Flood risk mapping and performance efficiency evaluation of machine learning algorithms: Best practice in northern Iran by M. Shirmohammadi, M. Shirmohammadi, S. Pirasteh, W. Li, D. Mafi-Gholami

“…For the analysis, we selected a comprehensive set of environmental and geographical parameters influencing flood susceptibility. …”
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Optimizing HVAC&R System Efficiency and Comfort Levels Using Machine Learning-Based Control Methods by Suroor M. Dawood, Raad Z. Homod, Alireza Hatami

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Strain promoted azide alkyne cycloaddition, an efficient surface functionalization strategy for microRNA magnetic separation by Djamila Kechkeche, Sirine El Mousli, Claire Poujouly, Emilie Secret, Vincent Dupuis, Isabelle Le Potier, Marie-Emmanuelle Goriot, Julien Siracusa, Sébastien Banzet, Jean Gamby, Jean-Michel Siaugue

“…Capture of the targeted miRNA by magnetic separation was then studied in buffered model media and in complex biological media. This study showed that MNP allowed magnetically-assisted extraction of target miRNA with good hybridization yields, even in biological media for which the capture capacity was preserved at around 75 %, with rapid kinetics and satisfactory selectivity.…”
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Constrained search space selection based optimization approach for enhanced reduced order approximation of interconnected power system models by Bala Bhaskar Duddeti, Asim Kumar Naskar, V. P. Meena, Jitendra Bahadur, Ibrahim A. Hameed

“…Abstract Metaheuristic search-based optimization strategies have recently emerged to obtain approximated models for interconnected complex power systems. However, these algorithms are frequently criticized for randomly selecting lower and upper search space boundaries and taking longer to simulate. …”
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RLEAFS: Reinforcement Learning-Based Energy Aware Forwarding Strategy for NDN-Based IoT Networks by Naeem Ali Askar, Adib Habbal

“…Our Strategy integrates Q learning algorithm into path selection procedure, focusing on minimizing energy consumption and extending network lifetime while maintaining efficient data delivery. …”
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Developing a hybrid machine learning model for employee turnover prediction: Integrating LightGBM and genetic algorithms by Hojat Talebi, Amid Khatibi Bardsiri, Vahid Khatibi Bardsiri

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Selection Method and Application of Dual-Mode TBM in Composite Strata: A Case Study of Shenzhen Metro Line 14 by Jizheng Huang, Xiaoyue Kang, Gaoyu Ma, Fan Chen, Shimin Wang, Renbin Luo

“…While dual-mode TBM selection requires comprehensive consideration of the combined effects of efficiency, duration, and cost related to the distribution of different strata. …”
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Coupled intelligent prediction model for medium- to long-term runoff based on teleconnection factors selection and spatial-temporal analysis. by Jintao Li, Ping Ai, Chuansheng Xiong, Yanhong Song

“…For instance, the RF-MLPR model achieved a 3.7%-6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R2 value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
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Optimization of Rockburst Grade Prediction Model Based on Multidimensional Feature Selection: Integrated Learning and Index System Correlation Analysis by Jiayang Chen, Xuebin Xie

“…The six-dimensional system in both types of systems can balance the performance and complexity and is the optimal choice for engineering applications. …”
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Integration of the analytic hierarchy process and Monte Carlo feature selection for a spatiotemporal weighting scheme in meteorological drought monitoring by Muhammad Hamza, Rizwan Niaz, Ibrahim Ali H Nafisah, Luca Di Persio, Abdulkareem M. Basheer, Mohammed M. A. Almazah

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Consistency and Stability in Feature Selection for High-Dimensional Microarray Survival Data in Diffuse Large B-Cell Lymphoma Cancer by Kazeem A. Dauda, Rasheed K. Lamidi

“…High-dimensional survival data, such as microarray datasets, present significant challenges in variable selection and model performance due to their complexity and dimensionality. …”
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Lung and Colon Cancer Classification Using Multiscale Deep Features Integration of Compact Convolutional Neural Networks and Feature Selection by Omneya Attallah

“…The experimental results exhibited outstanding performance, attaining 99.8% classification accuracy with cubic SVM classifiers employing merely 50 ANOVA-selected features, exceeding the performance of individual CNNs while markedly diminishing computational complexity. …”
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Selection of Frequency Estimation of 6-10 kV-Overhead Lines’ Technical Condition Based on Reliability Statistical Studies by Basmanov V.G., Kholmanskikh V.M.

“…The most essential result is the experimental and theoretical confirmation that the complex indicator of reliability, i.e., the technical preparedness coefficient with account of self-eliminating failures, can be used as the frequency criterion for verification of the OL technical condition. …”
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Efficient Access to New Thienobenzo-1,2,3-Triazolium Salts as Preferred Dual Cholinesterase Inhibitors by Milena Mlakić, Maja Sviben, Ana Ratković, Anamarija Raspudić, Danijela Barić, Ivana Šagud, Zlata Lasić, Ilijana Odak, Irena Škorić

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Enhanced framework for credit card fraud detection using robust feature selection and a stacking ensemble model approach by Rahul Kumar Gupta, Asmaul Hassan, Samir Kumar Majhi, Nikhat Parveen, Abu Taha Zamani, Raju Anitha, Binayak Ojha, Abhinav Kumar Singh, Debendra Muduli

“…With the increase in online payment volumes, conventional fraud detection technologies are increasingly confronted by the complexity of fraudulent strategies that require intelligent and scalable alternatives. …”
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Criteria Analysis for the Selection of a Generative Artificial Intelligence Tool for Academic Research Based on an Improved Group DEMATEL Method by Constanta Zoie Radulescu, Marius Radulescu

“…Generative Artificial Intelligence (GenAI) tools are transforming academic research by significantly enhancing efficiency, accuracy, and productivity. However, selecting the most appropriate GenAI tool requires careful evaluation of multiple, interdependent criteria. …”
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An Efficient Fine-Grained Recognition Method Enhanced by Res2Net Based on Dynamic Sparse Attention by Qifeng Niu, Hui Wang, Feng Xu

“…This paper presents an efficient architecture built upon the Res2Net backbone, significantly enhanced by a dynamic Sparse Attention mechanism. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…The choice of the k-value significantly impacts the model's performance, and traditional methods, such as random selection or selection based on empirical knowledge, often lead to suboptimal outcomes. …”
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Enhancing 3D A* path planning of intelligent bridge crane based on energy efficiency criteria by Heng YANG, Yue LI, Min LIU, Qing DONG

“…To address the problems of traditional three-dimensional (3D) A* algorithm, such as low planning efficiency, numerous path inflection points, and increased path complexity when the target point is surrounded by obstacles, a 3D A* path-planning algorithm based on energy efficiency criteria is proposed in this study. …”
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Insights into Phase Transformations during Selective Laser Melting of Ti6Al4V: A Numerical Approach by Gasser Abdelal, Daniel Higgins, Chi-Wai Chan, Brian Falzon

“…Selective Laser Melting (SLM) is a transformative additive manufacturing technique that enables the production of complex metallic components with high precision. …”
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