Grid tied hybrid PV fuel cell system with energy storage and ANFIS based MPPT for smart EV charging by Suresh vendoti, Narasimha Prasad Tulasi, Ravi Kumar Jalli, Sudhakiran Ponnuru, Zhang Jin, P. Yakaiah, Mamdooh Alwetaishi, S. Prabhakar

“…An adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) algorithm is employed to enhance PV power extraction under dynamically varying environmental conditions. …”
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Modelling Ergonomic Hazard Risks in Manual Handling: Insights from Ponorogo’s Traditional Industry by Dian Afif Arifah, Ratih Andhika Akbar Rahma, Triana Harmini, Dhiya Irsyad Hafidz

“…This study aims to develop a model to evaluate and predict ergonomic hazards using a neural network algorithm, focusing on the relationship between manual handling postures and musculoskeletal pain in 12 body regions. …”
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Modelling the future of cleaner energy: Explainable artificial intelligence model for green hydrogen production rate estimation by Okorie Ekwe Agwu, Saad Alatefi, Ahmad Alkouh

“…Overall, the model can be used in two modes: online, by integrating it into software programs, and offline, by simply entering parameter values into the explicit model without having to run long lines of code.…”
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Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals by Yan Zhao, Ming Guo, Xiangyong Chen, Jianqiang Sun, Jianlong Qiu

“…To effectively improve the performance of the recognition system, the proposed decision fusion algorithm combines Critic method and majority voting strategy to determine the weight values that affect the final decision results. …”
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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

“…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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Continuously Variable Geometry Quadrotor: Robust Control via PSO-Optimized Sliding Mode Control by Foad Hamzeh, Siavash Fathollahi Dehkordi, Alireza Naeimifard, Afshin Abyaz

“…A sliding mode control algorithm, optimized using particle swarm optimization, is implemented to ensure stability and high performance in the presence of uncertainties and noise. …”
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Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving by Seonghark Jeong, Heeseok Shin, Myeong-Jun Kim, Dongwan Kang, Seangwock Lee, Sangki Oh

“…In this study, we propose an enhanced LiDAR-based mapping and localization system that utilizes a camera-based YOLO (You Only Look Once) algorithm to detect and remove dynamic objects, such as vehicles, from the mapping process. …”
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A Portable Smartphone-Based 3D-Printed Biosensing Platform for Kidney Function Biomarker Quantification by Sangeeta Palekar, Sharayu Kalambe, Jayu Kalambe, Madhusudan B. Kulkarni, Manish Bhaiyya

“…The platform features a 3D-printed enclosure with integrated diffused LED lighting to ensure a controlled environment for image acquisition. …”
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Bat optimization of hybrid neural network-FOPID controllers for robust robot manipulator control by Bashra Kadhim Oleiwi, Mohamed Jasim, Ahmad Taher Azar, Ahmad Taher Azar, Saim Ahmed, Saim Ahmed, Ahmed Redha Mahlous, Ahmed Redha Mahlous

“…The bat optimization algorithm (BOA) is applied to find the best parameter values of the proposed control scheme by minimizing the performance index of the integral time square error (ITSE). …”
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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…By integrating the 7 radiomic features and 4 clinical features using a feature-level fusion strategy, the combined model exhibited further improved predictive performance, with an AUC value of 0.953 (95% CI: 0.924~0.983; accuracy: 0.884, specificity: 0.860) and 0.852 (95% CI: 0.729~0.976; accuracy: 0.682, specificity: 0.629), respectively in the training set and the validation set. …”
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Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The spectral characteristics of the forest canopy were employed as a bridge to enhance the sensitivity between the SWHC and various vegetation indices using mathematical statistical methods. This study integrated hyperspectral technology with machine learning algorithms to model complex nonlinear relationships and to select the optimal SWHC model. …”
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Mathematical approach for rapid determination of pull-in displacement in MEMS devices by Yongcun Shao, Yutong Cui

“…These equations are transformed into an iterative algorithm for calculating pull-in displacement, with nonlinear terms addressed through approximation and perturbation techniques tailored to the MEMS system’s characteristics.ResultsValidation using specific examples demonstrates the method's accuracy in determining pull-in displacement and voltage. …”
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Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

“…This study aims to develop a predictive model for daily hospital outpatient volume using the XGBoost algorithm. Meanwhile, the forecasting performance was compared with that of the Seasonal AutoRegressive Integrated Moving Average with exogenous regressors (SARIMAX) and Random Forest (RF) models. …”
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Development of a microwave low-pass filter based on a microstrip line projection mode by A. D. Yarlykov, O. A. Demin

“…Sections of microstrip lines having finite length are widely used to develop integrated circuits and microwave devices for various purposes, such as power dividers, directional couplers, attenuators, and filters. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…A key innovation of this work is the development and application of a selective cleaning algorithm that systematically filters assay data to mitigate noise and inconsistencies inherent in large-scale bioactivity datasets. …”
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Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
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Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. …”
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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…This study employs an integrated data-driven approach to optimize MXene-based aqueous ionic liquids by varying system temperature and MXene mass fraction (MF). …”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
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