Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE by Muhammad Sarmad Mahmood, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Syed Salman Ahmad Zaidi, Muwaffaq Alqurashi, Hawreen Ahmed, Muhammad Adnan, Abdul Hakim Hotak

“…This study aims to evaluate the compressive strength (CS) of high strength glass-powder concrete (HSGPC) using machine learning (ML) models and enhance predictive accuracy through hybrid optimization techniques. …”
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Trade-off analysis of machinability of steel alloy AISI 304L using Taguchi-grey integrated approach by Faisal Abbas, Muhammad Ali Khan, Muhammad Iftikhar Faraz, Syed Husain Imran Jaffery, Sohail Akram, Jana Petru, Refka Ghodhbani, Walid M. Shewakh

“…Nevertheless, surface quality and production rates also hold significant value for overall optimization of any manufacturing setup. In fact, machinability of a material can only be assessed by collectively optimizing all machining responses. …”
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Model Complexity Reduction for ZKML Healthcare applications by Sathya Krishnasamy, Ilangovan Govindarajan

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An Optimized Weighted-Voting-Based Ensemble Learning Approach for Fake News Classification by Muhammad Shahzaib Toor, Hooria Shahbaz, Muddasar Yasin, Armughan Ali, Norma Latif Fitriyani, Changgyun Kim, Muhammad Syafrudin

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Design optimization of inner and outer‐rotor PMSGs for X‐ROTOR wind turbines by Reza Yazdanpanah, Seyed Abolfazl Mortazavizadeh, Mohammad Salehian, David Campos‐Gaona, Olimpo Anaya‐Lara

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Predicting bearing capacity of gently inclined bauxite pillar based on numerical simulation and machine learning by Deyu WANG, Defu ZHU, Biaobiao YU, Chen WANG

“…Support Vector Machine (SVM), Extreme Learning Machine (ELM) and Light Gradient Boosting Machine (LightGBM) were used to construct the model for predicting the strength of gently inclined pillars. …”
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Automatic model of sleep apnea detection using optimized weighted fusion process of hybrid convolution (1D/2D) efficient attention network from EEG signals by R. Nandakumar, Rajesh Arunachalam, R Pugalenthi, Karthikayen Arunachalam

“…Then, the resultant features are fused with the optimized weight and it is designated as F2. Here the weight in DRBM is optimized using the improved Eurasian oystercatcher optimizer (IEOO). …”
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Enhancing Electricity Consumption Forecasting in The Republic of Kazakhstan Using Machine Learning by Vladimir Madin, Olga Salykova, Irina Ivanova, Olga Bizhanova, Dinara Aldasheva

“…This study enhances electricity consumption forecasting in Kazakhstan using machine learning models, improving accuracy and energy management. …”
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Trajectory Tracking of a Wall-Climbing Cutting Robot Based on Kinematic and PID Joint Optimization by Xiaoguang Liu, Zhenmin Wang, Jing Wu, Hongmin Wu, Hao Zhang

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Application of inertial navigation high precision positioning system based on SVM optimization by Ruiqun Han

“…In addition, support vector machines were used to optimize pedestrian trajectory prediction algorithms, and a pedestrian motion state recognition algorithm was designed based on this. …”
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Unveiling degradation patterns in dye-sensitized solar cells: a machine learning perspective by Ahmet Sait Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif

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Identification and Immunological Characterization of Cuproptosis Related Genes in Preeclampsia Using Bioinformatics Analysis and Machine Learning by Tiantian Yu, Guiying Wang, Xia Xu, Jianying Yan

“…The most precise forecasting model was chosen by evaluating the effectiveness of four machine learning models. …”
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Optimal Activity Recognition Framework Based on Improvement of Regularized Neighborhood Component Analysis (RNCA) by Norazman Shahar, Muhammad Amir As'Ari, Tan Tian Swee, Nurul Fathia Ghazali

“…In essence, the combined strength of RNCA and MRMR provides a versatile and effective approach for extracting meaningful features and enhancing the overall performance of machine learning models.…”
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Optimization of welding strength in the tungsten inert gas welding process for aluminium alloys by Amit Gupta, Rajeev Ranjan, Robert Cep, Ajay Kumar, Ajay Kumar, Sanjay Kumar Jha, Faisal Altarazi, Ashish Kumar, Namrata Dogra

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AI-Driven Optimization of Breakwater Design: Predicting Wave Reflection and Structural Dimensions by Mohammed Loukili, Soufiane El Moumni, Kamila Kotrasova

“…This study leverages machine learning (ML) to predict the optimal 2D dimensions of rectangular breakwaters in two configurations: submerged at the bottom of a wave tank and positioned at the free surface. …”
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Learning to Optimize Joint Chance-Constrained Power Dispatch Problems by Meiyi Li, Javad Mohammadi

“…To overcome the shortcomings of today&#x0027;s solvers, we propose a fast, scalable, and explainable machine learning-based optimization proxy. Our solution, called Learning to Optimize the Optimization of Joint Chance-Constrained Problems <tex>$(\mathcal{LOOP}-\mathcal{JCCP})$</tex>, is iteration-free and solves the underlying problem in a single-shot. …”
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Eye Collateral Channel Characteristic Analysis and Identification Model Construction of Mild Cognitive Impairment by WU Tiecheng, CAO Lei, YIN Lianhua, HE Youze, LIU Zhizhen, YANG Minguang, XU Ying, WU Jinsong

“…Based on the MCI identification model of eye collateral channel characteristics and TCM syndrome elements, the support vector machine model was selected as the optimal discriminant model, with an accuracy of 73.08%, a sensitivity of 0.677, a specificity of 0.765, and an AUC of 0.777. …”
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Enhanced convolutional neural networks for defect detection in fiber-reinforced composites: a hyperparameter optimization approach by Pankaj Beldar, Rasika Chandramore, Sarika Jagtap, Dipali Bendale

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Performance evaluations of AI-based obfuscated and encrypted malicious script detection with feature optimization by Kookjin Kim, Jisoo Shin, Jong-Geun Park, Jung-Tae Kim

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Optimizing timing and cost-effective use of plasma biomarkers in Alzheimer’s disease by Hsin-I Chang, Mi-Chia Ma, Kuo-Lun Huang, Chung-Gue Huang, Shu-Hua Huang, Chi-Wei Huang, Kun-Ju Lin, Chiung-Chih Chang

“…This study evaluates the diagnostic accuracy of a combined-panel approach using machine learning models and evaluated the biomarker significance. …”
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