In recent times, cloud computing has been a popular enterprise for holding as well as offering solutions, as it has grown up with great appeal in providing various solutions such as storage space and cloud holding. Ai...
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This research paper presents a comparative study on speed control techniques for servo motors in industrial and automation applications. The three techniques under investigation are the conventional PID control, Fuzzy...
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As the number of vehicles rises, there is a problem with traffic congestion on the roads. This problem is characterized by slower speeds, greater time spent travelling, and more congestion in the traffic lanes. In add...
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Millions of users worldwide are connected by cellular networks, which are the foundation of contemporary telecommunications.A vital component in guaranteeing the resilience and ecellular communication networks is radi...
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Shapley Values are concepts established for eXplainable AI. They are used to explain black-box predictive models by quantifying the features' contributions to the model's outcomes. Since computing the exact Sh...
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ISBN:
(纸本)9798350387544;9798350387537
Shapley Values are concepts established for eXplainable AI. They are used to explain black-box predictive models by quantifying the features' contributions to the model's outcomes. Since computing the exact Shapley Values is known to be computationally intractable on real-world datasets, neural estimators have emerged as alternative, more scalable approaches to get approximated Shapley Values estimates. However, experiments with neural estimators are currently hard to replicate as algorithm implementations, explainer evaluators and results visualizations are neither standardized nor promptly usable. To bridge this gap, we present BONES, a new benchmark focused on neural estimation of Shapley Value. It provides researchers with a suite of state-of-the-art neural and traditional estimators, a set of commonly used benchmark datasets, ad hoc modules for training black-box models, as well as specific functions to easily compute the most popular evaluation metrics and visualize results. The purpose is to simplify XAI model usage, evaluation, and comparison. In this paper, we showcase BONES results and visualizations for XAI model benchmarking on both tabular and image data. The open-source library is available at the following link: https://***/DavideNapolitano/BONES.
AGC which is also termed as LFC i.e. load frequency control, employs mathematical modelling to understand the dynamics of power generation and load fluctuations. The classical second-order system featuring a governor ...
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In order to improve the antenna's gain and alter its radiation properties, this study examines a rectangular microstrip patch antenna that is partially loaded with homogeneous substrate and superstrate made of μ-...
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The pursuit of sustainable transportation solutions has propelled research into regenerative braking systems for high-speed railways. The power conditioner with energy store system is proposed for high-speed railways,...
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Collaboration of edge nodes through task migration offers a promising solution for mobile edge computing to meet the varied computation-intensive demands with constrained resources. However, most existing task migrati...
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Substation automation is ever challenged by the integration of distributed energy resources which imposes higher deployment flexibility and adaptability for protection and control. Although virtualization helps to run...
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