Results 101 to 110 of about 5,654,392 (381)
Aspects of Evolutionary Design by Computers [PDF]
arXiv, 1998 This paper examines the four main types of Evolutionary Design by computers: Evolutionary Design Optimisation, Evolutionary Art, Evolutionary Artificial Life Forms and Creative Evolutionary Design. Definitions for all four areas are provided. A review of current work in each of these areas is given, with examples of the types of applications that have ...
arxiv
International Journal of Adaptive Control and Signal Processing, EarlyView.Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez +2 more
wiley +1 more source
Toward Design Principles for Biomolecular Condensates for Metabolic Pathways
Advanced Biology, EarlyView.Biomolecular condensates are membrane‐less compartments found through‐out nature which can serve as reaction crucibles for biochemical processes. This review explores the design strategies underlying how condensates can be used in biotechnology to enhance multistep enzyme cascades including enhancement by mass action and substrate channeling, and ...
Alain A.M. André +3 more
wiley +1 more source
An evolutionary method for finding the optimal path connecting two settlements
Научный вестник МГТУ ГА, 2016 The paper describes an evolutionary method and an algorithm for finding the optimal path connecting two settlements.
Yu. I. Dement'ev, R. V. Zimin
doaj
Evolutionary Computation and Its Applications in Neural and Fuzzy Systems
Applied Computational Intelligence and Soft Computing, 2011 Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization.
Biaobiao Zhang +3 more
doaj +1 more source
Automatic Component-Wise Design of Multiobjective Evolutionary Algorithms
IEEE Transactions on Evolutionary Computation, 2016 Multiobjective evolutionary algorithms (MOEAs) are typically proposed, studied, and applied as monolithic blocks with a few numerical parameters that need to be set.
L. Bezerra +2 more
semanticscholar +1 more source
VALIS: an evolutionary classification algorithm
Genetic Programming and Evolvable Machines, 2018 VALIS is an effective and robust classification algorithm with a focus on understandability. Its name stems from Vote-ALlocating Immune System, as it evolves a population of artificial antibodies that can bind to the input data, and performs classification through a voting process.
Peter Karpov +2 more
openaire +4 more sources
Evolutionary Robotics: What, Why, and Where to
Frontiers in Robotics and AI, 2015 Evolutionary robotics applies the selection, variation, and heredity principles of natural evolution to the design of robots with embodied intelligence. It can be considered as a subfield of robotics that aims to create more robust and adaptive robots. A
Stephane eDoncieux +6 more
doaj +1 more source
Dynamics of heuristics selection for cooperative behaviour
New Journal of Physics, 2020 Situations involving cooperative behaviour are widespread among animals and humans alike. Game theory and evolutionary dynamics have provided the theoretical and computational grounds to understand what are the mechanisms that allow for such cooperation.
Felipe Maciel Cardoso +2 more
doaj +1 more source
A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms
Computational Intelligence and Neuroscience, 2016 Multiobjective evolutionary algorithms have incorporated surrogate models in order to reduce the number of required evaluations to approximate the Pareto front of computationally expensive multiobjective optimization problems.
Alan Díaz-Manríquez +3 more
semanticscholar +1 more source