Results 31 to 40 of about 1,079,572 (317)

Prediction and Analysis of Borosilicate Glass Surface Deformation Induced by Flame Jet

Machines
To address the issues of low processing efficiency, poor forming accuracy, and internal damage in glass material processing, this study proposes the use of flame jet forming.
Biling Wang, Yutang Zhai, Xinming Zhang, Xinxin Qi, Weijie Fu   +4 more
doaj   +1 more source

Deep Spatiotemporal Model for COVID-19 Forecasting

Sensors, 2022
COVID-19 has caused millions of infections and deaths over the last 2 years. Machine learning models have been proposed as an alternative to conventional epidemiologic models in an effort to optimize short- and medium-term forecasts that will help health
Mario Muñoz-Organero, Paula Queipo-Álvarez   +1 more
doaj   +1 more source

Sparse model construction using coordinate descent optimization [PDF]

, 2013
We propose a new sparse model construction method aimed at maximizing a model’s generalisation capability for a large class of linear-in-the-parameters models.
Xia Hong, Hong, Xia, Sheng Chen, Chen, Sheng, Junbin Gao, Guo, Yi, Yi Guo, Guo, Yi (R18457), Gao, Junbin   +8 more
core   +1 more source

Modelling Dialogues for Optimal Legislation [PDF]

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law, 2019
This paper presents a framework for modelling legislative deliberation in the form of dialogues. Roughly, in legislative dialogues coalitions can dynamically change and propose rule-based theories associated with different utility functions, depending on the legislative theory the coalitions are trying to determine.
Guido Governatori, Antonino Rotolo, Régis Riveret, Serena Villata   +3 more
openaire   +3 more sources

Explainable and Optuna-Optimized Machine Learning for Battery Thermal Runaway Prediction Under Class Imbalance Conditions

Thermo
Modern energy storage systems for both power and transportation are highly related to lithium-ion batteries (LIBs). However, their safety depends on a potentially hazardous failure mode known as thermal runaway (TR).
Abir El Abed, Ghalia Nassreddine, Obada Al-Khatib, Mohamad Nassereddine, Ali Hellany   +4 more
doaj   +1 more source

Deep Learning Application of Fruit Planting Classification Based on Multi-Source Remote Sensing Images

Applied Sciences
With global climate change, urbanization, and agricultural resource limitations, precision agriculture and crop monitoring are crucial worldwide. Integrating multi-source remote sensing data with deep learning enables accurate crop mapping, but selecting
Jiamei Miao, Jian Gao, Lei Wang, Lei Luo, Zhi Pu   +4 more
doaj   +1 more source

Particle Swarm Optimization for Correlative Product Combinatorial Introduction Model

, 2009
Enterprises need to develop a process to determine how to find and develop new product ideas and finally, how to successfully introduce them to the marketplace.
Dong W(董威), Dong Wei, Wan Fucai
core   +1 more source

On optimal layer reinsurance model [PDF]

Applied Mathematical Sciences, 2019
In this paper, we consider the class of non-proportional reinsurance contracts known as layer reinsurance model or limited stop-loss treaty. With the aim of finding an optimal layer reinsurance, we make the choice of considering an optimization criteria preserving stop-loss order: we derive some conditions of optimality by minimizing insurer risk ...
Antonella Campana, Paola Ferretti
openaire   +3 more sources

HIGH SPEED FUNCTIONALITY OPTIMIZATION OF FIVE-PHASE PM MACHINE USING 3RD HARMONIC CURRENT [PDF]

, 2013
This project was supported by the Laboratory of Electrical Engineering and Power Electronics (L2EP) France. It is a successive cooperation project between the control team and optimization team of the laboratory .Some surrogate-assisted optimization ...
GONG, Jinlin, ASLAN, Bassel, SEMAIL, Eric, GONG, Jilin, GILLON, Frédéric   +4 more
core  

Simulation-optimization under uncertainty through metamodeling and bootstrapping [PDF]

, 2010
Most methods in simulation-optimization assume known environments, whereas this research accounts for uncertain environments combining Taguchi's world view with either regression or Kriging (Gaussian Process) metamodels (response surfaces).
Carlo Meloni, Dellino, Gabriella, Gabriella Dellino, Jack P.C. Kleijnen, Meloni, Carlo, Kleijnen, J. P. C., Kleijnen, Jack P.C., Dellino, G.   +7 more
core   +1 more source