Results 231 to 240 of about 6,130,994 (293)
An explicit constitutive reconstruction framework enables accurate tensile characterization of miniaturized additively manufactured specimens using only the grip‐to‐grip displacement measurements. Progressive validation through self‐consistency, analytical comparison, and inverse finite element method (iFEM) benchmarking demonstrates constitutive ...
Junqing Leng +4 more
wiley +1 more source
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source
CT‐based finite element simulations combined with in situ X‐ray computed tomography are used to analyze insert pull‐out in nickel‐coated polymer foams. Despite variations in material parameters, deformation consistently concentrates within a narrow annular region around the insert.
Yannik Bautz +4 more
wiley +1 more source
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A Fuzzy Adaptive Differential Evolution Algorithm
Soft Computing, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
J Lampinen
exaly +2 more sources
Rethinking the differential evolution algorithm
Service Oriented Computing and Applications, 2020Selection operation plays a significant role in differential evolution algorithm. A new differential evolution algorithm based on an improved selection process is presented in this work. It was studied that there was neither a practical method to maintain the distribution of population nor a correction to the variables out of bounds in mutation process
Hongwei Liu, Xiang Li 0070, Wenyin Gong
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A Parallel Differential Evolution Algorithm A Parallel Differential Evolution Algorithm
International Symposium on Parallel Computing in Electrical Engineering (PARELEC'06), 2006In the paper the problem of using a differential evolution algorithm for feed-forward neural network training is considered. A new parallelization scheme for the computation of the fitness function is proposed. This scheme is based on data decomposition.
Wojciech Kwedlo, Krzysztof Bandurski
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THE PARETO DIFFERENTIAL EVOLUTION ALGORITHM
International Journal on Artificial Intelligence Tools, 2002The use of evolutionary algorithms (EAs) to solve problems with multiple objectives (known as Vector Optimization Problems (VOPs)) has attracted much attention recently. Being population based approaches, EAs offer a means to find a group of pareto-optimal solutions in a single run.
Hussein A. Abbass, Ruhul A. Sarker
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An adaptive differential evolution algorithm
2011 IEEE Congress of Evolutionary Computation (CEC), 2011The performance of Differential Evolution (DE) algorithm is significantly affected by its parameter setting. But the choice of parameters is heavily dependent on the problem characteristics. Therefore, recently a couple of adaptation schemes that automatically adjust DE parameters have been proposed.
Nasimul Noman +2 more
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Cellular Differential Evolution Algorithm
2010This paper presents a cellular version of Differential Evolution (DE) algorithm. The notion behind the geographical distribution of DE population with local interaction is to study the influence of slow diffusion of information throughout the population.
Nasimul Noman, Hitoshi Iba
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