Comprehensive Assessment of Indoor Thermal in Vernacular Building Using Machine Learning Model with GAN-Based Data Imputation: A Case of Aceh Region, Indonesia by Muslimsyah Muslimsyah, Safwan Safwan, Andri Novandri

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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…Optimized hyperparameters with PBO effectively decreased RMSE, MAE, and MAPE and improved the model prediction, showcasing the capability of the PBO in hyperparameter tuning for STLF. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction by L. Raymond Guo, Jifu Tan, M. Courtney Hughes

“…Machine learning models (random forest, gradient boosting machine, support vector machine) were trained and optimized on the training data. …”
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High quality large‐scale nickel‐rich layered oxides precursor co‐precipitation via domain adaptation‐based machine learning by Junyoung Seo, Taekyeong Kim, Kisung You, Youngmin Moon, Jina Bang, Waunsoo Kim, Il Jeon, Im Doo Jung

“…Our domain adaptation based machine learning model, which accounts for equipment wear and environmental variations, achieves a defect detection accuracy of 97.8% based on machine data and process conditions. …”
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A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

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Exploring Kernel Machines and Support Vector Machines: Principles, Techniques, and Future Directions by Ke-Lin Du, Bingchun Jiang, Jiabin Lu, Jingyu Hua, M. N. S. Swamy

“…Related topics, including optimizing model architecture, are also discussed. We conclude by outlining future directions for kernel machines and SVMs. …”
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Toward Symmetry in Accessible Restrooms Design: Integrating KE, RST, and SVM for Optimized Emotional-Functional Alignment by Zimo Chen, Jingwen Tian, Hongtao Zhou, Duan Wu

“…This study develops an integrated Kansei Engineering (KE)–Rough Set Theory (RST)–Support Vector Machine (SVM) workflow that converts user emotions into verifiable design guidelines. …”
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Neural Network-Based Optimization for Bandwidth Enhancement of Millimeter-Wave Franklin Antenna With Proximity-Coupled Feed by Ahmad Firdausi, Eko Setijadi, Gamantyo Hendrantoro, Mudrik Alaydrus

“…The antenna performance evaluation comprises of a comprehensive technique that combines simulation, measurement, and development of R-L-C equivalent circuit models, as well as the application of machine learning methods. …”
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Prediction of Pollutant Emissions from a Low-Speed Marine Engine Based on Harris Hawks Optimization and Lightgbm by Yue Chen, Yulong Shen, Miaomiao Wen, Cunfeng Wei, Junjie Liang, Yuanqiang Li, Ying Sun

“…To further improve the forecast performance of the LGB model, we used Harris Hawks Optimization (HHO) to automatically optimize the hyperparameters of the model, and finally, we analyzed the importance of the model features. …”
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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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Optimizing Energy and Spectral Efficiency in Mobile Networks: A Comprehensive Energy Sustainability Framework for Network Operators by Luis Mata, Marco Sousa, Pedro Vieira, Maria Paula Queluz, Antonio Rodrigues

“…This framework supports network auditing, benchmarking, monitoring, and energy efficiency optimization while ensuring the desired Quality of Service (QoS). …”
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Penetration Testing and Machine Learning-Driven Cybersecurity Framework for IoT and Smart City Wireless Networks by Tamara Zhukabayeva, Zulfiqar Ahmad, Aigul Adamova, Nurdaulet Karabayev, Yerik Mardenov, Dina Satybaldina

“…Anomalies were identified using an optimized Isolation Forest model, revealing patterns such as unusual activity involving the Tenda_476300 WiFi network. …”
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Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines by YANG Xueqi, GAO Xinqin, ZHENG Haiyang, YANG Jun

“…Finally, combined with examples, the 3D visualization health condition monitoring system of the anchor digging machine was developed, which realized the data mapping between the integrated coal mining working face and the 3D visualization model and verified the correctness and feasibility of the method proposed in this study.Results and DiscussionsFor the performance validation experiments of the SDAE‒DT Net model, the sensitivity analysis experiments for PSO hyperparameter optimization showed that the best results were achieved when the population size and inertia factor were 40 and 0.5, respectively. …”
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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We demonstrate the overall effectiveness of the proposed model by using it to select the optimal features extracted from the Resnet50V2 model for pediatric brain tumor detection. …”
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Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…Experiments conducted with seven diverse machine learning algorithms (Adaptive Boosting, Extreme Gradient Boosting, Decision Trees, k-Nearest Neighbors, Logistic Regression, Random Forest, and Support Vector Machine) demonstrate that the proposed blending solution, utilizing an LR meta-model with three optimal base models, achieves a superior classification accuracy of 96.48%, offering an effective tool for clinical decision support.…”
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Machine Learning-Assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength–Cost–CO₂ Emissions Trade-Offs by Yuzhuo Zhang, Jiale Peng, Zi Wang, Meng Xi, Jinlong Liu, Lei Xu

“…To address this gap, this study proposes an AI-assisted framework integrating machine learning (ML) and Multi-Objective Optimization (MOO) to achieve a sustainable GPC design. …”
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A novel CFD-MILP-ANN approach for optimizing sensor placement, number, and source localization in large-scale gas dispersion from unknown locations by Yiming Lang, Michelle Xin Yi Ng, Kai Xiang Yu, Binghui Chen, Peng Chee Tan, Khang Wei Tan, Weng Hoong Lam, Parthiban Siwayanan, Kek Seong Kim, Thomas Shean Yaw Choong, Joon Yoon Ten, Zhen Hong Ban

“…The MILP was used to optimize sensor placement, while the ANN model was used to optimize sensor number. …”
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Predictive Modeling of the Hydrate Formation Temperature in Highly Pressurized Natural Gas Pipelines by Mustafa Karaköse, Özgün Yücel

“…This research illustrates the potential of machine learning techniques in advancing the predictive accuracy for hydrate formations in natural gas pipelines and suggests avenues for future optimizations through hybrid modeling approaches.…”
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Imitation Modeling of Production Processes in FlexSim Environment by E. V. Lapteva, Yu. S. Lekareva, S. S. Umansky

“…The article studies imitation modeling use in agricultural machine-building. Brief description of FlexSim software is provided. …”
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