Search alternatives:
small optimization » swarm optimization (Expand Search), whale optimization (Expand Search), spatial optimization (Expand Search)
case optimization » based optimization (Expand Search), phase optimization (Expand Search), dose optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based small » based smart (Expand Search), based sample (Expand Search)
based case » base case (Expand Search), based cancer (Expand Search)
small optimization » swarm optimization (Expand Search), whale optimization (Expand Search), spatial optimization (Expand Search)
case optimization » based optimization (Expand Search), phase optimization (Expand Search), dose optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based small » based smart (Expand Search), based sample (Expand Search)
based case » base case (Expand Search), based cancer (Expand Search)
-
1
-
2
-
3
-
4
MSE for ILSTM algorithm in binary classification.
Published 2023“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
-
5
-
6
-
7
-
8
-
9
-
10
-
11
-
12
-
13
-
14
-
15
Datasets and their properties.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
-
16
Parameter settings.
Published 2023“…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …”
-
17
-
18
-
19
-
20
Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…From this, we propose: (i) a new ILP model, and (ii) a new solution representation, which, unlike the reference work, guarantees that feasible solutions are obtained throughout the generation of new individuals. Based on this new representation, we proposed and evaluated other approximate methods, including a greedy algorithm and a genetic algorithm that improve the state-of-the-art results for test cases usually used in the literature. …”