Inversion Model for Total Nitrogen in Rhizosphere Soil of Silage Corn Based on UAV Multispectral Imagery by Hongyan Yang, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Jie Li, Qihong Da, Xuchun Li, Kejing Cheng

“…A total of 18 models based on machine learning algorithms, including BP neural networks (BPNNs), random forest (RF), and partial least squares regression (PLSR), were constructed to compare the most suitable inversion model for TN in the rhizosphere soil (0–30 cm) of silage corn at different growth stages. …”
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Soft Computing Techniques to Model the Compressive Strength in Geo-Polymer Concrete: Approaches Based on an Adaptive Neuro-Fuzzy Inference System by Zhiguo Chang, Xuyang Shi, Kaidan Zheng, Yijun Lu, Yunhui Deng, Jiandong Huang

“…It has emerged as an environmentally friendly substitute for traditional concrete, boasting reduced carbon emissions and improved longevity. This research delves into the prediction of the compressive strength of GePC (CSGePC) employing various soft computing techniques, namely SVR, ANNs, ANFISs, and hybrid methodologies combining Genetic Algorithm (GA) or Firefly Algorithm (FFA) with ANFISs. …”
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Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

“…This research provides a new solution for the identification of tomato leaf diseases and has broad potential for agricultural applications.…”
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Extraction of eucalyptus trees along railway lines based on decision tree classification and identification of potential landslides: A case study along Guangxi section of the Guizh... by Mingming MA, Shangqian WU, Meng XIE, Peng TONG, Xiaobo YUAN

“…Then, comprehensive analysis incorporating terrain and landforms factors is conducted to identify potential landslides hazards. The research findings show that: 1) compared to other methods, the decision tree classification algorithm conducted in this study improves the classification accuracy, with an overall average classification accuracy of 87.19% and an average Kappa coefficient of 0.80, indicating that this method can effectively extract the range of eucalyptus in the study area; 2) A large number of eucalyptus are planted along the Guangxi section of the Guinan high-speed railway, with eucalyptus distributed in patches in hilly areas. …”
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Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus by D. Yu. Sorokin, E. S. Trufanova, O. Yu. Rebrova, O. B. Bezlepkina, D. N. Laptev

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Numerical modeling of electromagnetic wave propagation in spatially-varying evaporation duct conditions via 3D parabolic equation method by Hanjie Ji, Hanjie Ji, Lixin Guo, Yan Zhang, Tianhang Nie, Yiwen Wei, Jinpeng Zhang, Qingliang Li, Xiangming Guo, Yusheng Zhang

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EUR Prediction for Shale Gas Wells Based on the ROA-CatBoost-AM Model by Weikang He, Xizhe Li, Yujin Wan, Honming Zhan, Nan Wan, Sijie He, Yaoqiang Lin, Longyi Wang, Wenxuan Yu, Liqing Chen

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Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

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Unsupervised Multistage-Clustering-Based Hammerstein Postdistortion for VLC by Rangeet Mitra, Vimal Bhatia

“…Recently, there has been a huge interest in research toward visible light communication (VLC) targeted toward fifth generation (5G) and beyond standards. …”
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Sentiment Analysis of Mobile Phone Reviews Using XGBoost and Word Vectors by Wang Zekai

“…Consumer reviews are an important source of data used to judge and examine consumer sentiment, and data mining for reviews of electronic products is an important way to help improve the design of electronic products. The research is based on the consumer reviews of online cell phone e-commerce, The paper constructs a sentiment dictionary in this field based on the Sentiment Oriented Point Mutual Information (SO-PMI) algorithm, and the sentiment weight of the review word vectors. …”
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Speaker Model Clustering to Construct Background Models for Speaker Verification by Gökay DİŞKEN, Zekeriya TÜFEKCİ, Ulus ÇEVİK

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Determining the Influence of Real Estate Features on Prices with Partial Dependence Plots: A Case Study in Szczecin, Poland by Gnat Sebastian

“…The CatBoost model, known for its robust handling of categorical features and strong predictive capabilities, is employed as the machine learning algorithm for this analysis. The performance of this model will be compared against a traditional multiple linear regression model, providing insights into the advantages of leveraging advanced machine learning techniques in real estate analysis. …”
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Multi-objective optimization of lithium-ion battery designs considering the dilemma between energy density and rate capability by Xiao-Ying Ma, Wen-Ke Zhang, Ying Yin, Kailong Liu, Xiao-Guang Yang

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Hybridized Brazilian–Bowein type spectral gradient projection method for constrained nonlinear equations by Jitsupa Deepho, Abdulkarim Hassan Ibrahim, Auwal Bala Abubakar, Maggie Aphane

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Influence of geomagnetic disturbances on myocardial infarctions in women and men from Brazil by Luiz Felipe C. Rezende, Eurico R. De Paula, Marcio T. A. H. Muella, Severino L. G. Dutra, Reinaldo R. Rosa, Paulo H. N. Saldiva, Jean P. H. B. Ometto

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Artificial intelligence based vision transformer application for grading histopathological images of oral epithelial dysplasia: a step towards AI-driven diagnosis by Mahdi Hadilou, Nazanin Mahdavi, Elham Keykha, Ali Ghofrani, Elahe Tahmasebi, Masoud Arabfard

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Integrating IoT With Adaptive Beamforming for Enhanced Urban Sensing in Smart Cities by Sunday Enahoro, Sunday C. Ekpo, Mfonobong Uko, Fanuel Elias, Stephen Alabi

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Powdery mildew resistance prediction in Barley (Hordeum Vulgare L) with emphasis on machine learning approaches by Farveh Vahidpour, Hossein Sabouri, Fakhtak Taliei, Sayed Javad Sajadi, Saeed Yarahmadi, Hossein Hosseini Moghaddam

“…Subsequently, Decision Tree, Random Forest, Neural Network, and Gaussian Process Regression models were compared using MAE, RMSE, and R2 metrics. The Bayesian algorithm was utilized to optimize the parameters of the machine-learning models. …”
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Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

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Predicting the clinical subcutaneous absorption rate constant of monoclonal antibodies using only the primary sequence: a machine learning approach by Ronghua Bei, Justin Thomas, Shiven Kapur, Mahlet Woldeyes, Adam Rauk, Jason Robarge, Jiangyan Feng, Kaoutar Abbou Oucherif

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