MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

One advantage of our algorithm is that it is not binary in nature. حسب Yong Kuk Kim (13955214)

Flowchart depicting the structure of the BDMO algorithm. حسب Olatunji A. Akinola (13919696)

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. حسب Tehnan I. A. Mohamed (16846175)

Principle of the SVM algorithm. حسب Anfeng Zhu (17817144)

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data حسب Changhun Kim (682542)

"…Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"

<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

Machine learning deployment strategies and schematic illustration of the proposed generative adversarial algorithm for domain adaptation. حسب Aly A. Valliani (13251484)

A* Path-Finding Algorithm to Determine Cell Connections حسب Max Weng (22327159)

"…The integration of heuristic optimization and machine learning significantly enhances both speed and precision in astrocyte data analysis. …"

Confusion matrix for multiclass classification. حسب Ebru Ergün (21395498)

"…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …"

General flow chart of the proposed method. حسب Ebru Ergün (21395498)

"…The experimental protocol involved eight participants performing tasks across four classes of scrolling text. To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. …"

Data_Sheet_1_Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence.PDF حسب Vito Janko (14605643)

Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. …"

Table_1_bSRWPSO-FKNN: A boosted PSO with fuzzy K-nearest neighbor classifier for predicting atopic dermatitis disease.docx حسب Yupeng Li (507508)

Fig 12 - حسب Nisha Yadav (366131)

Summary of LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

SHAP analysis for LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

Comparison of intrusion detection systems. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

Parameter setting for CBOA and PSO. حسب Asmaa Ahmed Awad (16726315)

"…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. …"

NSL-KDD dataset description. حسب Asmaa Ahmed Awad (16726315)

"…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. …"