Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

“…The construction industry increasingly embraces machine learning (ML) to estimate concrete properties and optimize cost and time accurately. …”
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Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
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Optimizing EV charging stations and power trading with deep learning and path optimization. by Qing Zhu

“…A Long Short-Term Memory (LSTM) model was employed to predict regional EV charging demand, improving forecasting accuracy by 12.3%. …”
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The AlexNet HSD model for industrial heritage damage detection and adaptive reuse under artificial intelligence by Huiling Zhang

“…By integrating the Convolutional Block Attention Module (CBAM) and Support Vector Machine (SVM), an AlexNet HSD + CBAM + SVM (AlexNet HCS) model is proposed to enhance the performance of industrial heritage damage detection. …”
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A Fused Multiscale Pictorial Sequence Learning Mechanism Applied to Pavement Detection by Zhang Jiazhen, Wang Xiulai, Zhao Shuxu

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Plastic Injection Molding Process Analysis: Data Integration and Modeling for Improved Production Efficiency by Jose Isidro Hernández-Vega, Luis Alejandro Reynoso-Guajardo, Mario Carlos Gallardo-Morales, María Ernestina Macias-Arias, Amadeo Hernández, Nain de la Cruz, Jesús E. Soto-Soto, Carlos Hernández-Santos

“…This paper presents a comprehensive analysis of the plastic injection molding process through the integration of data acquisition technologies and classification models. In collaboration with a company specializing in plastic injection, data were extracted directly from the machine during a specific period at the beginning of a shift change. …”
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Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model by Feng Cui, Xiangji Dang, Daiyun Peng, Yuanhua She, Yubin Wang, Ruifeng Yang, Zhiyao Han, Yan Liu, Hanteng Yang

“…Among the five machine learning algorithms developed, the LightGBM model demonstrated strong performance in the 3-year and 5-year survival prediction tasks, making it the optimal model selection. …”
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Interpretable Machine Learning Framework for Corporate Financialization Prediction: A SHAP-Based Analysis of High-Dimensional Data by Yanhe Wang, Wei Wei, Zhuodong Liu, Jiahe Liu, Yinzhen Lv, Xiangyu Li

“…The methodology simultaneously addresses high-dimensional feature selection using 40 independent variables (19 CSR-related and 21 financialization-related), multicollinearity issues, and model interpretability requirements. Using a comprehensive dataset of 25,642 observations from 3776 Chinese A-share companies (2011–2022), we implement nine optimized machine learning algorithms with hyperparameter tuning via the Hippopotamus Optimization algorithm and five-fold cross-validation. …”
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A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study by Rui-Tao Sun, Chang-Lei Li, Yu-Min Jiang, Ao-Yun Hao, Kui Liu, Kun Li, Bin Tan, Xiao-Nan Yang, Jiu-Fa Cui, Wen-Ye Bai, Wei-Yu Hu, Jing-Yu Cao, Chao Qu

“…A combination of radiomic and clinical features was selected using the Boruta-LASSO algorithm. Predictive models were constructed using six machine learning algorithms and validated, with model performance evaluated based on the AUC, accuracy, Brier score, and DCA to identify the optimal model. …”
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Predicting age at first calving of dairy breed calves using whale optimization-based ensemble learning framework by Tewodros Shekure, Hussien Seid Worku, Sudhir Kumar Mohapatra, Tapan Kumar Das

“…Furthermore, an ensemble of SVR, LSVR, NuSVR is designed, and the framework is trained by optimized features of data. The designed model achieved an accuracy of 98.3% superseding the other combinations.…”
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Design and Optimization of a Fan-Out Wafer-Level Packaging- Based Integrated Passive Device Structure for FMCW Radar Applications by Jiajie Yang, Lixin Xu, Ke Yang

“…Using this metric as a loss function, we apply the support vector machine (SVM) for electromagnetic simulation and the genetic algorithm (GA) for optimization. …”
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MODELING AS A TOOL FOR PREDICTING THE PRODUCTIVE CAPACITY OF WOOD HARVESTING: APPROACH OF FELLER-BUNCHER AND HARVESTER by Francisco de Assis Costa Ferreira, Cássio Furtado Lima, Luciano José Minette, Roldão Carlos Andrade Lima, Luis Carlos de Freitas, Fernanda Araujo Lima, Lucas Moraes Rufini de Souza, Bruno Leão Said Schettini, Arthur Araújo Silva, Leonardo França da Silva, Pedro Paulo Almeida Junior, Elton da Silva Leite, Leonardo Carneiro Freitas de Oliveira

“…This study addressed the analysis of the productive capacity of two important wood harvesting machines, the Feller-Buncher, and the Harvester, with an objective to propose a technical modeling to optimize the logistics associated with these machines. …”
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Response Modeling and Optimization of Process Parameters in Turning Medium Carbon Steel Under Minimum Quantity Lubrication (MQL) with Vegetable Oil and Oil Blends by Indranil Das, Prianka Binte Zaman

“…Machining is an important aspect of manufacturing. …”
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Fractional-Order LC Three-Phase Inverter Using Fractional-Order Virtual Synchronous Generator Control and Adaptive Rotational Inertia Optimization by Junhua Xu, Chunwei Wang, Yue Lan, Bin Liu, Yingheng Li, Yongzeng Xie

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Integrating autoencoder and decision tree models for enhanced energy consumption forecasting in microgrids: A meteorological data-driven approach in Djibouti by Fathi Farah Fadoul, Abdoulaziz Ahmed Hassan, Ramazan Çağlar

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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…Additionally, it employs eight machine learning models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Bayesian Regression Neural Network (BRNN), Elastic Net (EN), K-Nearest Neighbors (KNN), Extremely Randomized Trees (ETR), and Stochastic Gradient Boosting (SGBoost)—to estimate forest AGB in Wuyi Village, Zhenyuan County. …”
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Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins by Ahmed Elbeltagi, Abdullah A. Alsumaiei, Ali Raza, Mustafa Al-Mukhtar, Salim Heddam

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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. …”
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Development and Validation of a Nomogram Prediction Model for In-hospital Mortality in Patients with Cardiac Arrest: A Retrospective Study by Peifeng Ni, Shurui Xu, Weidong Zhang, Chenxi Wu, Gensheng Zhang, Qiao Gu, Xin Hu, Ying Zhu, Wei Hu, Mengyuan Diao

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Investigating the Impact of Drill Point Angles on the Drilling Behavior of Date Palm Biocomposites: Experimental, ANN, and Taguchi Modeling by Riyadh Benyettou, Salah Amroune, Mohamed Slamani, Mohammad Jawaid, Alain Dufresne, Hassan Fouad, Tarek Bidi

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