Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…As per the Boruta algorithm, 16 attributes were deemed important, while 14 attributes had less influence on AGB. …”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The optimal hyperparameter values for the XGBoost model can vary significantly depending on the specific problem at hand. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…Subsequently, five machine learning algorithms, such as RF and XGBoost, are used in combination with a grid search to find the optimal hyperparameters, and Lasso is used as the meta-learner to integrate the prediction results. …”
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An explainable predictive machine learning model for axillary lymph node metastasis in breast cancer based on multimodal data: A retrospective single-center study by Yuxi liu, Yunfeng Wu, Qing Xia, Hao He, Haining Yu, Ying Che

“…Ten machine learning algorithms—including Naïve Bayes, Random Forest, Logistic Regression, and Support Vector Machines—were implemented to construct predictive models. …”
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Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…The kernel regression parameters are optimized by minimizing the discrepancies between actual and predicted values of permeability at well locations, the integral permeability of the reservoir domain around each well, and skin factors. …”
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Diet Engine: A real-time food nutrition assistant system for personalized dietary guidance by Asim Moin Saad, Md. Raihanul Haque Rahi, Md. Manirul Islam, Gulam Rabbani

“…Moreover, a personalized chatbot provides diet advice, meal recommendations, and fitness suggestions. By seamlessly integrating advanced deep learning algorithms with user-centric features, this study underscores the transformative potential of Diet Engine in fostering healthier eating habits, raising nutritional awareness, and contributing to a global shift toward more informed and sustainable lifestyle choices.…”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Current single-aperture small target detection algorithms fail to exploit the spatial relationships among compound eye apertures, thereby underutilizing the inherent advantages of compound eye imaging systems. …”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The extracted features were then processed by a set of ML algorithms along with a voting ensemble approach. Additionally, Gradient-weighted Class Activation Mapping (Grad-CAM) was integrated as an explainable AI (XAI) technique for enhancing model transparency by highlighting key influencing regions in the CT scans, which improved interpretability and ensured reliable and trustworthy results for clinical applications. …”
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Recent Trends in Proxy Model Development for Well Placement Optimization Employing Machine Learning Techniques by Sameer Salasakar, Sabyasachi Prakash, Ganesh Thakur

“…Well placement optimization refers to the identification of optimal locations for wells (producers and injectors) to maximize net present value (NPV) and oil recovery. It is a complex challenge in all phases of production (primary, secondary and tertiary) of a reservoir. …”
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A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…PCSN-Net outperforms various complex algorithms, including EfficientNet, DenseNet, and Inception-ResNet-V2, despite preserving effective training and inference times. …”
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Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning by Qiong Li, Hongde Liu

“…A comprehensive machine learning framework incorporating 101 algorithmic combinations across 10 survival modeling approaches, including random survival forests and ridge regression, was employed to develop a robust prognostic model. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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A Versatile Gyro Inclinometer, Adaptive to the Borehole Trajectory, Based on a Uniaxial Angular Rate Sensor by Ya. I. Binder, I. A. Khazov

“…The properties of orientation errors are examined using linearization methods, integral calculus, fundamentals of the calculus of variations, and the theory of linear differential equations.Results. …”
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Numerical Modeling Tools and S-derivatives by Anatoly Nikolaevich Morozov

“…The constructions are algorithmic in nature and can be applied in numerically computer research of various relevant models.…”
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Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…Applying the random forest method to classify predictions of adaptive responses based on climatic variables showed that all thermoregulatory, hormonal, biochemical, and hematological responses are important, except for urea and T₃ concentrations, which had negative importance values. We conclude that adaptation results from an integration between energy and lipid metabolism, renal function, hormonal profile, and thermoregulatory, hematological, and productive responses. …”
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The PM_2.5-Bound Polycyclic Aromatic Hydrocarbon Behavior in Indoor and Outdoor Environments, Part III: Role of Environmental Settings in Elevating Indoor Concentrations... by Gordana Jovanović, Mirjana Perišić, Timea Bezdan, Svetlana Stanišić, Kristina Radusin, Aleksandar Popović, Andreja Stojić

“…We applied seven regression tree ensemble algorithms to interrelate the variables alongside six metaheuristic optimization algorithms to refine model accuracy and robustness. …”
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Identifying Lactylation-related biomarkers and therapeutic drugs in ulcerative colitis: insights from machine learning and molecular docking by Yao Yang, Xu Sun, Bin Liu, Yunshu Zhang, Tong Xie, Junchen Li, Jifeng Liu, Qingkai Zhang

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METHOD AND SYSTEM FOR ASSESSING OF SPORTSMAN’S PHYSIOLOGICAL RESERVES DURING PHYSICAL EXERCISES by Nguyen Mau Thach, Nguyen Trong Tuyen, Tran Trong Huu

“…The circle diagram is proposed for taking into account of all mentioned parameters and its variation dynamics. The value of the integral PR parameter is an area of a polygon, which is obtained on the circle diagram using normalized values of the diagnostically significant parameters. …”
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