Metaheuristics in large-scale global continues optimization: A survey
Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …
dimensional optimization problems. These algorithms provide effective tools with important …
[PDF][PDF] A Comprehensive Survey of Machine Learning in Healthcare: Predicting Heart and Liver Disease, Tuberculosis Detection in Chest X-Ray Images
C Banapuram, AC Naik, MK Vanteru… - … Journal of Electronics …, 2024 - researchgate.net
The utilization of Machine Learning (ML) has become widespread across several
disciplines. ML is utilized as an effective support mechanism in clinical diagnostics due to …
disciplines. ML is utilized as an effective support mechanism in clinical diagnostics due to …
Enhancing particle swarm optimization using generalized opposition-based learning
Particle swarm optimization (PSO) has been shown to yield good performance for solving
various optimization problems. However, it tends to suffer from premature convergence …
various optimization problems. However, it tends to suffer from premature convergence …
A hybrid artificial immune optimization for high-dimensional feature selection
Y Zhu, W Li, T Li - Knowledge-Based Systems, 2023 - Elsevier
For high-dimensional data, the traditional feature selection method is slightly inadequate. At
present, most of the existing hybrid search methods have problems of high computational …
present, most of the existing hybrid search methods have problems of high computational …
A hybrid machine learning algorithm for heart and liver disease prediction using modified particle swarm optimization with support vector machine
MP Behera, A Sarangi, D Mishra, SK Sarangi - Procedia Computer Science, 2023 - Elsevier
Abstract Machine learning is now extensively applied in a variety of fields. Machine learning
is employed like an efficient assistance mechanism in clinical diagnostics since vast …
is employed like an efficient assistance mechanism in clinical diagnostics since vast …
Opposition-based particle swarm algorithm with Cauchy mutation
Particle swarm optimization (PSO) has shown its fast search speed in many complicated
optimization and search problems. However, PSO could often easily fall into local optima …
optimization and search problems. However, PSO could often easily fall into local optima …
Chaos-induced and mutation-driven schemes boosting salp chains-inspired optimizers
Q Zhang, H Chen, AA Heidari, X Zhao, Y Xu… - Ieee …, 2019 - ieeexplore.ieee.org
Salp swarm algorithm (SSA) is a newly developed meta-heuristic algorithm, which is mainly
developed based on the swarming behavior of salps sailing and foraging in the ocean. An …
developed based on the swarming behavior of salps sailing and foraging in the ocean. An …
A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques
Particle swarm optimization is a stochastic population-based algorithm based on social
interaction of bird flocking or fish schooling. In this paper, a new adaptive inertia weight …
interaction of bird flocking or fish schooling. In this paper, a new adaptive inertia weight …
An improved particle swarm optimisation algorithm applied to battery sizing for stand-alone hybrid power systems
Stand-alone hybrid power systems with renewable energies are an economic alternative to
the main electricity grid where the extension of the grid is too costly or the small local …
the main electricity grid where the extension of the grid is too costly or the small local …
Capacitor placement of distribution systems using particle swarm optimization approaches
Capacitor placement plays an important role in distribution system planning and operation.
In distribution systems of electrical energy, banks of capacitors are widely installed to …
In distribution systems of electrical energy, banks of capacitors are widely installed to …