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Differential Evolution with DEoptim [PDF]
The R Journal, 2011 The R package DEoptim implements the Differential Evolution algorithm. This algorithm is an evolutionary technique similar to classic genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex ...
Ardia, David +4 more
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Comparison Four Different Probability Sampling Methods based on Differential Evolution Algorithm
Journal of Advances in Information Technology, 2012 Differential Evolution (DE) is one kind of evolution algorithm, which based on difference of individuals. DE has exhibited good performance on optimization problem.
Qingbo Lu +3 more
doaj +1 more source
Differential Evolution for Many-Particle Adaptive Quantum Metrology [PDF]
, 2013 We devise powerful algorithms based on differential evolution for adaptive many-particle quantum metrology. Our new approach delivers adaptive quantum metrology policies for feedback control that are orders-of-magnitude more efficient and surpass the few-
Crosnier, Cécile +3 more
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The Auxiliary Mass Method beyond the Local Potential Approximation [PDF]
, 1999 We show that the evolution equation of the effective potential in the auxiliary mass method corresponds to a leading approximation of a certain series. This series is derived from an evolution equation of an effective action using a derivative expansion.
Aoki +36 more
core +3 more sources
Shock and Vibration, 2021 Variational mode decomposition is an adaptive nonrecursive signal decomposition and time-frequency distribution estimation method. The improper selection of the decomposition number will cause under decomposition or over decomposition, and the improper ...
Yuanxin Wang
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Adaptive Distributed Differential Evolution
IEEE Transactions on Cybernetics, 2020 Due to the increasing complexity of optimization problems, distributed differential evolution (DDE) has become a promising approach for global optimization. However, similar to the centralized algorithms, DDE also faces the difficulty of strategies' selection and parameters' setting.
Zhi-Hui Zhan +3 more
openaire +3 more sources
Keck Deep Fields. II. The UV Galaxy Luminosity Function at z~4, 3, and 2 [PDF]
, 2006 We use very deep UGRI multi-field imaging obtained at the Keck telescope to study the evolution of the rest-frame 1700A galaxy luminosity function as the Universe doubles its age from z~4 to z~2.
David Thompson +3 more
core +2 more sources
Reservoir optimization with differential evolution
Vietnam Journal of Mechanics, 2016 Reservoir optimization, is one of recent problems, which has been researched by several methods such as Linear Programming (LP), Non-linear Programming (NLP), Genetic Algorithm (GA), and Dynamic Programming (DP). Differential Evolution (DE), a method in
Phan Thi Thu Phuong +2 more
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Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning. [PDF]
PLoS ONE, 2016 The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover ...
Kai Yit Kok, Parvathy Rajendran
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Hybrid Harmony Search Differential Evolution Algorithm
IEEE Access, 2021 Differential evolution (DE) algorithm has some excellent attributes including strong exploration capability. However, it cannot balance the exploitation with exploration ability in the search process.
Liyun Fu +4 more
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