Machine learning at the service of meta-heuristics for solving combinatorial optimization problems: A state-of-the-art
In recent years, there has been a growing research interest in integrating machine learning
techniques into meta-heuristics for solving combinatorial optimization problems. This …
techniques into meta-heuristics for solving combinatorial optimization problems. This …
Artificial olfactory sensor technology that mimics the olfactory mechanism: A comprehensive review
Artificial olfactory sensors that recognize patterns transmitted by olfactory receptors are
emerging as a technology for monitoring volatile organic compounds. Advances in statistical …
emerging as a technology for monitoring volatile organic compounds. Advances in statistical …
A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms
Evolutionary algorithms are widely used for solving multiobjective optimization problems but
are often criticized because of a large number of function evaluations needed …
are often criticized because of a large number of function evaluations needed …
Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus
Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …
Neural network classifier optimization using differential evolution with global information and back propagation algorithm for clinical datasets
Abstract A Computer-Aided Diagnostic (CAD) system that uses Artificial Neural Network
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
(ANN) trained by drawing in the relative advantages of Differential Evolution (DE), Particle …
Epidemiology of lung cancer and approaches for its prediction: a systematic review and analysis
Background Owing to the use of tobacco and the consumption of alcohol and adulterated
food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since …
food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since …
DESDEO: The modular and open source framework for interactive multiobjective optimization
Interactive multiobjective optimization methods incorporate preferences from a human
decision maker in the optimization process iteratively. This allows the decision maker to …
decision maker in the optimization process iteratively. This allows the decision maker to …
A survey on dendritic neuron model: Mechanisms, algorithms and practical applications
Research on dendrites has been conducted for decades, providing valuable information for
the development of dendritic computation. Creating an ideal neuron model is crucial for …
the development of dendritic computation. Creating an ideal neuron model is crucial for …
CAPSO: centripetal accelerated particle swarm optimization
Z Beheshti, SMH Shamsuddin - Information Sciences, 2014 - Elsevier
Meta-heuristic search algorithms are developed to solve optimization problems. Such
algorithms are appropriate for global searches because of their global exploration and local …
algorithms are appropriate for global searches because of their global exploration and local …
A cluster-based intelligence ensemble learning method for classification problems
Classification is a vital task in machine learning. By learning patterns of samples of known
categories, the model can develop the ability to distinguish the categories of samples of …
categories, the model can develop the ability to distinguish the categories of samples of …