Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM by Weigang Fu, Haitao Wang, Kuankuan Zhang, Xia Wang, Kunlun Chen, Chunmei Sun, Zhengwei Wang, Liuyang Song, Niannian Wang

“…The optimized SSA-LightGBM model was then trained, and its performance was rigorously evaluated through error analysis and stability assessment. …”
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A deep learning model for diagnosis of inherited retinal diseases by Freshteh Jafarbeglou, Hamid Ahmadieh, Farnaz Soleimani, Ali Karimi, Narsis Daftarian, Sahba Fekri, Tahmineh Motevasseli, Morteza Naderan, Babak Kamali Doust Azad, Abbas Sheikhtaheri, Farid Khorrami, Hemn Baghban Jaldian, Kia Bayat, Saeideh Shahbazi, Mahdi Yazdanpanah, Tahereh Sabbaghi, Kourosh Sheibani, Hadi Ghattan Kashani, Masoud Shariat Panahi, Hamideh Sabbaghi

“…The impact of single-input and multi-input architectures was further evaluated on state-of-the-art neural network models and machine learning algorithms. …”
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Machine learning-based prediction of speed of sound in fatty acid ethyl esters by Kusum Yadav, Shahad Almansour, Lulwah M. Alkwai, Anupam Yadav, Mehrdad Mottaghi

“…This conclusion was drawn from extensive statistical evaluations and visualization techniques. CNN achieved an R² value of 0.9996, with low average absolute relative error and mean squared error, outperforming other tested algorithms. …”
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System analysis and information processing to solve the problem of detecting breakdowns of computer information storage by N. M. Kodatsky, E. A. Revyakina, A. R. Gazizov

“…It involves conducting experiments with a data set and the Google Colab cloud environment, creating and analyzing a machine learning model, and evaluating the effectiveness and quality of training. …”
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Wireless Sensor Networks Focusing on Predicting Average Localization Error through Machine Learning Applications by Ioanna Gounari, Mattheos Kanzilieris

“…Extensive testing showed that the DTRT model outperformed others in predicting ALE. During training, the DTRT model achieved an R² value of 0.990, indicating its superior prediction accuracy. …”
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Hybrid Deep Neural Network-Based Generation Rescheduling for Congestion Mitigation in Spot Power Market by Anjali Agrawal, Seema N. Pandey, Laxmi Srivastava, Pratima Walde, Saumya Singh, Baseem Khan, R. K. Saket

“…The present approach provides a ready/instantaneous solution to manage congestion in a spot power market. During the training, the Root Mean Square Error (RMSE) is evaluated and minimized. …”
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Smart solutions for dissolved oxygen control in semi-batch fermenters: A machine learning approach by J. Sumathi, P. Aravind, G. Gandhimathi

“…LM algorithm produced a maximum correlation coefficient under training (0.99818), testing (0.99351), valediction (1.0), and an overall correlation coefficient be 0.9568. …”
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Advanced pathological subtype classification of thyroid cancer using efficientNetB0 by Hongpeng Guo, Junjie Zhang, You Li, Xinghe Pan, Chenglin Sun

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A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network by Jafar A. Alzubi, Kiran Sree Pokkuluri, Rajesh Arunachalam, Surendra Kumar Shukla, Sumanth Venugopal, Karthikayen Arunachalam

“…From the database, both the masked face images and mask-free images are used for training the Generative Adversarial Network (GAN) model. …”
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Applying text-mining to clinical notes: the identification of patient characteristics from electronic health records (EHRs) by Simone ten Hoope, Koen Welvaars, Kylian van Geijtenbeek, Mellanie Klok-Everaars, Sander van Schaik, Fatma Karapinar-Çarkit

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Deep neural networks and fractional grey lag Goose optimization for music genre identification by Yuanye Tian

“…In this work, a new methodology is presented based on deep learning and metaheuristic algorithms to enhance the performance in music style categorization. …”
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Optimization Design of Lazy-Wave Dynamic Cable Configuration Based on Machine Learning by Xudong Zhao, Qingfen Ma, Jingru Li, Zhongye Wu, Hui Lu, Yang Xiong

“…Three optimization algorithms—Particle Swarm Optimization (PSO), Ivy Optimization (IVY), and Tornado Optimization (TOC)—were evaluated for their effectiveness in optimizing the arrangement of buoyancy and weight blocks. …”
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StegGPT: A Novel Foundation-Model-Based Character-Level Linguistic Steganography Method Utilizing Large Language Models by Omer Farooq Ahmed Adeeb, Seyed Jahanshah Kabudian

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. The system is trained and evaluated on a real-world dataset derived from structured field experiments, comprising 52 instances and 42 agronomic, microbial, and ecological variables. …”
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Predicting student retention: A comparative study of machine learning approach utilizing sociodemographic and academic factors by Reymark D. Deleña, Norniña J. Dia, Redeemtor R. Sacayan, Joseph C. Sieras, Suhaina A. Khalid, Amer Hussien T. Macatotong, Sacaria B. Gulam

“…A total of 482 student records and 146 variables were preprocessed using Power BI and prepared via the CRISP-DM methodology before being modeled in Jupyter Notebook. Ten ML algorithms such asExtreme Gradient Boosting (XGBoost), Gradient Boosting (GB), Artificial Neural Network (ANN), Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Logistic Regression (LR), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Naïve Bayes (NB) were evaluated using both train-test split and 5-fold cross-validation to ensure robustness and generalizability. …”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…Analysis of the five evaluation criteria revealed that the RSA can better optimize the parameters of the VMD algorithm. …”
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Artificial intelligence-based optimization and modeling of cadmium reduction via ultraviolet-assisted malathion/sulfite reaction mechanisms by Hossein Azarpira, Parsa Khakzad, Tayebeh Rasolevandi, Amir Sheikhmohammadi

“…Regarding the training set evaluation, high accuracy was observed with minimal error and R2 of 0.996. …”
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A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading by Mohammed Taha Kaaitan, Rashid Ali Fayadh, Zuhair S. AL-sagar, Salam J. Yaqoob, Mohit Bajaj, Mebratu Sintie Geremew

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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…The FWOA-SVR model is comprehensively evaluated against traditional SVR, Long Short-Term Memory (LSTM), and Backpropagation Neural Network (BPNN) models using training, validation, and testing datasets. …”
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RESEARCH ON THE REMAINING INTENSITY OF PIPELINE CORROSION BASED ON IWOA-LSSVM by ZHANG Jia, Ll LinFeng, WANG HaoJie, ZHANG Ting

“…In response to pipeline corrosion surplus intensity, a surplus intensity prediction method based on the Improved Whale Optimization Algorithm (IWOA ) -Least Square Support Vector Machine (LSSVM) combination algorithm model. …”
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