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

Subjects:

Greedy optimization algorithm. by Alexis Bénichou (19832361)

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. …”

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. …”

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

Subjects:

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

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

Subjects:

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. …”

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. …”

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)

Subjects:

Line chart of influence propagation results of different algorithms when propagation probability p = 0.01. by Lihong Han (7280045)

Flowchart of the model solution. by Jiefei Zhang (8787494)

Subjects:

Sensitivity analysis of the TV-BayesOpt algorithm with a forgetting (orange line) or a forgetting-periodic (blue line) covariance function for a range of ε values. by John E. Fleming (8533956)

SIFs amplitude of cracks in lining at different depths. by Dapeng Wang (250459)

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

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