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Estimation of distribution algorithms in machine learning: a survey
The automatic induction of machine learning models capable of addressing supervised
learning, feature selection, clustering, and reinforcement learning problems requires …
learning, feature selection, clustering, and reinforcement learning problems requires …
A multiobjective evolutionary algorithm using Gaussian process-based inverse modeling
To approximate the Pareto front, most existing multiobjective evolutionary algorithms store
the nondominated solutions found so far in the population or in an external archive during …
the nondominated solutions found so far in the population or in an external archive during …
Multiobjective estimation of distribution algorithm based on joint modeling of objectives and variables
This paper proposes a new multiobjective estimation of distribution algorithm (EDA) based
on joint probabilistic modeling of objectives and variables. This EDA uses the …
on joint probabilistic modeling of objectives and variables. This EDA uses the …
Convergence analysis and performance of an improved gravitational search algorithm
S Jiang, Y Wang, Z Ji - Applied Soft Computing, 2014 - Elsevier
Gravitational search algorithm (GSA) has been shown to yield good performance for solving
various optimization problems. However, it tends to suffer from premature convergence and …
various optimization problems. However, it tends to suffer from premature convergence and …
Fuzzy convolutional deep-learning model to estimate the operational risk capital using multi-source risk events
Operational Risk (OR) is usually caused by losses due to human errors, inadequate or
defective internal processes, system failures or external events that affect an organization …
defective internal processes, system failures or external events that affect an organization …
Estimation distribution algorithms on constrained optimization problems
Estimation distribution algorithm (EDA) is an evolution technique that uses sampling to
generate the offspring. Most developed EDAs focus on solving the optimization problems …
generate the offspring. Most developed EDAs focus on solving the optimization problems …
A novel single multiplicative neuron model trained by an improved glowworm swarm optimization algorithm for time series prediction
H Cui, J Feng, J Guo, T Wang - Knowledge-Based Systems, 2015 - Elsevier
To better predict time series, in this paper the single multiplicative recurrent neuron (SMRN)
is constructed by adding feedforward and feedback links at the nodes of the original single …
is constructed by adding feedforward and feedback links at the nodes of the original single …
Gravitational search algorithm with both attractive and repulsive forces
The gravitational search algorithm (GSA) is a meta-heuristic optimization algorithm which is
inspired by the gravity force. This algorithm uses Newton's gravity and motion laws to …
inspired by the gravity force. This algorithm uses Newton's gravity and motion laws to …
A Gaussian estimation of distribution algorithm with random walk strategies and its application in optimal missile guidance handover for multi-UCAV in over-the …
X Wang, H Zhao, T Han, Z Wei, Y Liang, Y Li - IEEE Access, 2019 - ieeexplore.ieee.org
To overcome the premature convergence caused by the ill-distribution of solutions in the
basic Gaussian estimation of distribution algorithm (GEDA), this paper explores a novel …
basic Gaussian estimation of distribution algorithm (GEDA), this paper explores a novel …
Anisotropic adaptive variance scaling for Gaussian estimation of distribution algorithm
Traditional Gaussian estimation of distribution algorithms (EDAs) are confronted with issues
that the variable variances decrease fast and the main search direction tends to become …
that the variable variances decrease fast and the main search direction tends to become …