Multiple PM Low-Cost Sensors, Multiple Seasons’ Data, and Multiple Calibration Models by S Srishti, Pratyush Agrawal, Padmavati Kulkarni, Hrishikesh Chandra Gautam, Meenakshi Kushwaha, V. Sreekanth

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Novel Optimized Support Vector Regression Networks for Estimating Fresh and Hardened Characteristics of SCC by Babak Naeim, Ali Javadzade Khiavi, Parisa Dolatimehr, Behnam Sadaghat

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Forecasting Dissolved Organic Carbon Levels Utilizing Metaheuristic Optimization with Artificial Intelligence Techniques by Peng He, Chengjun Ma

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Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

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The Optimal Machine Learning Model for the Precise Prediction of HighPerformance Concrete Strength Property by Yufeng Qian

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Analysis of inductive power transfer systems by metamodeling techniques by Pei, Yao, Pichon, Lionel, Bensetti, Mohamed, Le Bihan, Yann

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Appraising the Pile Settlement Rates by Support Vector Regression Optimized Using the Novel Optimization Algorithms by Argyros Maris

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Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization by Saravana Kumar, Savarimuthu Robinson

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Hourly Ozone and PM2.5 Prediction Using Meteorological Data – Alternatives for Cities with Limited Pollutant Information by Felipe Cifuentes, Angel Gálvez, Carlos M. González, Mauricio Orozco-Alzate, Beatriz H. Aristizábal

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Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA by Francisca Blanco, Ye Woo

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Estimation of the Compressive Strength of Self-Compacting Concrete (SCC) by a Machine Learning Technique Coupling with Novel Optimization Algorithms by Ling Chen, Wengang Jiang

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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization by Lian-Hua Zhang, Ze-Hong Deng, Wen-Bo Wang

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Novel Optimization Algorithms Usage to Model the Compressive Strength of Ultra-High-Performance Concrete in Machine Learning Technique: Support Vector Regression by Tianhua Zhou, Dorota Mozyrska

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The Implementation of a Support Vector Regression Model Utilizing Meta-Heuristic Algorithms for Predicting Undrained Shear Strength by Rami Al-Qasimi, Firas Al-Hajri

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Harnessing synergy of machine learning and nature-inspired optimization for enhanced compressive strength prediction in concrete by Abba Bashir, Esar Ahmad, Shashivendra Dulawat, Sani I. Abba

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