Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Differential Evolution: A review of more than two decades of research
Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …
frequently used algorithms for solving complex optimization problems. Its flexibility and …
Recent advances in differential evolution–an updated survey
Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
[HTML][HTML] An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems
Abstract Teaching–Learning-Based Optimization (TLBO) algorithms simulate the teaching–
learning phenomenon of a classroom to solve multi-dimensional, linear and nonlinear …
learning phenomenon of a classroom to solve multi-dimensional, linear and nonlinear …
Differential evolution with ranking-based mutation operators
Differential evolution (DE) has been proven to be one of the most powerful global numerical
optimization algorithms in the evolutionary algorithm family. The core operator of DE is the …
optimization algorithms in the evolutionary algorithm family. The core operator of DE is the …
Review of differential evolution population size
AP Piotrowski - Swarm and Evolutionary Computation, 2017 - Elsevier
Abstract Population size of Differential Evolution (DE) algorithms is often specified by user
and remains fixed during run. During the first decade since the introduction of DE the …
and remains fixed during run. During the first decade since the introduction of DE the …
Optimal distributed renewable generation planning: A review of different approaches
Distributed generation has gained a lot of attractions in the power sector due to its ability in
power loss reduction, increased reliability, low investment cost, and most significantly, to …
power loss reduction, increased reliability, low investment cost, and most significantly, to …
A novel differential evolution based clustering algorithm for wireless sensor networks
Clustering is an efficient topology control method which balances the traffic load of the
sensor nodes and improves the overall scalability and the life time of the wireless sensor …
sensor nodes and improves the overall scalability and the life time of the wireless sensor …
[HTML][HTML] K-means-based nature-inspired metaheuristic algorithms for automatic data clustering problems: Recent advances and future directions
K-means clustering algorithm is a partitional clustering algorithm that has been used widely
in many applications for traditional clustering due to its simplicity and low computational …
in many applications for traditional clustering due to its simplicity and low computational …
Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference
Structural damage identification can be considered as an optimization problem, by defining
an appropriate objective function relevant to structural parameters to be identified with …
an appropriate objective function relevant to structural parameters to be identified with …
A cluster-based differential evolution with self-adaptive strategy for multimodal optimization
Multimodal optimization is one of the most challenging tasks for optimization. It requires an
algorithm to effectively locate multiple global and local optima, not just single optimum as in …
algorithm to effectively locate multiple global and local optima, not just single optimum as in …