Primary training parameters for the model. by Junjie Lu (160350)

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

Subjects:

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

Subjects:

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

Subjects:

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

Subjects:

Improving Gibberellin GA₃ Production with the Construction of a Genome-Scale Metabolic Model of Fusarium fujikuroi by Ya-Wen Li (1733782)

Subjects:

DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx by Dongdong Li (123985)

“…The optimization model is solved by the multi-objective salp swarm algorithm (MSSA) to obtain the setting value of wind-storage combined frequency regulation parameters and the optimal energy storage capacity. …”

Table_1_Optimal Reopening Pathways With COVID-19 Vaccine Rollout and Emerging Variants of Concern.pdf by Yanyu Xiao (682443)

The baseline case–the model in the absence of sentinel plants. by Francesca A. Lovell-Read (14378253)

<b>Spatial modeling of gully density on the Qinghai-Tibet Plateau: Application of hyperparameter optimization in interpretable machine learning</b> by Zhoujiang Liu (22741966)

“…Various machine learning models were used, and different hyperparameter optimization algorithms were selected to train the models to obtain the best model. …”

Table_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.xlsx by Xinping Lin (1591438)

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)

“…The optimal ML model was selected to be DAMS. In addition, SHapley Additive exPlanations (SHAP) approach was introduced to rank the feature importance. …”

Image_1_A cost-effective, machine learning-driven approach for screening arterial functional aging in a large-scale Chinese population.JPEG by Rujia Miao (12075653)

Table_1_A cost-effective, machine learning-driven approach for screening arterial functional aging in a large-scale Chinese population.DOC by Rujia Miao (12075653)

Data_Sheet_1_Tobacco shred varieties classification using Multi-Scale-X-ResNet network and machine vision.docx by Qunfeng Niu (13263975)

“…By increasing the multi-scale structure and optimizing the number of blocks and loss function, a new tobacco shred image classification method is proposed based on the MS-X-ResNet (Multi-Scale-X-ResNet) network. …”

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

Simulation study of district heating control based on load forecasting by Bingwen Zhao (13192882)

“…Based on the high-precision heating load prediction model of thermal power station, the primary side flow as the control variable, secondary return temperature as the controlled variable, and the generalized predictive control (GPC) algorithm as the control method, the secondary return temperature of the target system is accurately controlled; at the same time, particle swarm optimization (PSO) is used to determine parameters adaptively for parameter tuning in GPC; and the control strategy is simulated. …”

Table_1_Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation.DOCX by Arto J. Hautala (3072576)

“…ECR was programmed in accordance with international guidelines. Risk analysis algorithms (cross-decomposition algorithms) were employed to rank risk factors based on variances in their effects. …”

A CemOrange2 marker co-localizes a mutant ABC transporter protein to the ER. by Brian J. Thomas (6508961)

Supplementary report for "Full-reference stereoscopic video quality assessment using a motion sensitive HVS model" by Chathura Galkandage (7185236)

“…The proposed HVS model generalises previous HVS models, which characterised the behaviour of simple and complex cells but ignored motion sensitivity, by estimating optical flow to measure scene velocity at different scales and orientations. …”