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moradabadi--behnaz
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Designing an Estimation of Distribution Algorithm based on Learning Automata
, M.Sc. Thesis Sharif University of Technology ; Beigy, Hamid (Supervisor)
Abstract
Evolutionary algorithms are a type of stochastic optimization techniques influenced by genetics and natural evolution. Once the set of candidate solutions has been selected, a new generation is sampled by using recombination (crossover) and mutation operators to the candidate solutions. Public, fixed, problem independent mutation and recombination operators frequently lead to missing building blocks, knowledge of the relationship between variables and result in converging to a local optimum. A method to prevent disruption of building blocks is using the estimation of distribution algorithms (EDAs). The experimental results show that EDAs is capable to identify correct linkage between the...
A new real-coded Bayesian optimization algorithm based on a team of learning automata for continuous optimization
, Article Genetic Programming and Evolvable Machines ; Vol. 15, Issue. 2 , 2014 , pp. 169-193 ; ISSN: 13892576 ; Beigy, H ; Sharif University of Technology
2014
Abstract
Estimation of distribution algorithms have evolved as a technique for estimating population distribution in evolutionary algorithms. They estimate the distribution of the candidate solutions and then sample the next generation from the estimated distribution. Bayesian optimization algorithm is an estimation of distribution algorithm, which uses a Bayesian network to estimate the distribution of candidate solutions and then generates the next generation by sampling from the constructed network. The experimental results show that the Bayesian optimization algorithms are capable of identifying correct linkage between the variables of optimization problems. Since the problem of finding the...
An improved real-coded bayesian optimization algorithm for continuous global optimization
, Article International Journal of Innovative Computing, Information and Control ; Volume 9, Issue 6 , 2013 , Pages 2505-2519 ; 13494198 (ISSN) ; Beigy, H ; Ahn, C. W ; Sharif University of Technology
2013
Abstract
Bayesian optimization algorithm (BOA) utilizes a Bayesian network to estimate the probability distribution of candidate solutions and creates the next generation by sampling the constructed Bayesian network. This paper proposes an improved real-coded BOA (IrBOA) for continuous global optimization. In order to create a set of Bayesian networks, the candidate solutions are partitioned by an adaptive clustering method. Each Bayesian network has its own structure and parameters, and the next generation is produced from this set of networks. The adaptive clustering method automatically determines the correct number of clusters so that the probabilistic building-block crossover (PBBC) is...
Investigation of the Synergism Between Engineered Stem Cells with Vtk Containing Construct and Electrical Stimulation in Osteogenic Differentiation
, M.Sc. Thesis Sharif University of Technology ; Alemzadeh, Iran (Supervisor) ; Bakhshandeh, Behnaz (Supervisor) ; Saadatmand, Maryam (Co-Supervisor)
Abstract
In recent years, advances in medical science and increasing the level of healthcare have increased the life expectancy index; But in the meantime, a phenomenon called “diseases related to life expectancy” has appeared. Bone and skeletal diseases have a significant share in this category because the passage of time reduces bone mineral density and this is the source of many diseases, including osteoporosis. Current bone therapies, which include autologous and allogeneic bone grafts, will not meet this high need. Bone tissue engineering has been proposed as a potential alternative to solve this challenge. In bone tissue engineering, the essential components required for bone formation and...