Results 251 to 260 of about 787,704 (278)

Reinforcement Learning Estimation of Distribution Algorithm

2003
This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions to generate a new population of solutions. We call it Reinforcement Learning Estimation of Distribution Algorithm (RELEDA).
Topon Kumar Paul, Hitoshi Iba
openaire   +1 more source

Memetic Algorithms of Graph-Based Estimation of Distribution Algorithms

2015
This paper constitutes Memetic Algorithms of the graph-based Estimation of Distribution algorithms which have been proposed by us previously. The graph-based EDA employs graph-kernels to estimate the probabilistic distributions of individuals, i.e., graphs. In this paper, a greedy-search is introduced into the graph-based EDA.
Kenta Maezawa, Hisashi Handa
openaire   +1 more source

Continuous Gaussian Estimation of Distribution Algorithm

2013
Metaheuristics algorithms such as Estimation of Distribution Algorithms use probabilistic modeling to generate candidate solutions in optimization problems. The probabilistic presentation and modeling allows the algorithms to climb the hills in the search space.
Shahram Shahraki, Mohammad Reza Akbarzadeh Tutunchy   +1 more
openaire   +1 more source

Estimation of Distribution Algorithms with Mutation

2005
The Estimation of Distribution Algorithms are a class of evolutionary algorithms which adopt probabilistic models to reproduce the genetic information of the next generation, instead of conventional crossover and mutation operations. In this paper, we propose new EDAs which incorporate mutation operator to conventional EDAs in order to keep the ...
openaire   +1 more source

Occupancy Estimation Using Thermal Imaging Sensors and Machine Learning Algorithms

IEEE Sensors Journal, 2021
Veena Chidurala, Xinrong Li
exaly  

Diversity Loss in General Estimation of Distribution Algorithms

2006
A very general class of EDAs is defined, on which universal results on the rate of diversity loss can be derived. This EDA class, denoted SML-EDA, requires two restrictions: 1) in each generation, the new probability model is build using only data sampled from the current probability model; and 2) maximum likelihood is used to set model parameters ...
openaire   +3 more sources

Metaheuristic Algorithms in Optimizing Deep Neural Network Model for Software Effort Estimation

IEEE Access, 2021
Muhammad Sufyan Khan, Farhana Jabeen, Sanaa Ghouzali   +2 more
exaly  

Comparisons on Kalman-Filter-Based Dynamic State Estimation Algorithms of Power Systems

IEEE Access, 2020
Hui Liu, Fei Hu, Jinshuo Su
exaly  

An introduction and survey of estimation of distribution algorithms

Swarm and Evolutionary Computation, 2011
Mark Hauschild, Martin Pelikan
exaly  

Estimation of particle swarm distribution algorithms: Combining the benefits of PSO and EDAs

Information Sciences, 2012
Chang-Wook Ahn
exaly