Results 31 to 40 of about 709,118 (272)
Prediction of Drifter Trajectory Using Evolutionary Computation
Discrete Dynamics in Nature and Society, 2018 We used evolutionary computation to predict the trajectory of surface drifters. The data used to create the predictive model comprise the hourly position of the drifters, the flow and wind velocity at the location, and the location predicted by the MOHID
Yong-Wook Nam, Yong-Hyuk Kim
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Evolutionary techniques in lattice sieving algorithms [PDF]
11th International Conference on Evolutionary Computation Theory
and Applications (ECTA), pp. 31-39, 2019, 2019 Lattice-based cryptography has recently emerged as a prominent candidate for secure communication in the quantum age. Its security relies on the hardness of certain lattice problems, and the inability of known lattice algorithms, such as lattice sieving, to solve these problems efficiently.
arxiv +1 more source
Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem [PDF]
arXiv, 2022 Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity
arxiv
Biclustering of Smart Building Electric Energy Consumption Data
Applied Sciences, 2019 Nowadays, smart buildings can collect data regarding the electric energy consumption, which can then be analyzed to gain insights or to predict or identify abnormal energy consumption.
Federico Divina +2 more
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eLife, 2022 Directed microbial evolution harnesses evolutionary processes in the laboratory to construct microorganisms with enhanced or novel functional traits. Attempting to direct evolutionary processes for applied goals is fundamental to evolutionary computation,
Alexander Lalejini +3 more
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GA Approach to Optimize Training Client Set in Federated Learning
IEEE Access, 2023 Federated learning, where the distribution of distributed data is unknown, is more difficult and costly to train a central model with than traditional machine learning.
Dongseok Kang, Chang Wook Ahn
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Supporting Air-Conditioning Controller Design Using Evolutionary Computation
Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2008 In recent years, as part of the remarkable development of electronic techniques, electronic control has been applied to various systems. Many sensors and actuators have been implemented into those systems, and energy efficiency and performance have been ...
Kazuyuki KOJIMA, Keiichi WATANUKI
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Optimizing Team Sport Training With Multi-Objective Evolutionary Computation
International Journal of Computer Science in Sport, 2021 This research introduces a new novel method for mathematically optimizing team sport training models to enhance two measures of athletic performance using an evolutionary computation based approach.
Connor Mark +4 more
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Design Exploration of Initial Bubbles for Higher-Speed Laser-Induced Microjets
IEEE Access, 2023 Laser-induced microjets are advantageous for yielding high-speed and convergent microjets shape. However, owing to the need for high-power laser devices, reducing the required laser power is a prerequisite for convenience in practical use.
Tatsumasa Ishikawa +2 more
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Epigenetic opportunities for Evolutionary Computation [PDF]
arXiv, 2021 Evolutionary Computation is a group of biologically inspired algorithms used to solve complex optimisation problems. It can be split into Evolutionary Algorithms, which take inspiration from genetic inheritance, and Swarm Intelligence algorithms, that take inspiration from cultural inheritance. However, recent developments have focused on computational
arxiv