An overview of the high-resolution global LAnd surface satellite (Hi-GLASS) products suite by Shunlin Liang, Tao He, Jie Cheng, Bo Jiang, Huaan Jin, Ainong Li, Siwei Li, Liangyun Liu, Xiaobang Liu, Han Ma, Dan-Xia Song, Lin Sun, Yunjun Yao, Wenping Yuan, Yufang Zhang, Feng Tian, Leshi Li

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Understanding the environmental health implications of tourism on carbon emissions in China by Jinhua Shao, Sheng Fang, Meiling Zhao, Wanxin Qian, Cai Wang

“…Our findings demonstrate that sparrow search algorithm and random forest (SSA-RF) hybrid model can model the relationship between carbon emissions and tourism factors with low error. …”
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Evolving Spiking Neural Network Model for PM2.5 Hourly Concentration Prediction Based on Seasonal Differences: A Case Study on Data from Beijing and Shanghai by Hengyuan Liu, Guibin Lu, Yangjun Wang, Nikola Kasabov

“…Various evaluation indicators show that the Staging-eSNN model achieves higher performance than the support vector regression (SVR), random forest (RF) and other eSNN models.…”
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Improving Streamflow Prediction Using Multiple Hydrological Models and Machine Learning Methods by Hiren Solanki, Urmin Vegad, Anuj Kushwaha, Vimal Mishra

“…We used Multiple Linear Regression, Random Forest (RF), Extreme Gradient Boosting (XGB), and Long Short‐Term Memory (LSTM) for the post‐processing of simulated streamflow from HMs. …”
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A Machine Learning Approach for Predicting Particle Spatial, Velocity, and Temperature Distributions in Cold Spray Additive Manufacturing by Lurui Wang, Mehdi Jadidi, Ali Dolatabadi

“…Stage 2 combines sampling, interpolation and symbolic regression to extract key features, then uses a weighted random forest model to forecast particle velocity and temperature upon impact. …”
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A machine learning framework for predictive electron density modelling to enhance 3D NAND flash memory performance by Dikendra Verma, Upendra Mohan Bhatt, Anurag Vidyarthi

“…The dataset, which was derived using TCAD simulations, has a sizable number of samples that show the electron density as a function of channel length. …”
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Hybrid retrieval of grass biophysical variables based-on radiative transfer, active learning and regression methods using Sentinel-2 data in Marakele National Park by Philemon Tsele, Abel Ramoelo

“…The NPRMs used were, namely (i) Partial least squares regression (PLSR), (ii) Principle components regression (PCR), (iii) Kernel ridge regression (KRR), (iv) Random forest regression (RFR), and (v) K-nearest neighbours regression (KNNR). …”
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Study on Drive System of Hybrid Tree Harvester by Shen Rong-feng, Zhang Xiaozhen, Zhou Chengjun

“…Hybrid tree harvester with a 60 kW diesel engine combined with a battery pile could be a “green” forest harvesting and transportation system. With the new design, the diesel engine maintains a constant engine speed, keeping fuel consumption low while charging the batteries that drive the forwarder. …”
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Machine Learning-Based Network Detection Research for SDNs by Lai Jiayue

“…To accomplish this, this study constructed a rigorously designed simulated SDN environment, which served as the cornerstone for meticulously assembling a comprehensive dataset encompassing a diverse array of attack vectors, with particular emphasis on DoS. …”
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Metrics and Algorithms for Identifying and Mitigating Bias in AI Design: A Counterfactual Fairness Approach by Dongsoo Moon, Seongjin Ahn

“…To validate the framework, we conducted empirical experiments using random forest and eXtreme Gradient Boosting models on the xAPI-Edu-Data dataset. …”
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Improving the prediction of bitumen’s density and thermal expansion by optimizing artificial neural networks with Optuna and TensorFlow by Eli I. Assaf, Xueyan Liu, Sandra Erkens

“…Previous work demonstrated that Random Forest Regressors (RFRs) could estimate the physical properties of bitumen using molecular descriptors derived from Molecular Dynamics (MD) simulations, thereby reducing the need for computationally intensive simulations. …”
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Predicting Cardiovascular Aging Risk Based on Clinical Data Through the Integration of Mathematical Modeling and Machine Learning by Kuat Abzaliyev, Madina Suleimenova, Siming Chen, Madina Mansurova, Symbat Abzaliyeva, Ainur Manapova, Almagul Kurmanova, Akbota Bugibayeva, Diana Sundetova, Raushan Bitemirova, Nazipa Baizhigitova, Merey Abdykassymova, Ulzhas Sagalbayeva

“…A system of ordinary differential equations was used to simulate the dynamic interactions of these factors. …”
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Evaluating key predictors of breast cancer through survival: a comparison of AFT frailty models with LASSO, ridge, and elastic net regularization by Senyefia Bosson-Amedenu, Emmanuel Ayitey, Francis Ayiah-Mensah, Luyton Asare

“…These results indicate its superior fit and predictive accuracy. The forest plot analysis further validates the strong impact of significant covariates. …”
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Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model by E. Fatima, E. Fatima, R. Kumar, S. Attinger, S. Attinger, M. Kaluza, O. Rakovec, O. Rakovec, C. Rebmann, C. Rebmann, R. Rosolem, R. Rosolem, S. E. Oswald, L. Samaniego, L. Samaniego, S. Zacharias, M. Schrön

“…But since CRNS provides an integral measurement over several soil horizons, a direct comparison of observed and simulated soil moisture products is not possible. This study establishes a framework to assess the accuracy of soil moisture simulated by the mesoscale Hydrologic Model (mHM) by generating simulated neutron counts and comparing these with observed neutron measurements for the first time. …”
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Using Satellite‐Based Vegetation Cover as Indicator of Groundwater Storage in Natural Vegetation Areas by Soumendra N. Bhanja, Pragnaditya Malakar, Abhijit Mukherjee, Matthew Rodell, Pabitra Mitra, Sudeshna Sarkar

“…Artificial neural network‐ and support vector machine‐simulated GWL matches very well with observed GWL, particularly in naturally vegetated areas. …”
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Impacts of Large‐Scale Sahara Solar Farms on Global Climate and Vegetation Cover by Zhengyao Lu, Qiong Zhang, Paul A. Miller, Qiang Zhang, Ellen Berntell, Benjamin Smith

“…Our results indicate a redistribution of precipitation causing Amazon droughts and forest degradation, and global surface temperature rise and sea‐ice loss, particularly over the Arctic due to increased polarward heat transport, and northward expansion of deciduous forests in the Northern Hemisphere. …”
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The influence of body condition and personality on nest defense behavior of Japanese tits (Parus minor) by Mingju E, Chao Shen, Nehafta Bibi, Yu Zhang, Li Liu, Xudong Li

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RSSI-Based Autonomous Tracking System for Radio-Tagged Flying Insects Using UAV With Rotational Antenna by Jeonghyeon Pak, Bosung Kim, Hyoung Il Son

“…The proposed tracking system was verified in a simulated field environment that was constructed by considering the RSSI values obtained in a forest. …”
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A Novel Deep Learning-Based Data Analysis Model for Solar Photovoltaic Power Generation and Electrical Consumption Forecasting in the Smart Power Grid by Camille Franklin Mbey, Felix Ghislain Yem Souhe, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum

“…The results obtained show the outperformance of the proposed optimized method based on deep learning in the both electrical consumption and PV power generation forecasting and its superiority compared to basic methods of deep learning such as support vector machine (SVM), MLP, recurrent neural network (RNN), and random forest algorithm (RFA).…”
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An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand by Nutchapon Prasertsoong, Nattapong Puttanapong

“…The result obtained from Random Forest (RF) demonstrates the highest predictive power for GDP forecasting (r-squared value of 0.912). …”
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