Different meta-heuristic optimization techniques for feature selection
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Updated
May 19, 2020 - Python
Different meta-heuristic optimization techniques for feature selection
This is the repository of codes written in class.
Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators ser…
Regenerated a state-of-the-art meta-heuristic algorithm for the UAV path planning problem, proposed by Qu, Gai, and Zhong.
The codes for metaheuristic optimization algorithms
Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine
Implementation of three nature-inspired search algorithms: Bees Algorithm, Bat Algorithm, and Firefly Algorithm
Obtaining the best coefficients of Inverse Dynamics Controller, for a dynamical system, with Optimization Algorithms.
Implementation of metaheuristic optimization using population-based simulated annealing.
This paper presents an intelligent sizing method to improve the performance and efficiency of a CMOS Ring Oscillator (RO). The proposed approach is based on the simultaneous utilization of powerful and new multi-objective optimization techniques along with a circuit simulator under a data link. The proposed optimizing tool creates a perfect trad…
A study on swarm intelligence optimizing neural networks for workload elasticity prediction
Algorithmes de selection de variables pour préparer un apprentissage non supervisé. La version finale du programme est sélectionne les prédicteurs les plus pertinents en effectuant un apprentissage à chaque génération. La métrique optimisée (dans le cadre du dataset utilisé) est l'accuracy. Nous avons testé les deux métaheuristiques sur un datas…
a Simple Python Implementation of IAS Optimization Algorithm
A list of metaheuristics and links to their respective papers.
Implementation of Generic Algorithm
Implementation of multivariate regression and classification using an adaptive neuro-fuzzy inference system (Takaki-Sugeno) and metaheuristic optimization.
Metaheuristic Minimization Using Particle Swarm Optimization.
A new optimization method based on the dynamic of sliding motion along a frictionless inclined plane. In IPO, a collection of agents cooperate with each other and move toward better positions in the search space by employing Newton’s second law and equations of motion. The standard version of the IPO is presented by Mozafari et al. in 2016. Powe…
FAEICA-Algorithm (Fuzzy adaptive optimisation method)
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