Improved cluster analysis of Werner solutions for geologic depth estimation using unsupervised machine learning by Daniel Eshimiakhe, Raimi Jimoh, Magaji Suleiman, Kola Lawal

“…The unsupervised clustering algorithm was then used to improve the detection of geological structures generated from magnetic field data. …”
Get full text

Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty by Muqiao Cai

“…CSA is used to tune the network weights and feature parameters worldwide to improve the neural model’s convergence speed and predictive ability. …”
Get full text

The Effect of Resampling Techniques on Model Performance Classification of Maternal Health Risks by Nia Mauliza, Aisha Shakila Iedwan, Yoga Pristyanto, Anggit Dwi Hartanto, Arif Nur Rohman

“…Performance evaluation was carried out using accuracy, precision, recall, and F1-score metrics to determine the best method and algorithm. The results showed that the SMOTE-ENN and ADASYN-ENN methods significantly improved the model's performance in predicting maternal disease. …”
Get full text

Automating Colon Polyp Classification in Digital Pathology by Evaluation of a “Machine Learning as a Service” AI Model: Algorithm Development and Validation Study by David Beyer, Evan Delancey, Logan McLeod

“… BackgroundArtificial intelligence (AI) models are increasingly being developed to improve the efficiency of pathological diagnoses. …”
Get full text

Multi-Innovation Stochastic Gradient Identification Algorithm for Hammerstein Controlled Autoregressive Autoregressive Systems Based on the Key Term Separation Principle and on the... by Huiyi Hu, Xiao Yongsong, Rui Ding

“…An input nonlinear system is decomposed into two subsystems, one including the parameters of the system model and the other including the parameters of the noise model, and a multi-innovation stochastic gradient algorithm is presented for Hammerstein controlled autoregressive autoregressive (H-CARAR) systems based on the key term separation principle and on the model decomposition, in order to improve the convergence speed of the stochastic gradient algorithm. …”
Get full text

Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

“…With the experimental data, the roughness regression model is established. The ANOVA module is used to evaluate the quality of the regression model. …”
Get full text

An Underwater Acoustic Communication Signal Modulation-Style Recognition Algorithm Based on Dual-Feature Fusion and ResNet–Transformer Dual-Model Fusion by Fanyu Zhou, Haoran Wu, Zhibin Yue, Han Li

Get full text

Research on the financial early warning models based on ensemble learning algorithms: Introducing MD&A and stock forum comments textual indicators. by Zhiheng Zhang, Zhenji Zhu, Yongjun Hua

Get full text

Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…The results show that the prediction model with the integrated decomposition algorithm reduces the RMSE and MAE by 33% and 37%, respectively, which significantly improves the prediction accuracy and generalization ability of the neural network to meet the demand of practical engineering prediction and simultaneously enhances the risk warning ability of the model.…”
Get full text

Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field by Shuangshuang Zhang, Shuangshuang Zhang, Xiangdong Yu, Xiuli Gao, Donglin Li, Shijun Huang

“…Aiming at this problem, this paper establishes a set of dynamic and static integrated classification model of tight sandstone gas wells in Sulige based on XGBoost algorithm. …”
Get full text

Synergistic coupling of ultrasonic cavitation with tailored deep eutectic solvent systems for intensified extraction of Scutellaria Radix flavonoids: Modelling and optimization by... by Qi Cui, Jia-Yi Shi, Le-Le Wen, Wei-Hua Kong, Li-Jie Jiang, Ju-Zhao Liu

Get full text

Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…This model is best suited for further research on AET prediction at the stations under investigation, which could improve irrigation and boost agricultural productivity.…”
Get full text

A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…As a result, the hybrid approach outperforms 10 recent studies on two publicly available datasets (COVID-CT-Dataset and HUST-19), achieving an average accuracy score of 100% across different epochs, along with perfect accuracy, 100% sensitivity, and 100% specificity. The proposed models significantly outperform the baseline model, with accuracy improvements of 13.6% on Data1 and 2.5% on Data2. …”
Get full text

Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms by Manal Abdullah Alohali, Sultan Alahmari, Mohammed Aljebreen, Mashael M. Asiri, Achraf Ben Miled, Sami Saad Albouq, Othman Alrusaini, Ali Alqazzaz

“…Besides, the proposed MDMIoV-DLXAI model utilizes the reptile search algorithm (RSA) model for feature selection. …”
Get full text

Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. …”
Get full text

A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation by Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

Get full text

Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…A model for the identification of breast cancer based on the lightweight gradient boosting machine (GBM) algorithm. …”
Get full text

A novel extraction model optimization with effective separation coefficient for rare earth extraction process using improve differential evolution by Fangping Xu, Hui Yang, Jianyong Zhu, Wenjia Chang

“…First, a chaotic sequence is embedded into the improved algorithm to generate the initial population, enhancing population diversity. …”
Get full text

Iterative segmentation and classification for enhanced crop disease diagnosis using optimized hybrid U-Nets model by Malathi Chilakalapudi, Sheela Jayachandran

“…To further refine this model, classification is adeptly handled by a process inspired by the LeNet architecture, significantly improving identification against various diseases. …”
Get full text

Research on Gating Fusion Algorithm for Power Grid Survey Data Based on Enhanced Mamba Spatial Neighborhood Relationship by Aiyuan Zhang, Jinguo Lv, Yu Geng, Xiaolei Wang, Xianhu Li

Get full text