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

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Pseudocode of artificial dragonfly algorithm. حسب Ghassan Ahmed Ali (17041488)

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The Hopfield artificial neural network algorithm. حسب Ghassan Ahmed Ali (17041488)

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Data_Sheet_1_Phase-wise evaluation and optimization of non-pharmaceutical interventions to contain the COVID-19 pandemic in the U.S..pdf حسب Xiao Zhou (122661)

Comparison of MAPE mean and RMSE mean for statistical significance. حسب Ghassan Ahmed Ali (17041488)

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Flow diagram of Wan Abdullah method for HNN. حسب Ghassan Ahmed Ali (17041488)

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G<i>m</i>R performance of various HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

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List of some parameters of the ADA-HNN- EB<i>k</i>SAT model. حسب Ghassan Ahmed Ali (17041488)

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<i>MAPE performance of various</i> HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

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RMSE performance of various HNN-EB<i>k</i>SAT models. حسب Ghassan Ahmed Ali (17041488)

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Flowchart for HNN-EB<i>k</i>SAT implementation procedure. حسب Ghassan Ahmed Ali (17041488)

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Training error and accuracy for all HNN models. حسب Ghassan Ahmed Ali (17041488)

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Implementation time performance of various HNN-EBkSAT models. حسب Ghassan Ahmed Ali (17041488)

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QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm حسب Z.Y. Algamal (5547620)

"…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"

Iteration curve of the optimization process. حسب Meijun Shang (22806461)

"…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …"

An exemplar procedure for activity flow modeling based on the direct and shortest paths at a network density of 15%. حسب Zhengdong Wang (35299)

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

"…<p>It is of great practical and theoretical significance to identify driver fatigue state in real time and accurately and provide active safety warning in time. In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"

Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

"…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. In addition, we compared four common machine learning algorithms, including naive Bayes, decision tree, K-nearest neighbors, support vector machine (SVM), and fully connected network. …"

Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

"…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. In addition, we compared four common machine learning algorithms, including naive Bayes, decision tree, K-nearest neighbors, support vector machine (SVM), and fully connected network. …"

Data Sheet 1_TBESO-BP: an improved regression model for predicting subclinical mastitis.pdf حسب Kexin Han (10933209)

"…The model is based on TBESO (Multi-strategy Boosted Snake Optimizer) and utilizes monthly Dairy Herd Improvement (DHI) data to forecast the status of subclinical mastitis in cows.…"