Contribution of hydrogeological, well logs and machine learning in predicting the aquifer hydraulic properties in arid regions: a case study of Nubian Sandstone aquifer, Farafra Oa... by Ahmed Nosair, Muhammad Nabih, Ahmed Bakry

“…Traditionally, these parameters are obtained through pumping tests and well log data. …”
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A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset by Rulyansyah Permata Putra, Amarudin Amarudin

“…Each algorithm was trained using tuned parameters, and performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and an analysis of training and prediction time. …”
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Modeling of biodiesel production using optimization designs from literature: aiming to reduce the laboratory workload by Iver Bergh Hvidsten, Kristian Hovde Liland, Oliver Tomic, Jorge Mario Marchetti

“…Random forest (RF) and gradient boosting regressor (GBR) models were employed to predict biodiesel yield across the various reaction systems. …”
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Emotion recognition with multiple physiological parameters based on ensemble learning by Yilong Liao, Yuan Gao, Fang Wang, Li Zhang, Zhenrong Xu, Yifan Wu

“…This study presents an innovative approach to emotion recognition using multiple physiological parameters, demonstrating the potential of ensemble learning for complex tasks. …”
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Machine Learning and Parameter Optimization for Banking Stability Prediction and Determinants Identification in ASEAN by Pham Thuy Tu, Dao Le Kieu Oanh, Do Doan Trang

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Rhizosphere Growth-Promoting Fungi of Healthy <i>Nicotiana tabacum</i> L.: A Systematic Approach to Boosting Plant Growth and Drought Resistance by Quanyu Yin, Zhao Feng, Zhichao Ren, Ao Li, Amit Jaisi, Mengquan Yang

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Prohexadione calcium and KH2PO4 synergy optimizes pod pepper plant architecture for mechanized harvesting and boosts yield and fruit quality by Yongqi Geng, Ke Xia, Xiangda Song, Pu Yan, Xueying He, Guoxiu Wu, Yang Li, Yanman Li, Fan Wang, Wenyue Li, Dandan Cui, Shengli Li

“…ProCa and ProCa + KDP evaluated fruit yield primarily through increased fruit number per plant and individual fruit dry weight. …”
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Optimising plastic-film mulching under drip irrigation to boost maize productivity through enhanced water and fertiliser efficiency in sub-humid regions by Xiaodong Bo, Fuqi Yao

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Simultaneous integrated boost-intensity modulated radiation therapy (SIBIMRT) planning for pelvic tumours: dose coverage to target volume and normal tissue sparing by Marwa Ali Hussein, Siham Sabah Abdullah, Hadeel Kamil Abdullah, Abdulrahman Mohammed Abdulbaqi, Sura Abdul Kareem Madlool

“… Objective: To evaluate the better radiotherapy plan for pelvic tumours that may achieve a high target coverage dose and low normal tissue tolerance dose using simultaneous integrated boost-intensity-modulated radiation therapy technique. …”
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Prognostication of advanced CO2 capture using tunable solvents with an ensemble learning-based decision tree model by Reza Soleimani, Amir Hossein Saeedi Dehaghani, Ziba Behtouei, Hamidreza Farahani, Seyyed Mohsen Hashemi

“…The model incorporates key parameters such as temperature, pressure, mole percent of salt and hydrogen bond donor (HBD) compounds, HBD melting points, molecular weights of salts and HBDs, and other critical factors. …”
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Machine learning algorithms for predictive modeling of dyslipidemia-associated cardiovascular disease risk in pregnancy: a comparison of boosting, random forest, and decision tree... by Idris Zubairu Sadiq, Fatima Sadiq Abubakar, Muhammad Auwal Saliu, Babangida Sanusi katsayal, Aliyu Salihu, Aliyu Muhammad

“…Results The results showed that random forest regression outperformed both boosting and decision tree regression, recording the lowest error criteria (MSE = 0.071 and RMSE = 0.266) for evaluating the model. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…We evaluated three optimization approaches—Grid Search (GS), Random Search (RS), and Bayesian Search (BS)—across three machine learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). …”
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Advanced Machine Learning Methods for the Prediction of the Optical Parameters of Tellurite Glasses by Fahimeh Ahmadi, Mohsen Hajihassani, Tryfon Sivenas, Stefanos Papanikolaou, Panagiotis G. Asteris

“…This study evaluates the predictive performance of advanced machine learning models, including DeepBoost, XGBoost, CatBoost, RF, and MLP, in estimating the Ω₂, Ω₄, and Ω₆ parameters based on a comprehensive set of input variables. …”
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Toward sustainable solar energy: Analyzing key parameters in photovoltaic systems by Nugzar Gomidze, Lali Kalandadze, Omar Nakashide, Izolda Jabnidze, Miranda Khajishvili, Jaba Shainidze

“…This Review article offers a thorough investigation of the direct current parameters in photovoltaic panels, aiming to boost their efficiency and cost-effectiveness in production. …”
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Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique by Lijie Jiang, Qi Li, Huiqing Liao, Hourong Liu, Bowen Tan

“…Abstract This study develops and evaluates advanced hybrid machine learning models—ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)—optimized via the Black Widow Optimization Algorithm (BWOA) to predict the density of supercritical carbon dioxide (SC-CO2) and the solubility of niflumic acid, critical for pharmaceutical processes. …”
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MVA.85A boosting of BCG and an attenuated, phoP deficient M. tuberculosis vaccine both show protective efficacy against tuberculosis in rhesus macaques. by Frank A W Verreck, Richard A W Vervenne, Ivanela Kondova, Klaas W van Kralingen, Edmond J Remarque, Gerco Braskamp, Nicole M van der Werff, Ariena Kersbergen, Tom H M Ottenhoff, Peter J Heidt, Sarah C Gilbert, Brigitte Gicquel, Adrian V S Hill, Carlos Martin, Helen McShane, Alan W Thomas

“…<h4>Conclusions</h4>Both the BCG/MVA.85A prime-boost regime and the novel live attenuated, phoP deficient TB vaccine candidate SO2 showed significant protective efficacy by various parameters in rhesus macaques. …”
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Sustainable extraction of phytochemicals from Mentha arvensis using supramolecular eutectic solvent via microwave Irradiation: Unveiling insights with CatBoost-Driven feature analy... by Zubera Naseem, Muhammad Bilal Qadir, Abdulaziz Bentalib, Zubair Khaliq, Muhammad Zahid, Fayyaz Ahmad, Nimra Nadeem, Anum Javaid

“…The present study revealed the higher extraction potential of sustainable choline chloride (ChCl) and ethylene glycol (EG) based deep eutectic solvent (DES) from Mentha arvensis via microwave irradiation. The categorical boosting (CatBoost) machine learning model was applied to optimize the extraction process against time (4–8 min), microwave power (160–320 W), and biomass quantity (1–2.0 g/10 mL) with DES. …”
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Machine learning algorithms to predict the tensile strength of novel composite materials by S. Sathees Kumar, P. Shyamala, Pravat Ranjan Pati

“…Five regression algorithms such as polynomial regression, bagging regression, random forest, XGBoost, and gradient boosting were trained and evaluated using five-fold cross-validation and standard error metrics. …”
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Prediction of Liquefaction-Induced Lateral Displacements Using Hybrid GBRT and EOA by Arash Ziaie, Bahareh Mehdizadeh, Farzad Safi Jahanshahi, Nazanin Ahmadi, Ali Reza Ghanizadeh

“…Consequently, predicting these lateral movements is vital for evaluating the effects of earthquakes on buildings and infrastructures in regions susceptible to liquefaction. …”
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A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…This study conducts a comparative analysis of the performance of ten novel and well-performing metaheuristic algorithms for parameter estimation of solar photovoltaic models. …”
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