Results 91 to 100 of about 769,255 (291)
FEBS Open Bio, EarlyView.This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi +2 more
wiley +1 more source
Evolutionary Optimization in an Algorithmic Setting [PDF]
arXiv, 2006 Evolutionary processes proved very useful for solving optimization problems. In this work, we build a formalization of the notion of cooperation and competition of multiple systems working toward a common optimization goal of the population using evolutionary computation techniques.
arxiv
Evolutionary Algorithms for Quantum Computers [PDF]
Algorithmica, 2013 Algorithmica, 68 (1)
Johannsen, Daniel +2 more
openaire +4 more sources
A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem [PDF]
, 2015 A revised weight-coded evolutionary algorithm (RWCEA) is proposed for solving multidimensional knapsack problems. This RWCEA uses a new decoding method and incorporates a heuristic method in initialization.
Yang, Zhixin, Yuan, Quan
core +1 more source
A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
Hybridization of Evolutionary Algorithms [PDF]
Iztok Fister, Marjan Mernik and Janez Brest (2011). Hybridization
of Evolutionary Algorithms, Evolutionary Algorithms, Eisuke Kita (Ed.), ISBN:
978-953-307-171-8, InTech, 2013 Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized.
arxiv
A Theoretical Assessment of Solution Quality in Evolutionary Algorithms for the Knapsack Problem [PDF]
, 2014 Evolutionary algorithms are well suited for solving the knapsack problem. Some empirical studies claim that evolutionary algorithms can produce good solutions to the 0-1 knapsack problem. Nonetheless, few rigorous investigations address the quality of solutions that evolutionary algorithms may produce for the knapsack problem. The current paper focuses
arxiv +1 more source
Evolutionary Strategy Guided Reinforcement Learning via MultiBuffer Communication [PDF]
arXiv, 2023 Evolutionary Algorithms and Deep Reinforcement Learning have both successfully solved control problems across a variety of domains. Recently, algorithms have been proposed which combine these two methods, aiming to leverage the strengths and mitigate the weaknesses of both approaches. In this paper we introduce a new Evolutionary Reinforcement Learning
arxiv
Linear Evolutionary Algorithm [PDF]
, 2011 During the past three decades, global optimization problems (including single-objective optimization problems (SOP) and multi-objective optimization problems (MOP)) have been intensively studied not only in Computer Science, but also in Engineering.
Kezong Tang +3 more
openaire +3 more sources
A convergence acceleration operator for multiobjective optimisation [PDF]
, 2007 A novel multiobjective optimisation accelerator is introduced that uses direct manipulation in objective space together with neural network mappings from objective space to decision space.
Adra, S.F., Fleming, P.J., Griffin, I.A.
core +1 more source