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. …"

The architecture of LSTM cell. 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. …"

The architecture of ILSTM. 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 LSTM. 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. …"

LITNET-2020 data splitting approach. 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. …"

Transformation of symbolic features in NSL-KDD. 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. …"

A new fast filtering algorithm for a 3D point cloud based on RGB-D information حسب Chaochuan Jia (7256237)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب Jianfang Cao (1881379)

the functioning of BRPSO. حسب Hossein Jarrahi (22530251)

Characteristic of 6- and 10-story SMRF [99,98]. حسب Hossein Jarrahi (22530251)

The RFD’s behavior mechanism (2002). حسب Hossein Jarrahi (22530251)

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

Schematic representation of semi-automated algorithm for organoids analyzing. حسب Anna Demchenko (18449439)

Comparison in terms of the sensitivity. حسب Ying Li (38224)

Parameter sensitivity of BIMGO. حسب Ying Li (38224)

Details of the medical datasets. حسب Ying Li (38224)

The flowchart of IMGO. حسب Ying Li (38224)

Comparison in terms of the selected features. حسب Ying Li (38224)

Iterative chart of control factor. حسب Ying Li (38224)

Details of 23 basic benchmark functions. حسب Ying Li (38224)