Search alternatives:
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
primary base » primary case (Expand Search), primary cause (Expand Search), primary care (Expand Search)
binary atp » binary data (Expand Search)
atp driven » data driven (Expand Search), ai driven (Expand Search)
base model » based model (Expand Search), based models (Expand Search), game model (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
primary base » primary case (Expand Search), primary cause (Expand Search), primary care (Expand Search)
binary atp » binary data (Expand Search)
atp driven » data driven (Expand Search), ai driven (Expand Search)
base model » based model (Expand Search), based models (Expand Search), game model (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
Features selected by optimization algorithms.
Published 2024“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
-
7
-
8
-
9
Models’ performance without optimization.
Published 2024“…To enhance the performance of these models, Bayesian optimization techniques were employed. …”
-
10
-
11
Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement
Published 2019“…The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. …”
-
12
Descriptive statistics of algorithms.
Published 2024“…BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. …”
-
13
Routing policy based on path satisfaction.
Published 2025“…Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
-
14
-
15
Q-value of comparison of algorithms with WOA.
Published 2024“…BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. …”
-
16
p-values of comparison of algorithms with WOA.
Published 2024“…BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. …”
-
17
A portfolio selection model based on the knapsack problem under uncertainty
Published 2019“…This paper presents a knapsack based portfolio selection model where the expected returns, prices, and budget are characterized by interval values. …”
-
18
-
19
-
20