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48453 results in Computer Science

Page 590 of 2423

  • Deep kernel learning approach to engine emissions modeling

  • Changmin Yu, Marko Seslija, George Brownbridge, Sebastian Mosbach, Markus Kraft, Mohammad Parsi, Mark Davis, Vivian Page, Amit Bhave
  • Journal:
    Data-Centric Engineering / Volume 1 / 2020
    Published online by Cambridge University Press:
    18 June 2020, e4
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  • We apply deep kernel learning (DKL), which can be viewed as a combination of a Gaussian process (GP) and a deep neural network (DNN), to compression ignition engine emissions and compare its performance to a selection of other surrogate models on the same dataset. Surrogate models are a class of computationally cheaper alternatives to physics-based models. High-dimensional model representation (HDMR) is also briefly discussed and acts as a benchmark model for comparison. We apply the considered methods to a dataset, which was obtained from a compression ignition engine and includes as outputs soot and NOx emissions as functions of 14 engine operating condition variables. We combine a quasi-random global search with a conventional grid-optimization method in order to identify suitable values for several DKL hyperparameters, which include network architecture, kernel, and learning parameters. The performance of DKL, HDMR, plain GPs, and plain DNNs is compared in terms of the root mean squared error (RMSE) of the predictions as well as computational expense of training and evaluation. It is shown that DKL performs best in terms of RMSE in the predictions whilst maintaining the computational cost at a reasonable level, and DKL predictions are in good agreement with the experimental emissions data.

  • Autonomous Intelligent Planning Method for Welding Path of Complex Ship Components

  • Tao Wang, Zhilong Xue, Xiaoqing Dong, Senlin Xie
  • Journal:
    Robotica / Volume 39 / Issue 3 / March 2021
    Published online by Cambridge University Press:
    18 June 2020, pp. 428-437

  • Aiming at planning the welding path of complex ship components, a welding path planning optimization model was constructed with the shortest welding path and using the target and the welding process and welding starting and ending points as constraints. Based on the model, an improved ant colony algorithm with dynamic adaptive parameters was proposed to complete the path planning work. Simulation results showed that, compared with other classical optimization algorithms, the proposed algorithm improved optimization speed while ensuring optimization effect and achieving better results in path planning of complex ship components.

  • Data-Centric Engineering in modern science from the perspective of a statistician, an engineer, and a software developer

  • Christophe Ley, Mike Tibolt, Dirk Fromme
  • Journal:
    Data-Centric Engineering / Volume 1 / 2020
    Published online by Cambridge University Press:
    18 June 2020, e2
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  • Data-Centric Engineering is an emerging branch of science that certainly will take on a leading role in data-driven research. We live in the Big Data era with huge amounts of available data and unseen computing power, and therefore a crafty combination of Statistics (or, in more modern terms, Data Science), Computer Science and Engineering is required to filter out the most important information, master the ever more difficult challenges of a changing world and open new paths. In this paper, we will highlight some of these aspects from a combined perspective of a statistician, an engineer and a software developer. In particular, we will focus on sound data handling and analysis, computational science in Structural Engineering, data care, security and monitoring, and conclude with an outlook on future developments.

Page 590 of 2423