DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…Due to incorporation of dual bioinspired optimizers with autoregressive correlation, the model is able to improve prediction accuracy by 8.5%, precision by 4.9%, recall by 1.5%, while reducing computational delay by 3.4% when compared with standard air quality analysis models. …”
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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. …”
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Multi-Objective Optimal Power Flow of Integrated Transmission and Distribution Network Considering Node Carbon Emission Intensity by ZHANG Xianglong, YUAN Zhaoxiang, DONG Shufeng, LIU Ying, XIAO Zhihong, TIAN Yuzhou

“…[Methods] To address these challenges， a collaborative distributed optimal power flow model based on a heterogeneous decomposition algorithm was proposed. …”
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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…Using dimensional analysis, key factors are transformed into dimensionless numbers, which are then input into models integrating least squares support vector machine (LSSVM) with genetic algorithm (GA), particle swarm optimization (PSO), and a hybrid GA-PSO (HGAPSO). …”
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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

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Learning‐based tracking control of AUV: Mixed policy improvement and game‐based disturbance rejection by Jun Ye, Hongbo Gao, Manjiang Hu, Yougang Bian, Qingjia Cui, Xiaohui Qin, Rongjun Ding

“…By combining prior dynamic knowledge and actual sampled data, the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm. …”
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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…【Method】The model uses sample entropy reconstruction and the K-means clustering algorithm to optimize the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) process, generating multiple intrinsic mode functions (IMF). …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Multi-objective optimization of current-assisted splitting spinning of small module tooth-shaped part based on the combination of BP neural network and NSGA-II algorithm by Zhou Haoyang, Xia Qinxiang, Xiao Gangfeng, Chen Can

“…The results show that the material at the tooth tip along the radial direction is in the state of tensile stress along radial and compressive stresses along tangential and axial directions, which promotes the radial flowing of the material and is beneficial the tooth filling of SMTSPs; the tooth saturation increases obviously under pulse current comparing without pulse current; the BPNN combined with the NSGA-II algorithm can reliably optimize the process parameters of the CASS, improving the forming quality of SMTSPs; experiments verified the feasibility of the process and the accuracy of the predictive model based on the optimization results.…”
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Improved FraSegNet-Based Rock Nodule Identification Method and Application by Yanbo Zhang, Guanghan Zhang, Qun Li, Xulong Yao, Hao Zhou

“…This study presents an enhanced version of the FraSegNet algorithm, focusing on improving its ability to identify nodal features in images. …”
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Mod Tanh‐Activated Physical Neural Network MPPT Control Algorithm for Varying Irradiance Conditions by Khuong Nguyen‐Vinh, Surender Rangaraju, Michal Jasinski

“…ABSTRACT The increasing adoption of solar photovoltaic systems necessitates efficient maximum power point tracking (MPPT) algorithms to ensure optimal performance. This study proposes a Mod tanh‐activated physical neural network (MAPNN)‐based MPPT control algorithm, which addresses inefficiencies in existing models caused by spectral mismatch and improper converter control. …”
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Optimization analysis of air cooled open cathode proton exchange membrane fuel cell flow channel structure by Zhijun Deng, Qingwei Wang, Xun Fang, Yaru Han, Kunxiang Liu, Chen Zhao

“…In addition, in order to further improve the power density of the fuel cell, two agent models, support vector regression and Gaussian process regression, are constructed and trained, and a genetic algorithm is used to find the parameter optimization for the bending angle, width and height of the cathode channel. …”
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Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm by Andranik S. Akopov, Levon A. Beklaryan

“…To achieve this goal, a new multiagent hybrid clustering-assisted genetic algorithm (MA-HCAGA). The proposed algorithm combines the use of binary-coded crossovers and mutations as genetic operators, and biobjective discrete particle swarm optimization (BODPSO) techniques to improve the evolutionary search process. …”
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A cross-chain model for warehouse receipts in port supply chain based on notary mechanism and ShangMi cryptographic algorithms by Yangbo Chen, Wei Ou, Mengxue Pang, Jianqiang Ma, Qiuling Yue, Wenbao Han

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Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…To address the challenge of multiple possible paths due to missing trajectory data, this study proposes a novel two-stage model for vehicle path reconstruction. In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. …”
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Gradient descent based dynamic optimization for VSG dominated microgrid by Yan Li, Decheng Wang, Qun Zhang, Jian Du, Qinshan Wang, Qiong Wang

“…This article proposes an optimization method based on the gradient descent algorithm to fine‐tune the control parameters of multiple VSGs in independent microgrids. …”
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Optimal Autonomous Control for Distribution Transformer Area With High Photovoltaic Penetration Based on CSBO-LSTM by Yukai Wei, Chun He, Zhuo Chen, Yinyuan Guo, Zongyuan Li

“…To enhance the autonomous control capability of transformer area with high PV penetration, this paper proposes a “data-model” dual-driven collaborative optimization model that integrates the Circulatory System Based Optimization (CSBO) algorithm and Long Short-Term Memory (LSTM), constructing an architecture of “offline optimization-knowledge migration-online inference”. …”
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A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain by Guan Lian, Yingzi Wu, Weizhen Luo, Wenyong Li, Yaping Zhang, Xiaoyue Zhang

“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
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Improving energy efficiency for intelligent reflecting surface assisted PD-NOMA in EH relaying network by Hong Nguyen-Thi, Thuc Kieu-Xuan, Thang Le-Nhat, Anh Le-Thi

“…To determine the efficiency of PSO, we consider two other techniques: Genetic Algorithm (GA) and Exhaustive Search (ES). Finally, we evaluate the proposed model's performance in different scenarios, such as the number of IRS elements and the number of relay nodes, the relaying selection strategies, and the transmit power at the BS. …”
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A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…The model is trained on a dataset comprising 1536 samples, which were annotated using an automatic labeling algorithm and expanded to 7680 samples through data augmentation techniques. …”
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