Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net) by Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner, Seong Woo Jeon, Yowhan Son, Andrey Krasovskiy, Woo-Kyun Lee

“…The optimization revealed spatial concentration of fires near metropolitan areas and the east coast, with temporal concentration in spring due to agricultural burning. Integration of multiscale features through DN-FLAM achieved optimal performance with Pearson's <italic>r</italic> values of 0.943, 0.840, and 0.641 for temporal, spatial, and spatio-temporal validations. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…After handling missing values, balancing the dataset, and analyzing the classifier&#x2019;s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment by Goda Srinivasa Rao, P. Santosh Kumar Patra, V.A. Narayana, Avala Raji Reddy, G.N.V. Vibhav Reddy, D. Eshwar

“…This nature-inspired metaheuristic algorithm imitates the behaviour of African buffalos to determine which traits are the most important. …”
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Vibration Signal Analysis for Intelligent Rotating Machinery Diagnosis and Prognosis: A Comprehensive Systematic Literature Review by Ikram Bagri, Karim Tahiry, Aziz Hraiba, Achraf Touil, Ahmed Mousrij

“…In the context of fault detection, support vector machines (SVMs), convolutional neural networks (CNNs), Long Short-Term Memory (LSTM) networks, k-nearest neighbors (KNN), and random forests have been identified as the five most frequently employed algorithms. Meanwhile, transformer-based models are emerging as a promising venue for the prediction of RUL values, along with data transformation. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. Specifically, an optimized You Only Look Once (YOLO) v8n model was developed by integrating a dilation-wise residual–dilated re-parameterization block module, a generalized feature pyramid network, and the Scylla Intersection-over-Union loss function. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…The monitoring data of Urumqi Metro Line 1 is analyzed as an example, and the suitable combination of prediction models for each region under the environmental risk zoning of the subway tunnel construction is obtained: high-risk region (singular value decomposition (SVD) + long and short-term memory (LSTM) neural network); middle-risk region (wavelet transform/Kalman filter + back propagation neural network (BPNN)); and low-risk region (mean filtering + autoregressive integrated moving average model (ARIMA)).…”
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A Study Investigating Interpretable Deep Learning Models for Predicting Mortality and Survival in Patients with Primary Thyroid Lymphomas by Zihan Yu, Rong Hu, Jiaqing Chen

“…The findings underscore the value of integrating interpretable machine learning frameworks into survival analysis for rare cancers.…”
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A Detailed Set of Ideas for Designing a Quantum Computing Framework Based on Smart Contracts, Configured Using Foundry and Qiskit by Alexandru-Gabriel Tudorache

“… The purpose of this paper is to describe a new system design for integrating quantum computing algorithms (and their results) into a blockchain network. …”
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Predictive optimization in automotive supply chains: a BiLSTM-Attention and reinforcement learning approach by Asmae Amellal, Issam Amellal, Mohammed Rida Ech-charrat, Hamid Seghiouer

“…To further our analysis, we incorporated reinforcement learning, evaluating three algorithms: Q-learning, Deep Q-Networks (DQN), and SARSA. …”
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The Aboveground Biomass Estimation of the Grain for Green Program Stands Using UAV-LiDAR and Sentinel-2 Data by Gaoke Yueliang, Gentana Ge, Xiaosong Li, Cuicui Ji, Tiancan Wang, Tong Shen, Yubo Zhi, Chaochao Chen, Licheng Zhao

“…Then, the AGB of the GGP stands was estimated using the Sentinel-2 data and the gradient boosting decision tree (GBDT) algorithm. The results showed that the AGB sample dataset constructed using the proposed approach exhibited strong consistency with field-measured data (R² = 0.89). …”
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TRANS: a prediction model for EGFR mutation status in NSCLC based on radiomics and clinical features by Zhigang Chen, Huiying Lu, Ao Liu, Jia Weng, Lei Gan, Lina Zhou, Xiao Ding, Shicheng Li

“…A nomogram was developed by integrating predictive features. Biological functions were analyzed utilizing RNA sequencing data. …”
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A novel method for monitoring Cladophora blooms in Qinghai Lake based on UAV imagery by Juan Zhang, Xiaojun Yao, Xinde Chu, Hongyu Duan, Yuxuan Zhang, Hui Chang, Ju Huang

“…In this study, we propose a new spectral index called the visible band spectral slope index (VSSI) and integrate it with a triangular threshold segmentation algorithm to automatically extract features of Cladophora blooms from very-high-resolution UAV imagery. …”
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An explainable web application based on machine learning for predicting fragility fracture in people living with HIV: data from Beijing Ditan Hospital, China by Bo Liu, Bo Liu, Qiang Zhang, Qiang Zhang, Xin Li, Xin Li

“…Decision Curve Analysis indicated clinical utility across various threshold probabilities, with calibration curves showing high concordance between predicted and observed risks. SHAP values explained individual risk profiles. The XGBoostpowered web calculator (https://sydtliubo.shinyapps.io/cls2shiny/) enables clinicians and patients to assess fragility fracture risk in PLWH.ConclusionWe developed a web-based risk assessment tool using the XGBoost algorithm for predicting fragility fractures in HIV-positive patients. …”
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Point-to-Interval Prediction Method for Key Soil Property Contents Utilizing Multi-Source Spectral Data by Shuyan Liu, Dongyan Huang, Lili Fu, Shengxian Wu, Yanlei Xu, Yibing Chen, Qinglai Zhao

“…Among these strategies, the outer-product analysis fusion algorithm proved particularly effective in improving prediction accuracy. …”
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Predicting soil chemical characteristics in the arid region of central Iran using remote sensing and machine learning models by Azita Molaeinasab, Hossein Bashari, Mostafa Tarkesh Esfahani, Saeid Pourmanafi, Norair Toomanian, Bahareh Aghasi, Ahmad Jalalian

“…The ensemble model performed best, achieving R2 values of 0.89 for Ca, 0.84 for CaCO3, 0.79 for SO4, and 0.73 for CaSO4. …”
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Investigating the Dynamic Change and Driving Force of Isolated Marsh Wetland in Sanjiang Plain, Northeast China by Shuangwei Zhang, Jiping Liu, Yanhui Chen, Wenhan Pei, Lihui Xuan, Yingpu Wang

“…The dynamic change characteristics as well as the patch importance values (dIIC) of isolated and non-isolated marsh wetlands were analyzed using the dynamic degree, standard deviation ellipse model, and the integral index of connectivity (IIC). …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…This study employed the Informer model to forecast drought and conducted a comparative analysis with Autoregressive Integrated Moving Average (ARIMA), long short-term memory (LSTM), and Convolutional Neural Network (CNN) models. …”
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Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…The Improved Whale Optimization Algorithm (IWOA) is employed to optimize parameters in this blueprint, facilitating real-time scheduling by rapidly converging to the global optimum. …”
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Fuzzy Logic-Based Performance Enhancement of FSO Systems Under Adverse Weather Conditions by Hassan Yousif Ahmed, Medien Zeghid, Akhtar Nawaz Khan, Somia A. Abd El-Mottaleb

“…The FLC module operates through an algorithm comprising eight well-defined steps, ensuring robust and adaptive control of the BER. …”
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Development of an explainable prediction model for portal vein system thrombosis post-splenectomy in patients with cirrhosis by Caixia Dong, Guodong Li, Rui Zhou, Dou Qu, Duwei Dai, Junxia Zhao, Lingbo An, Xiaojie Song, Jiazhen Zhu, Zong Fang Li

“…The predictive model integrated 37 candidate predictors based on accessible clinical data, including demographic characteristics, disease features, imaging results, laboratory values, perioperative details and postoperative prophylactic therapies, and finally, eight predictors were selected for model construction. …”
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