Enhanced Hyperspectral Forest Soil Organic Matter Prediction Using a Black-Winged Kite Algorithm-Optimized Convolutional Neural Network and Support Vector Machine by Yun Deng, Lifan Xiao, Yuanyuan Shi

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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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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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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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Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology by Raoof Nopour

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Truck Transportation Scheduling for a New Transport Mode of Battery-Swapping Trucks in Open-Pit Mines by Yufeng Xiao, Wei Zhou, Boyu Luan, Keyi Yang, Yuqing Yang

“…The primary objective is to minimize the total haulage cost and total waiting time. Both a genetic algorithm and an adaptive genetic algorithm are applied to solve the proposed multi-objective scheduling optimization model. …”
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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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A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…Additionally, the improved dynamic PSO algorithm optimizes feature selection in real time, enhancing classification accuracy and adaptability to evolving IoT network threats. …”
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A Virtual Power Plant-Integrated Proactive Voltage Regulation Framework for Urban Distribution Networks: Enhanced Termite Life Cycle Optimization Algorithm and Dynamic Coordination by Yonglin Li, Zhao Liu, Changtao Kan, Rongfei Qiao, Yue Yu, Changgang Li

“…While virtual power plants (VPPs) and network reconfiguration mitigate operational risks, extant methods inadequately model load flexibility and suffer from algorithmic stagnation in non-convex optimization. …”
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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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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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Evaluating energy efficiency in Turkish electric distribution using network DEA and GA models by Serpil Aydin, Talat Şenel

“…This shows that Sakarya EDC operates optimally and is a benchmark for other companies in the sector. …”
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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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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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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

“…This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet and Gated Recurrent Unit (GRU) networks, optimized using the Hippopotamus Optimization Algorithm (HOA). …”
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Optimizing oil production forecasts in Iranian oil fields: a comprehensive analysis using ensemble learning techniques by Mohammad Ghodsi, Pouya Vaziri, Mahdi Kanaani, Behnam Sedaee

“…The inclusion of advanced optimization strategies, such as Genetic Algorithm (GA), Teaching-Learning-Based Optimization (TLBO), and Particle Swarm Optimization (PSO), ensures that each base model reaches its highest potential performance. …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…Subsequently, six machine learning (ML) models were developed and compared to identify the optimal model. …”
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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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Ways to improve the efficiency of automatic control systems of pressing current collectors for railway service of high speeds by A. S. GOLUBKOV, O. A. SIDOROV, S. N. SMERDIN

“…For the considered current collector model, the optimal values of the controller coefficients are kp = 1.5 and ki= 1.0. …”
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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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