Texas Rio Grande Valley Red–crowned Parrot predicted general use habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence... by Elise Varaela Voltura (17592996)

Texas Rio Grande Valley Red–crowned Parrot predicted roost site habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence)... by Elise Varaela Voltura (17592996)

Texas Rio Grande Valley Red–crowned Parrot predicted nest site habitat distribution as determined via a consensus-based feature ensemble of 12 calibrated (binary presence/absence)... by Elise Varaela Voltura (17592996)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”

The overlap of Texas Rio Grande Valley Red–crowned Parrot predicted general use, roost site, and nest site habitat distributions as determined using consensus-based feature ensembl... by Elise Varaela Voltura (17592996)

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)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”

Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. by Doaa Sami Khafaga (21463870)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

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

Subjects:

DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

Test results of different algorithms. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Testing algorithm for modified 2-tiered approaches to Lyme disease diagnosis. by Richard Porwancher (11413931)

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

“…<b>K)</b> Algorithm selection from all models. <b>L)</b> Random forest selection. …”

The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

“…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”