Application of Artificial Intelligence Models for Evapotranspiration Prediction along the Southern Coast of Turkey by Mohammed Majeed Hameed, Mohamed Khalid AlOmar, Siti Fatin Mohd Razali, Mohammed Abd Kareem Khalaf, Wajdi Jaber Baniya, Ahmad Sharafati, Mohammed Abdulhakim AlSaadi

“…For this purpose, twenty input combinations including hydrological and geographical parameters were introduced to three different approaches called multiple linear regression MLR, random forest RF, and extreme learning machine ELM. Moreover, in this study, large investigation was done, involving the establishment of 60 models and their assessment using ten statistical measures. …”
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A problem-agnostic approach to feature selection and analysis using SHAP by John T. Hancock, Taghi M. Khoshgoftaar, Qianxin Liang

“…We explore feature selection for data reduction with Isolation Forest and SHAP for this case. When data of one class is available, a one-class classifier, such as Gaussian Mixture Model (GMM) can be used in combination with SHAP for determining feature importance, and for feature selection. …”
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Rapid detection of drug abuse via tear analysis using surface enhanced Raman spectroscopy and machine learning by Yingbin Wang, Yulong Huang, Xiaobao Liu, Chishan Kang, Wenjie Wu

“…To enable rapid analysis of complex SERS data, three ML algorithms—linear discriminant analysis (LDA), partial least squares discriminant analysis (PLS-DA), and random forest (RF)—were employed. These algorithms achieved over 90% accuracy in distinguishing between EPH-injected and non-injected SD rats, with area under the ROC curve (AUC) values ranging from 0.9821 to 0.9911. …”
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Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms by Jie Zhu, Jianmei Zhou, Chunhui Tao, Guomei Xia, Bingyan Liu, Xiaowei Zheng, Xu Li, Zhenhua Zhang

“…These, along with other clinical features, were reduced to 8 variables using Lasso regression for model construction. The random forest model demonstrated the best performance in both internal validation (AUC: 0.961) and external validation (AUC: 0.948). …”
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Exotic Laguncularia racemosa drives rapid shifts in pond-to-mangrove restoration communities by Lin Zhang, Yamian Zhang, Yijuan Deng, Pingping Guo, Wenqing Wang, Mao Wang

“…In China and Southeast Asia, a recently popular method involves converting abandoned aquaculture ponds into secondary mangrove forests (i.e., pond-to-mangrove restoration), which reshapes the landscape to create suitable habitats for mangrove plants. …”
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Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models by Chuan Jiang, Zhenyu Xu, Jinqing Liu, Ronghua Li, Keyu Chen, Wenting Peng, Yueming Xiao, Da Cheng, Lei Fu, Shifang Peng

“…Among six machine learning models, the random forest (RF) model achieved the highest AUC (AUC 0.819, 95% CI: 0.720–0.906). …”
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Efecto del pastoreo en el crecimiento de Grevillea robusta A. Cunn. y la dinámica del pastizal enmisiones, Argentina by S. M. Lacorte, H. E. Fassola, C.M. Domecq, M. San José, A. Hennig, E. M. Correa, P. Ferrere

“…. - ubicado en el Sur de Misiones - a partir de los cinco años de edad fue sometido en un sector a pastoreo (P) durante 3 años, con la finalidad de evaluar el efecto del mismo sobre el crecimiento forestal y la dinámica del pastizal bajo ese dosel y otro sector bajo clausura (CL) fue empleado como tratamiento testigo. …”
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Tilapia Lake Virus (TiLV): a Globally Emerging Threat to Tilapia Aquaculture by Lowia Al-Hussinee, Kuttichantran Subramaniam, Win Surachetpong, Vsevolod Popov, Kathleen Hartman, Katharine Starzel, Roy Yanong, Craig Watson, Hugh Ferguson, Salvatore Frasca Jr, Thomas Waltzek

“…., and Thomas Waltzek and published by the UF/IFAS School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences describes this important emerging disease and explains how to prevent outbreaks and what to do if you suspect TiLV in an aquaculture facility or in the wild.  …”
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Polymerization and modeling of phenolic resins from crude wood resin in the presence of AlCl3 by Ömür Aras, Murat Ertaş, Muhammed Yusuf Aksakal, Naile Angın, Merve Genç

“…Natural resin is a promising and valuable renewable non-wood forest product and is used as a natural resource in the production of many biochemical products. …”
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Diversity, Distribution, and Evolution of Bioluminescent Fungi by Brian A. Perry, Dennis E. Desjardin, Cassius V. Stevani

“…They are distributed across the globe with the highest diversity occurring on woody or leafy substrates in subtropical closed canopy forests with high plant diversity. With the caveat that most regions of the world have not been extensively sampled for bioluminescent fungi, the areas with the most known species are Japan (36), South America (30), North America (27), Malesia, South Asia, and Southeast Asia (26), Europe (23), Central America (21), China (13), Africa (10), Australasia, Papua New Guinea, and New Caledonia (11), and the Pacific Islands (5). …”
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Predictive analysis of ratings of perceived exertion in elite Gaelic football by Dermot Sheridan, Aidan J. Brady, Dongyun Nie, Mark Roantree

“…Data were analysed using decision tree, random forest (RF), and bootstrap aggregation (BS) models. …”
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Ensemble modelling reveals spiny monkey orange (Strychnos spinosa Lam.) as a vulnerable wild edible fruit tree in West Africa by Hospice Gérard Gracias Avakoudjo, Mahunan Eric José Vodounnon, Rodrigue Idohou, Aly Coulibaly, Achille Ephrem Assogbadjo

“…Bioclimatic and soil variables were used at a resolution of 30 arcseconds with 588 occurrence records analysed using five algorithms (Random Forest (RF), Maximum Entropy (MaxEnt), Support Vector Machine (SVM), Boosted Regression Trees, and Generalized Linear Model (GLM)) and four global climate models (CanESM5, CNRM-CM6-1, HadGEM3-GC31-LL, and MIROC6). …”
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Design and Evaluation of a Leader–Follower Isomorphic Vascular Interventional Surgical Robot by Pengfei Chen, Yutang Wang, Dapeng Tian

“…The classification process includes time-frequency domain feature extraction, feature selection based on the Relief method and random forest (RF) method, and a BP neural network (NN) classifier. …”
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Improved Pedestrian Positioning with Inertial Sensor Based on Adaptive Gradient Descent and Double-Constrained Extended Kalman Filter by Miaoxin Ji, Jinhao Liu, Xiangbo Xu, Yuyang Guo, Zhenchun Lu

“…The Foot-mounted Inertial Pedestrian-Positioning System (FIPPS) based on the Micro-Inertial Measurement Unit (MIMU) is a good choice for the forest fire fighters when the Global Navigation Satellite System is unavailable. …”
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Machine learning for early detection and severity classification in people with Parkinson’s disease by Juseon Hwang, Changhong Youm, Hwayoung Park, Bohyun Kim, Hyejin Choi, Sang-Myung Cheon

“…Key features—walking speed at PWS, stride length at HWS, and the coefficient of variation (CV) of the stride length at LWS—achieved a classification accuracy of 78.1% using the random forest algorithm. For early PD detection, the stride length at HWS and CV of the stride length at LWS provided an accuracy of 67.3% with Naïve Bayes. …”
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Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data by Qingwen Xue, Ke Wang, Jian John Lu, Yujie Liu

“…The performance of Random Forest (RF), K-Nearest Neighbor (KNN), and Multi-Layer Perceptron (MLP) is also compared with SVM. …”
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ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological Simulation in Upper Huai River Basin by Yongwei Liu, Wen Wang, Yuanbo Liu

“…Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. …”
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Analysis of Roadside Land Use Changes and Landscape Ecological Risk Assessment Based on GF-1: A Case Study of the Linghua Expressway by Mengdi Wen, Liangliang Zhang, Huawei Wan, Peirong Shi, Longhui Lu, Zixin Zhao, Zhiru Zhang, Jinhui Wu

“…The results revealed a decrease in cropland and forest land, accompanied by an increase in the grassland and road areas. …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…Utilizing the CIC-MalMem-2022 dataset, the effectiveness of decision trees, gradient-boosted trees, logistic Regression, random forest, and LightGBM in identifying obfuscated malware was evaluated. …”
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Evaluating Urban Sewage Sludge Distribution on Agricultural Land Using Interpolation and Machine Learning Techniques by Andrea Lazzari, Simone Giovinazzo, Giovanni Cabassi, Massimo Brambilla, Carlo Bisaglia, Elio Romano

“…Interpolation methods, such as spline, cubic spline, and inverse distance weighting (IDW) were used to model the distribution, while machine learning models (k-nearest neighbors, random forest, neural networks) classified spatial patterns. …”
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