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Mirko Dinulovic, Aleksandar Benign and Bo?ko Ra?uo
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials is ...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Giorgio Lazzarinetti, Riccardo Dondi, Sara Manzoni and Italo Zoppis
Solving combinatorial problems on complex networks represents a primary issue which, on a large scale, requires the use of heuristics and approximate algorithms. Recently, neural methods have been proposed in this context to find feasible solutions for r...
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Yiming Mo, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li and Haiting Xia
The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and the...
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Xin Liao and Khoi D. Hoang
Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular form...
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