Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

Estimating Bridge Deterioration Age Using Artificial Neural Networks by AL HUSSEIN, ASEEL

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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series by Lasfer, Assia

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Modeling and thermoeconomic analysis of new polygeneration system based on geothermal energy with sea water desalination and hydrogen production by Wulaer Shaersaikai (21436652)

“…With strong R-squared values and high predictive accuracy, the Random Forest machine learning model predicts exergy efficiency, freshwater production, unit specific product cost (USPC), net present value (NPV), and environmental impact. …”

Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic by Saeed Al-Maroof, Rana

“…The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. The main hypotheses of this study are related to the effect of COVID-19 on the adoption of Google Meet as COVID-19 rise s various types of fear. …”
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Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings by Ahmad Yaser Alhaddad (7017434)

“…Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. …”

Design and Analysis of Secure Digital Twin Architecture by Shaikh, Eman

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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…We build our model using machine learning techniques in particular rule-based models. …”
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PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

“…Next, we constructed conversation threads and used the toxicity prediction results to build a training set for detecting toxicity triggers. …”

Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics by Abbas Khan (5141000)

“…Hence, the current study focuses on the screening of clinically reported substitutions in the <i>RAF1</i> and <i>RAP1A</i> genes using predictive algorithms integrated with all‐atoms simulation, essential dynamics, and binding free energy methods. …”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. Additionally, personalized medicine promises to revolutionize healthcare, with its key goal of providing the right treatment to the right patient at the right time and dose, and thus the potential of improving quality of life and helping to bring down healthcare costs.…”