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Siyuan Xing and Jian-Qiao Sun
The Gaussian-radial-basis function neural network (GRBFNN) has been a popular choice for interpolation and classification. However, it is computationally intensive when the dimension of the input vector is high. To address this issue, we propose a new fe...
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Mao Nishira, Satoshi Ito, Hiroki Nishikawa, Xiangbo Kong and Hiroyuki Tomiyama
Delivery drones have been attracting attention as a means of solving recent logistics issues, and many companies are focusing on their practical applications. Many research studies on delivery drones have been active for several decades. Among them, exte...
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Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
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Eleonora Dallan, Andrea Bottacin-Busolin, Mattia Zaramella and Andrea Marion
Solute transport in rivers is controlled by mixing processes that occur over a wide spectrum of spatial and temporal scales. Deviations from the classic advection?dispersion model observed in tracer test studies are known to be generated by the temporary...
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Laura Patricia García-Pineda and Oscar Danilo Montoya
This research deals with the problem regarding the optimal siting and sizing of distribution static compensators (D-STATCOMs) via the application of a master?slave optimization technique. The master stage determines the nodes where the D-STATCOMs must be...
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Seydali Ferahtia, Azeddine Houari, Mohamed Machmoum, Mourad Ait-Ahmed and Abdelhakim Saim
Due to the present trend in the wind industry to operate in deep seas, floating offshore wind turbines (FOWTs) are an area of study that is expanding. FOWT platforms cause increased structural movement, which can reduce the turbine?s power production and...
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Dimitris C. Tsamatsoulis, Christos A. Korologos and Dimitris V. Tsiftsoglou
This study aims to approximate the optimum sulfate content of cement, applying maximization of compressive strength as a criterion for cement produced in industrial mills. The design includes tests on four types of cement containing up to three main comp...
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Patrice Koehl, Marc Delarue and Henri Orland
The Gromov-Wasserstein (GW) formalism can be seen as a generalization of the optimal transport (OT) formalism for comparing two distributions associated with different metric spaces. It is a quadratic optimization problem and solving it usually has compu...
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Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan and Jonathon Corrales de Oliveira
In the field of Artificial Intelligence (AI) and Machine Learning (ML), a common objective is the approximation of unknown target functions y=f(x)" role="presentation">??=??(??)y=f(x)
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using limited instances S=(x(i),y(i))" role="presentation...
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Jiang Fan, Qinghao Yuan, Fulei Jing, Hongbin Xu, Hao Wang and Qingze Meng
The emerging Local Maximum-Entropy (LME) approximation, which combines the advantages of global and local approximations, has an unsolved issue wherein it cannot adaptively change the morphology of the basis function according to the local characteristic...
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