Train platooning, which allows multiple train units to be virtually coupled into a platoon with very short following distances, has become an emerging technology in railway industry. Our study investigates the energy-...
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By querying approximate surrogate models of different fidelity as available information sources, Multi-Fidelity Bayesian Optimization (MFBO) aims at optimizing unknown functions that are costly if not infeasible to ev...
By querying approximate surrogate models of different fidelity as available information sources, Multi-Fidelity Bayesian Optimization (MFBO) aims at optimizing unknown functions that are costly if not infeasible to evaluate. Existing MFBO methods often assume that approximate surrogates have consistently high/low fidelity across the input domain. However, approximate evaluations from the same surrogate can have different fidelity at different input regions due to data availability and model constraints, especially when considering machine learning surrogates. In this work, we investigate MFBO when multi-fidelity approximations have input-dependent fidelity. By explicitly capturing input dependency for multi-fidelity queries in Gaussian Process (GP), our new input-dependent MFBO (iMFBO) with learnable noise models better captures the fidelity of each information source in an intuitive way. We further design a new acquisition function for iMFBO and prove that the queries selected by iMFBO have higher quality than those by naive MFBO methods, with the derived sub-linear regret bound. Experiments on both synthetic and real-world data demonstrate its superior empirical performance.
Water conservation starts from rationalizing irrigation,as it is the largest consumer of this vital *** the critical and urgent nature of this issue,several works have been *** idea of most researchers is to develop i...
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Water conservation starts from rationalizing irrigation,as it is the largest consumer of this vital *** the critical and urgent nature of this issue,several works have been *** idea of most researchers is to develop irrigation management systems tomeet the water needs of plants with optimal use of this *** fact,irrigation water requirement is only the amount of water that must be applied to compensate the evapotranspiration ***-Monteith equation is the most common formula to evaluate reference evapotranspiration,but it requiresmany factors that cannot be available in many *** leads to a trend towards behavior model *** identification with control is one of the most promising applications in this *** idea behind this proposal depends on three stages:First,the estimation of reference evapotranspiration(ET0)by a linear ARX model,where temperature,relative humidity,insolation duration and wind speed are used as inputs,and ET0 estimated by Penman-Monteith equation as *** results show that the values estimated by thismethodwere in good agreement with the measured *** second part of this paper is tomanage the quantity of *** this purpose,two controllers are used for testing,lead-lag and *** adjust the first controller and optimize the choice of its parameters,Nelder-Mead algorithm is *** the last part,a comparative study is done between the two used controllers.
Internet of Things (IoT) is considered as the next industrial revolution in the years ahead. Many devices will have been connected to the Internet and more and more devices were added to them. The number of these type...
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This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that ...
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In this paper, we address the problem of automatic clothing parsing in surveillance images using the information from user-generated tags, such as "jeans" and "T-shirt." Although clothing parsing h...
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One of the main stages in the training of an air traffic controller: practical work. The trainee must apply all theoretical knowledge concerning the separation rules decreed by ICAO to resolve a traffic situation pres...
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ISBN:
(数字)9798350367560
ISBN:
(纸本)9798350367577
One of the main stages in the training of an air traffic controller: practical work. The trainee must apply all theoretical knowledge concerning the separation rules decreed by ICAO to resolve a traffic situation presenting a certain number of conflicts generated by a group of aircraft (A/C). At the end of his performance, the solution proposed by the trainee is compared to that of the instructor or that generated by a control simulator. For a trainee wishing to train in the absence of an instructor or simulator, it is useful to offer them a simple tool that can provide an optimized solution. Thus, the use of metaheuristics in this tool is recommended and the challenge revolves around two main objectives, eliminating the risk of collisions between A/C while minimizing changes to initial flight plans. Regarding previous work, where genetic algorithms and simulated annealing were used to the problem, we present a comparison an analyse of the results obtained for both principals objectives by this two algorithms through a series of tests on exercises inspired by real practical work.
As Large Language Models (LLMs) become more integrated into our daily lives, it is crucial to identify and mitigate their risks, especially when the risks can have profound impacts on human users and societies. Guardr...
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There are fundamental rules and principles setting the limits of physical systems. It triggers an interesting thought—can we break the limits under specific circumstances? A realistic system can only provide limited ...
There are fundamental rules and principles setting the limits of physical systems. It triggers an interesting thought—can we break the limits under specific circumstances? A realistic system can only provide limited functionalities because its performance is physically constrained by some fundamental principles.‘Breaking the limit’, which usually implies that the capability of a system could be enhanced significantly,
Presuppositions are implicit assumptions that interlocutors take for granted. Verifying presuppositions is crucial for reasoning-based fact-checking that aims to reason about True or False, but existing pipelines have...
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Presuppositions are implicit assumptions that interlocutors take for granted. Verifying presuppositions is crucial for reasoning-based fact-checking that aims to reason about True or False, but existing pipelines have overlooked it. We first raise this critical issue with the community and propose a system that addresses the generation, verification, and reasoning of presuppositions through a recursive question-answering process. Importantly, our system automatically determines which knowledge entails which presuppositions, making it an unsupervised system for evidence retrieval, fact-checking, and justification production. We conduct a comprehensive experiment on the FEVER, Vitamin C, and FEVEROUS-S datasets. Our system outperforms competitive baselines, including LLM, and achieves state-of-the-art unsupervised performance. We highlight this critical issue to encourage further research on reasoning-based fact-checking.
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