An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…However, conventional methods for modelling and optimizing these frameworks frequently encounter challenges owing to their intricacy and the multitude of interconnected variables. …”
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A photovoltaic power forecasting method based on the LSTM-XGBoost-EEDA-SO model by Ying Xu, Xinrong Ji, Zhengyang Zhu

“…The proposed method provides a novel approach to high-precision PV power forecasting by integrating multi-modal feature fusion and optimized weight allocation.…”
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A mixed-method approach to develop an eco-robust supply chain management framework for Bangladeshi RMG industries by Md Al Amin, Roberto Baldacci

“…This study adopts a mixed-method approach with a QFD-based Optimization Model to develop an Eco-Robust Supply Chain Management (ERSCM) framework. …”
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A Frequency Hybrid Multi-mode PWM Modulation Method for SiC Traction Inverter by HU Liang, FU Xiangyu, LYU Yongcan, FENG Ling, HU Dong

“…During high speeds above 30% rated speed, the current harmonics are optimized modulated to achieve motor current harmonic suppression, while the motor voltage utilization rate can reach 97%. …”
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Structural Design of Segmented Linings for High-Pressure CAES in Underground Workings: Method and Case Study by Sheng Wang, Mengfan Gao, Caichu Xia

“…The study determined, from an engineering case, that six seams are optimal when the lateral pressure coefficient <i>λ</i> is below 1, while four seams are more suitable when <i>λ</i> > 1. …”
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Optimizing space heating efficiency in sustainable building design a multi criteria decision making approach with model predictive control by Zheng Qi, Nan Zhou, Xianwei Feng, Sama Abdolhosseinzadeh

“…Pareto set analysis evaluates optimization outcomes for selected winter days and electricity price scenarios ($0.328/kWh vs. $0.493/kWh), with results demonstrating up to 17% daily heating cost savings compared to conventional methods while maintaining comparable thermal comfort levels. …”
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Prediction on Permeability Coefficient of Continuously Graded Coarse-Grained Soils: A Data-Driven Machine Learning Method by Jinhua Wang, Haibin Ding, Lingxiao Guan, Yulin Wang

“…Three machine learning models—a neural network model (BPNN), a regression model (GPR), and a tree-based model (RF)—were employed to predict <i>k</i>, with hyperparameters optimized via particle swarm optimization (PSO) and four-fold cross-validation applied to improve generalization. …”
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SELECTING THE OPTIMAL SCENARIO FOR THE SIMULTANEOUS APPLICATION OF DIAMOND WIRE CUTTING AND CHAINSAW MACHINES IN DIMENSIONAL STONE MINES USING SECA MULTI-CRITERIA DECISION-MAKING M... by Abbas Amou, Majid Ataee-pour, Satar Mahdevari

“…In order to find the best scenario to achieve the optimal technical and economic conditions, the SECA decision-making method was used due to the presence of several influential criteria. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…This article presents a symbiotic learning-based Grey Wolf Optimizer (SL-GWO) formulated through the introduction of symbiotic hunting and learning strategies to achieve a better trade-off between exploration and exploitation while standing immune to the curse of dimensionality. …”
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Research on Configuration Optimization and Control Methods for Mid-Deep Geothermal Heat Pumps Coupled with Air-Source Heat Pump Systems for Space Heating in Residential Buildings by Yanhui Wang, Jiewen Deng, Yangyang Su, Chenwei Peng, Minghui Ma, Yin Chen, Lei Fan, Min Chen, Qingpeng Wei, Hui Zhang

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Optimization and Validation of a QuEChERS-Based Method Combined with Gas Chromatography–Tandem Mass Spectrometry for Analyzing Pesticide Residues in Edible Insect Samples by Phannika Tongchai, Nootchakarn Sawarng, Anurak Wongta, Udomsap Jaitham, Kunrunya Sutan, Saweang Kawichai, Chuleui Jung, Bajaree Chuttong, Surat Hongsibsong

“…The method was optimized by evaluating various extraction parameters and showed strong linearity for all 47 target pesticides, with correlation coefficients (R²) ranging from 0.9940 to 0.9999. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…To address this issue, this paper proposes an optimized YOLOv8n algorithm, incorporating a C2f-DynamicConv optimization module. …”
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Particle Swarm Optimization with Various Inertia Weight Variants for Optimal Power Flow Solution by Prabha Umapathy, C. Venkataseshaiah, M. Senthil Arumugam

“…This paper proposes an efficient method to solve the optimal power flow problem in power systems using Particle Swarm Optimization (PSO). …”
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Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer by Yulong Chai, Xiuqing Chai, Lan Zhang, Gang Ye, Fatima Rashid Sheykhahmad

“…Due to its effectiveness in search space exploration while avoiding local optimal points, the IAPO algorithm is chosen to optimize the convolutional neural network. …”
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Hybrid proton planning combining spread-out Bragg peak beams with transmission beams to shorten field delivery times while maintaining plan quality by Roni Hytönen, Reynald Vanderstraeten, Wilko F.A.R. Verbakel

“…In this study, we investigated the trade-offs in field delivery times (FDT) and plan quality when using both field types. Materials and methods: Reference treatment plans were created for eight left-sided breast and ten oropharynx cancer patients using an in-house automatic iterative optimizer. …”
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Method for constructing an adaptive suboptimal stationary train traffic controller based on artificial neural networks by S. V. Malakhov, M. Yu. Kapustin

“…Adequacy check is not part of the known methods of optimal control theory. To eliminate this drawback, it is proposed to use the method of optimal (suboptimal) traction calculations based on artificial neural networks. …”
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An optimized anomaly detection framework in industrial control systems through grey wolf optimizer and autoencoder integration by Muhammad Muzamil Aslam, Liyanage Chandratilak De Silva, Rosyzie Anna Awg Haji Mohd Apong, Ali Tufail

“…The method operates in two stages: (1) Optimizing GWO for feature selection to identify relevant features and reduce feature errors, and (2) Utilizing AE for efficient anomaly detection. …”
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Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…The proposed method is designed to achieve a better balance between exploration and exploitation with minimal tuning while overcoming the limitations of SGO. …”
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Development of Eccentric Transmitter Transducer for LWD Acoustic Remote Detection by SUN Zhifeng, QIU Ao, LIU Xien, LUO Bo, LI Jie, ZHAO Han

“…Numerical simulations of the transducer’s vibration modes, frequency response, and emission voltage level (EVL) are conducted via the finite element method, followed by prototype fabrication and anechoic tank testing. …”
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A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process by Partha Protim Das

“…This paper attempts to demonstrate the applicability of three well-known multi-criteria decision-making (MCDM) techniques, including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), multi-attributive border approximation area comparison (MABAC), and complex proportional assessment (COPRAS) methods, separately hybridized with the grey wolf optimization (GWO) algorithm. …”
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