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Titlebook: Machine Learning, Optimization, and Big Data; Third International Giuseppe Nicosia,Panos Pardalos,Renato Umeton Conference proceedings 201

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樓主: detumescence
41#
發(fā)表于 2025-3-28 15:19:24 | 只看該作者
Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm wbility of multi-objective deterministic particle swarm optimization (MODPSO) is combined with the local search accuracy of a derivative-free multi-objective (DFMO) linesearch method. Six MODHA formulations are discussed, based on two MODPSO formulations and three DFMO activation criteria. Forty five
42#
發(fā)表于 2025-3-28 20:14:22 | 只看該作者
43#
發(fā)表于 2025-3-28 23:42:10 | 只看該作者
Multi-objective Genetic Algorithm for Interior Lighting Design,d in lighting design: the respect of a given target level of illuminance, uniformity of lighting, and electrical energy saving. The proposed solution integrates the 3D graphic software Blender, used to reproduce the architectural space and to simulate the effect of illumination, and the genetic algo
44#
發(fā)表于 2025-3-29 04:34:23 | 只看該作者
Conference proceedings 2018eld in Volterra, Italy, in September 2017..The 50 full papers presented were carefully reviewed and?selected from 126 submissions. The papers cover topics in the?field of machine learning, artificial intelligence, computational optimization and data science?presenting a substantial array of ideas, t
45#
發(fā)表于 2025-3-29 08:48:28 | 只看該作者
Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models,anslation of different features using examples from cancer literature. We also outline several issues that still arise when assembling cellular network models from state-of-the-art reading engines. Finally, we illustrate the details of our approach with a case study in pancreatic cancer.
46#
發(fā)表于 2025-3-29 12:41:58 | 只看該作者
Dolphin Pod Optimization, method, resulting in more than 140,000 optimization runs. The most promising setup is compared with deterministic particle swarm optimization, central force optimization, and DIviding RECTangles and finally applied to the optimization of a destroyer hull form for reduced resistance and improved seakeeping.
47#
發(fā)表于 2025-3-29 18:01:31 | 只看該作者
48#
發(fā)表于 2025-3-29 23:00:24 | 只看該作者
49#
發(fā)表于 2025-3-30 03:18:19 | 只看該作者
50#
發(fā)表于 2025-3-30 04:30:44 | 只看該作者
Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm wcs. The most promising formulations are finally applied to the hull-form optimization of a high-speed catamaran in realistic ocean conditions and compared to MODPSO and DFMO, showing promising results.
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