Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison of performance with complex continuous lines. by Yunhu Huang (21402795)

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MSE for ILSTM algorithm in binary classification. by 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. …”

Complex traffic line and track point diagram. by Mingkang Sun (6498791)

Complex traffic line and track point diagram. by Mingkang Sun (6498791)

Greedy optimization algorithm. by Alexis Bénichou (19832361)

Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

Parameters in algorithms. by Chao Li (145513)

“…Considering the constraints of operation and passenger flow demand, an integer nonlinear programming model is established to minimize the cost of operation and passenger waiting time. The model complexity is analyzed and based on its decomposability a deterministic search algorithm is designed. …”

DMTD algorithm. by Yunhu Huang (21402795)

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Comparison of line planning results. by Chao Li (145513)

“…Considering the constraints of operation and passenger flow demand, an integer nonlinear programming model is established to minimize the cost of operation and passenger waiting time. The model complexity is analyzed and based on its decomposability a deterministic search algorithm is designed. …”

Algorithm flow of BBO. by Jian Yang (12136)

“…This study introduces a comprehensive optimization design method for transmission line crossing frame structures based on the Biogeography-Based Optimization (BBO) algorithm, which integrates size, shape, and topology optimization. …”

Operation curve comparison among the EITO algorithms. by Yunhu Huang (21402795)

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Operation curve comparison among the EITO algorithms. by Yunhu Huang (21402795)

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Operation curve comparison among the five algorithms in the 95 s trip. by Yunhu Huang (21402795)

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Operation curve comparison among the five algorithms in the 115 s trip. by Yunhu Huang (21402795)

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Operation curve comparison among the five algorithms in the 101s trip. by Yunhu Huang (21402795)

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If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

EITO_P with flexible trip time. by Yunhu Huang (21402795)

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