Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
levels based » level based (Expand Search), models based (Expand Search), cells based (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
levels based » level based (Expand Search), models based (Expand Search), cells based (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based wolf » based whole (Expand Search), based work (Expand Search), based well (Expand Search)
-
1
Comparison of optimization results obtained for experimental classical benchmark functions.
Published 2022Subjects: -
2
-
3
Improved NSGA-II algorithm flowchart.
Published 2024“…<div><p>To address the issue of insufficiently comprehensive representation of service composition indexes in the shared manufacturing environment, service reliability, confidence, and other indexes are decomposed in detail to establish a composition evaluation system, and a shared manufacturing service composition optimization model based on bi-level programming is proposed. …”
-
4
-
5
Features selected by optimization algorithms.
Published 2024“…After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”
-
6
-
7
-
8
Function graph and algorithm iterative graph.
Published 2024“…This paper presents an effective technique to minimize the SLL and thus improve the radiation pattern of the linear antenna array (LAA) using the chaotic inertia-weighted Wild Horse optimization (IERWHO) algorithm. The wild horse optimizer (WHO) is a new metaheuristic algorithm based on the social behavior of wild horses. …”
-
9
Flowchart of proposed fitness function algorithm.
Published 2025“…The mathematical model was transformed into a fitness function and a solution was provided with the Tabu Search Algorithm and Simulated Annealing. …”
-
10
Performance of the three algorithms.
Published 2024“…An integrated framework based on a novel genetic algorithm and the Frank—Wolfe algorithm is designed to solve the stochastic model. …”
-
11
-
12
-
13
Impact of the resource level on the CVaR-R value.
Published 2024“…An integrated framework based on a novel genetic algorithm and the Frank—Wolfe algorithm is designed to solve the stochastic model. …”
-
14
-
15
-
16
-
17
-
18
-
19
Algorithm for generating hyperparameter.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
-
20