan. However, developing deep learning (DL) models for PdM faces challeng...
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