The comparison of different optimization models. by Jiefei Zhang (8787494)

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The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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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. …”

Greedy optimization algorithm. by Alexis Bénichou (19832361)

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

Parameters in algorithms. by Chao Li (145513)

“…The model complexity is analyzed and based on its decomposability a deterministic search algorithm is designed. …”

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

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DataSheet1_Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.docx by Ying Sun (23237)

“…In this paper, a genetic algorithm-based optimization method for ladle refractory lining structure is proposed. …”

Dimensions of the calculated model. by Dapeng Wang (250459)

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

“…The model complexity is analyzed and based on its decomposability a deterministic search algorithm is designed. …”

Spearman correlation coefficient results for classification algorithms (predicted probabilities) and regression algorithms (predicted IC50 values). by Sofia P. Miranda (11418930)

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Optimal schemes for different resource limitations. by Jiefei Zhang (8787494)

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SUNRISE hybrids obtained from 36 maintainer lines (females, rows) crossed to 36 restorer lines (males, columns). by Brigitte Mangin (336874)

Example medication days generated for patients P4 and P6, medication times (red dots), patient’s state—TRS score (blue line) with bounds for the states (red lines) and optimal stat... by Tomasz Gutowski (17200042)

Average running time line graph of different algorithms. by Wuyi Li (2984439)

The parameters of model. by Jiefei Zhang (8787494)

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Cracked tunnel-strata coupled finite element model. by Dapeng Wang (250459)

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Classification results for all subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

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Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

“…Then, a novel molecular property prediction model, called a multiembedding-based synthetic network (MESN), was generated by applying a deep learning algorithm based on the synthesis of multiple types of molecular embeddings. …”

Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

“…Then, a novel molecular property prediction model, called a multiembedding-based synthetic network (MESN), was generated by applying a deep learning algorithm based on the synthesis of multiple types of molecular embeddings. …”