Fig 3 - by Ryan J. Haasl (3259872)

Supplementary file 1_Enhancing dissolved oxygen prediction in lake-reservoirs via a hybrid BO+SSA-driven backpropagation neural network.docx by Hanyi Liu (10227785)

“…In this study, a new hybrid optimization technology called Bayesian Optimization (BO) + improved Sparrow Search Algorithm (SSA), named BO+SSA, is employed to optimize the hyperparameters of BPNN and search initial weights and thresholds to overcome such a problem. …”

Table 1_Composition-centered prediction of kenaf core saccharification for next-generation bioethanol via machine learning.docx by Yitong Niu (22658927)

“…The curated dataset (n = 35) was used to train Random-Forest regressors tuned by six hyperparameter optimizers (grid search, random search, Bayesian optimization, genetic algorithm, particle swarm optimization, and simulated annealing). …”

Data from: Enhancing Evapotranspiration Estimates in Composite Terrain Through the Integration of Satellite Remote Sensing and Eddy Covariance Measurements by Ali Karbalaye Ghorbanpour (20723321)

“…The approach was evaluated at four sites in California, each representing different land uses. Parameter optimization was achieved through Bayesian inference using the Differential Evolution Adaptive Metropolis (DREAM) algorithm, which minimized discrepancies between ET estimates derived from Landsat 8 and 9 imagery and the observed ET from EC measurements. …”

Data Sheet 2_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Data Sheet 1_Early stroke detection through machine learning in the prehospital setting.pdf by María Ríos Delgado (22004942)

Table 1_Early stroke detection through machine learning in the prehospital setting.xlsx by María Ríos Delgado (22004942)

Data Sheet 1_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf by Habtamu Setegn Ngusie (12178327)

“…The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …”

Data Sheet 2_Predicting place of delivery choice among childbearing women in East Africa: a comparative analysis of advanced machine learning techniques.pdf by Habtamu Setegn Ngusie (12178327)

“…The findings showed that the support vector machine (SVM) algorithm and CatBoost performed best in predicting the place of delivery, in which both of those algorithms scored an accuracy of 95% and an AUC of 0.98 after optimized with Bayesian optimization tuning and insignificant difference between them in all comprehensive analysis of metrics performance. …”

Examples of model selection methods for the PHMM. by Tianshu Li (1527088)

Mean and root mean square errors of DOA estimate. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Coprime array with interpolated array elements. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Schematic diagram of maritime array arming. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Variation of RMSE with the number of snapshots. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Velocity of sound profile. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Variation of RMSE with input SNR. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Coprime array. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Variation of RMSE with different grid spacing. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Spatial power spectrum of compact sound source. by Chuanxi Xing (20141665)

“…<div><p>This letter presents a novel approach to sparse Bayesian underwater acoustic signal direction estimation. …”

Properties of A286 steel. by Ameer Malik Shaik (21263019)

“…Bayesian Ridge regression outperformed other models, achieving an R² of 0.99849 and RMSE of 0.00049, confirming its robustness in capturing corrosion trends. …”