AI Merged With Human Knowledge Produces the Best Possible Weather Forecasts by Stephen G. Penny

“…., 2025, https://doi.org/10.1029/2024gl110472) aims to improve weather forecasts by using neural networks to learn optimal maps between nature and imperfect numerical weather prediction (NWP) models. …”
Get full text

Ensemble stacking: a powerful tool for landslide susceptibility assessment – a case study in Anhua County, Hunan Province, China by Lei-Lei Liu, Aasim Danish, Xiao-Mi Wang, Wen-Qing Zhu

“…Initially, we employ an ensemble stacking technique that combines the strengths of three machine learning classifiers. This combination leverages the support vector classifier (SVC) as the key meta-classifier to optimize and refine predictions. …”
Get full text

Optimizing turning parameters of duralumin nano Cr₂C₃–MoS₂ using ANN and MOORA: A multi-objective approach by Ramesh Vellaichamy, Pugazhenthi Rajagopal, Ajith Arul Daniel Selsam Chandradoss, A. Geetha Selvarani

“…This investigation presents a comprehensive parametric optimization study for the precision machining of duralumin matrix composites reinforced with hybrid nano-scale particles comprising chromium carbide (Cr₂C₃) and molybdenum disulfide (MoS₂). …”
Get full text

Risk prediction models for diabetic retinopathy: a systematic review by Hui Huang, Yingmin Wu, Hejiang Ye, Jiaoyang Li, Ling Chen, Xuan Huang

“…Hopefully, future studies will ensure transparency and science in the model-building process by conducting large-sample integrated machine learning, reinforcing multicenter external validation. …”
Get full text

Automated Prediction of Good Dictionary EXamples (GDEX): A Comprehensive Experiment with Distant Supervision, Machine Learning, and Word Embedding-Based Deep Learning Techniques by Muhammad Yaseen Khan, Abdul Qayoom, Muhammad Suffian Nizami, Muhammad Shoaib Siddiqui, Shaukat Wasi, Syed Muhammad Khaliq-ur-Rahman Raazi

“…We find that the random forests with parts-of-speech information and word2vec-based bidirectional LSTM are the most optimal ML and DL combinations for automated GDEX elicitation; on the test set, these models, respectively, secured a balanced accuracy of 73% and 77%.…”
Get full text

Improved prediction and risk stratification of major adverse cardiovascular events using an explainable machine learning approach combining plasma biomarkers and traditional risk f... by Xi-Ru Zhang, Wen-Fang Zhong, Rui-Yan Liu, Jie-Lin Huang, Jing-Xiang Fu, Jian Gao, Pei-Dong Zhang, Dan Liu, Zhi-Hao Li, Yan He, Hongwei Zhou, Zhuang Li

Get full text

A novel lightweight deep learning framework using enhanced pelican optimization for efficient cyberattack detection in the Internet of Things environments by Yaozhi Chen, Yan Guo, Yun Gao, Baozhong Liu

“…To counter these challenges, the current study proposes a hybrid model incorporating an efficient convolutional neural network (CNN) and an enhanced pelican optimization algorithm (EPOA) to detect IoT network attacks. …”
Get full text

Rolling Bearing Fault Diagnosis Based on VMD-DWT and HADS-CNN-BiLSTM Hybrid Model by Luchuan Shao, Bing Zhao, Xutao Kang

Get full text

Large Language Model-Assisted Deep Reinforcement Learning from Human Feedback for Job Shop Scheduling by Yuhang Zeng, Ping Lou, Jianmin Hu, Chuannian Fan, Quan Liu, Jiwei Hu

Get full text

Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms by Wenzhi Wang, Feng Jin, Lina Song, Jinfang Yang, Yingjian Ye, Junjie Liu, Lei Xu, Peng An

“…During model training, cross-validation was used to evaluate model performance, and the optimal model was selected. …”
Get full text

Enhancing Consumer Agent Modeling Through Openness-Based Consumer Traits and Inverse Clustering by Brahim Benaissa, Masakazu Kobayashi, Hiroshi Takenouchi

Get full text

A novel model for expanding horizons in sign Language recognition by Esraa Hassan, Mahmoud Y. Shams, Tarek Abd El-Hafeez, Marwa Elseddik

Get full text

Construction of a Surface Roughness and Burr Size Prediction Model Through the Ensemble Learning Regression Method by Ali Khosrozadeh, Seyed Ali Niknam, Fatemeh Hajizadeh

“…This work represents a novel and accurate approach for predicting key surface quality indicators, with significant implications for process optimization and cost reduction in precision machining.…”
Get full text

Numerical Modelling of the Multiphase Flow in an Agricultural Hollow Cone Nozzle by Paweł Karpiński, Zbigniew Czyż, Stanisław Parafiniuk

Get full text

Fuzzy One-Class Classification Model Using Contamination Neighborhoods by Lev V. Utkin

“…Optimal classification parameters of the models are derived by minimizing the fuzzy expected risk. …”
Get full text

High-speed threat detection in 5G SDN with particle swarm optimizer integrated GRU-driven generative adversarial network by R. Shameli, Sujatha Rajkumar

“…The discriminator model uses the PSO-optimized generator model to produce synthetic and real attack data to forecast the attack. …”
Get full text

Development of a clinical-radiological nomogram for predicting severe postoperative peritumoral brain edema following intracranial meningioma resection by Chen Bo, Geng Ao, Lu Siyuan, Lu Siyuan, Wu Ting, Wang Dianjun, Zhao Nan, Shan Xiuhong, Deng Yan, Sun Eryi

“…The most optimal model was used to create a nomogram for visualization. …”
Get full text

Using Convolutional Neural Networks for segmentation of brain tumors by Kauã Gabriel Silva de Lima, Vagner Alves Ferreira da Silva, João Victor Oliveira da Silva, Lucas Patrick Ramos de Oliveira, Diogo Lopes da Silva

Get full text

Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803 by Namrata Bhagat, Guddu Kumar Gupta, Amritpreet Kaur Minhas, Deepak Chhabra, Pratyoosh Shukla

“…PCC 6803. Furthermore, these machine learning tools can be used as a model to improve and optimize the yields for other metabolites production. …”
Get full text

Paint shop vehicle sequencing based on quantum computing considering color changeover and painting quality by Jing Huang, Qing Chang, Hua-Tzu Fan

“…This work reveals that different sequencing of vehicles also significantly affects the quality performance of the painting process. We use a machine learning model pretrained on historical data to predict the probability of painting defect. …”
Get full text