Nature-inspired metaheuristic optimization algorithms, e.g., the butterfly algorithm (BOA), have become increasingly popular. The BOA, which adapts food foraging and social behaviors of butterflies, involves randomly defined, algorithmic-dependent parameters that affect exploration exploitation strategies, negatively influences overall performance algorithm. To address this issue improve perfor...

Since chaos systems generally have the intrinsic properties of sensitivity to initial conditions, topological mixing and density of periodic orbits, they may tactfully use the chaotic ergodic orbits to achieve the global optimum or their better approximation to given cost functions with high probability. During the past decade, they have increasingly received much attention from academic commun...

This paper introduces hybridization of particle swarm optimization (PSO) with genetic algorithm (GA) denoted as PSO+GA provides an efficient approach which is used to solve non linear chaotic datasets. The proposed algorithm employed in probabilistic neural network(PNN) which is a variant of radial basic function artificial neural network (RBFANN) for finding precise value spread factor for acc...

The proposed approach brings up a manner of cognitiveness that inherits a paradigm in particle swarm optimization to implement a chaotic mapping and enhanced by K-means clustering algorithm. In this work, named KCPSO, chaotic mapping with ergodicity, irregularity and the stochastic properties in PSO contributes to global search while K-means with clustering properties in PSO results in rapid co...

Aim at the class electromagnetic algorithm (EM) late for “mining” ability is insufficient, solution precision is not higher, and easy in premature problem, this paper proposes a combination of chaotic map and confined quasi-Newton (L-BFGS) local optimization operator of the chaotic class electromagnetism algorithm. Its main idea is in the late class electromagnetism algorithm using limit domain...

Among most machine learning algorithms for optimization problem including meta-heuristic search algorithms, the solution is drawn like a moth to a flame and cannot keep away. The track of chaotic variable can travel ergodically over the whole search space. In general, the chaotic variable has special characters, i.e., ergodicity, pseudo-randomness and irregularity. To enrich the searching behav...

Given that the basic cuckoo search algorithm is vulnerable to local optimum and unsatisfactory calculation precision, chaotic operator (CO), employed as local algorism to optimize elitist individuals in the population, can effectively enhance the properties of cuckoo search (CS) algorithm. Tested by 15 benchmark high-dimensional functions, the experiment result indicates that chaotic cuckoo sea...

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find...