Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm by V. Parthasaradi, A. Karunamurthy, C. H. Hussaian Basha, S. Senthilkumar

“…The major aim of the research work is to reduce the cost and the execution time as well as to improve the resource utilization of the task scheduling problem using the improved support vector machine (ISVM) and the optimization concept. The novel algorithm used here merges two familiar algorithms as squirrel search algorithm (SSA) and the horse herd optimization algorithm (HOA) leading to a new hybrid metaheuristic algorithm called the horse herd–squirrel search algorithm (HO–SSA). …”
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A toolkit for quantifying individual response to herbal extracts in metabolic and inflammatory stress by Soo-yeon Park, Oran Kwon, Tim van den Broek, Jildau Bouwman, Ji Yeon Kim

“…This study integrated a health space model and machine learning to quantify and visualize the impact of herbal extracts on inflammatory and metabolic health at the individual level. …”
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Research on Heat Transfer Coefficient Prediction of Printed Circuit Plate Heat Exchanger Based on Deep Learning by Yi Su, Yongchen Zhao, Jingjin Wu, Ling Zhang

“…These findings not only validate the efficacy of machine learning and deep learning in complex heat exchanger modeling but also provide critical theoretical support for engineering optimization.…”
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Landslide Susceptibility Mapping in Darjeeling Himalayas, India by Amit Chawla, Sowmiya Chawla, Srinivas Pasupuleti, A. C. S. Rao, Kripamoy Sarkar, Rajesh Dwivedi

“…Genetic Programming and Particle Swarm Optimization-Support Vector Machine have performed well with respect to overall prediction accuracy and validated the landslide susceptibility model generated in the Geographic Information System environment. …”
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Accurate Location Method for Abnormal Line Losses in Distribution Network Considering Topology Matching and Parameter Estimation in Grid by Haiyun An, Qian Zhou, Qiuwei Wu, Yufang Liu, Cheng Huang, Jiaxun Li

“…The accuracy of SVM is enhanced through an optimized parameter selection strategy. Secondly, a multi-objective optimization model is built employing the operation data collected by the measurement equipment, focusing on voltage and power estimation to form a parameter estimation model. …”
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Reliable ECG Anomaly Detection on Edge Devices for Internet of Medical Things Applications by Moez Hizem, Leila Bousbia, Yassmine Ben Dhiab, Mohamed Ould-Elhassen Aoueileyine, Ridha Bouallegue

“…The advent of Tiny Machine Learning (TinyML) has unlocked the potential to deploy machine learning models on resource-constrained edge devices, revolutionizing real-time monitoring in Internet of Medical Things (IoMT) applications. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
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Energy Management Prediction in Hybrid PV-Battery Systems Using Deep Learning Architecture by Mohamad Reda A. Refaai, Shanmukha Naga Raju Vonteddu, Prasanthi Kumari Nunna, P. Suresh Kumar, C. Anbu, Mebratu Markos

“…The proposed model is tested on dynamic electricity costs. Compared with existing energy systems, the proposed strategy and prediction model can handle more than half of the annual load need.…”
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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…We further shed light on the effect of feature selection and optimization on feature attribution and model decision-making processes using the SHapley Additive exPlanations (SHAP) framework, with a particular emphasis on cancer classification using the DMR-IR dataset. …”
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Research on Submarine Cable Buried Depth Monitoring Technology based on Brillouin Effect by WU Kun, WU Mingnian, CHEN Qingqing, WU Zhengming, XIE Shuhong, WANG Daogen, LI Songlin

“…Based on this dataset, a BPNN model is constructed. Through machine learning, the model automatically identifies temperature distribution characteristics to establish a mapping relationship between the temperature of the submarine cable and its burial depth status. …”
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Enhancing Software Quality with AI: A Transformer-Based Approach for Code Smell Detection by Israr Ali, Syed Sajjad Hussain Rizvi, Syed Hasan Adil

“…However, challenges such as low recall (53.0%) and computational overhead indicate the need for further optimization. We present a comprehensive comparative analysis between classical machine-learning models and transformer-based architectures, evaluating their computational efficiency and predictive capabilities. …”
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A Novel Method of Self-Healing Concrete to Improve Durability and Extend the Service Life of Civil Infrastructure by Yan Xue, Weiliang Gao, Yanming Zhao

“…Moreover, a concrete durability prediction model based on particle swarm optimization-least squares support vector machine (PSO-LSSVM) and improved NSGA-II (nondominated sorting genetic algorithm II) algorithm was proposed to quickly and accurately determine the optimization scheme of self-healing concrete mix proportion. …”
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Using SVM Classifier and Micro-Doppler Signature for Automatic Recognition of Sonar Targets by Abbas Saffari, Seyed Hamid Zahiri, Navid Khozein Ghanad

“…The mathematical model used in this paper simulates the return signal of moving sonar targets well. …”
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A neural network-based synthetic diagnostic of laser-accelerated proton energy spectra by Christopher J. G. McQueen, Robbie Wilson, Timothy P. Frazer, Martin King, Matthew Alderton, Ewan F. J. Bacon, Ewan J. Dolier, Thomas Dzelzainis, Jesel K. Patel, Maia P. Peat, Ben C. Torrance, Ross J. Gray, Paul McKenna

“…Abstract Machine learning can revolutionize the development of laser-plasma accelerators by enabling real-time optimization, predictive modeling and experimental automation. …”
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A multi-objective synergistic design for low modulus and high yield strength in complex concentrated alloys by Qingfeng Yin, Yuan Wu, Honghui Wu, Xiaobin Zhang, Suihe Jiang, Hui Wang, Xiongjun Liu, Zhaoping Lu

“…In this study, we developed a machine learning model for multi-objective synergistic optimization of modulus and yield strength, successfully enabling simultaneous prediction of Young’s modulus and yield strength in the Ti-Zr-Hf-Nb-Ta-Mo-Sn alloy system. …”
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Predicting mechanical properties of marble powder concrete using artificial neural networks and blockchain-rock for sustainable construction by Moutaman M. Abbas, Radu Muntean

“…This paper suggests a novel use of artificial neural networks (ANN) and Blockchain-Rock technology to enhance predictive accuracy and assure tracking of data in concrete mix optimization. Using an ANN model trained on 629 data sets, the proposed approach achieved high predictive accuracy for mechanical properties of marble powder concrete: Model I reached R2 = 0.99 and RMSE = 1.63 on the test set, while Model II achieved R2 = 1.00 and RMSE = 0.21. …”
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Overview of sugarcane harvester virtual design in China by Wang Jun, Hu Jinbing, Wu Jianfeng

“…It mainly conducts further research from the following aspects: Physical characteristics of sugarcane research, combined with the agronomic requirements and the machine battery solution, and the virtual prototype model will be perfected.As the method of the new product development design and the optimization of improvement, the virtual design not only simplifies the design of the complex mechanical system, but also shortens the development cycle of new products, improves the design quality, and reduces the development cost largely. …”
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An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

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Advancements in thermochemical predictions: a multi-output thermodynamics-informed neural network approach by Raheel Hammad, Sownyak Mondal

“…In recent literature, there is a growing emphasis on evaluating machine learning models under challenging conditions, such as small datasets and out-of-distribution predictions. …”
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Speech emotion recognition algorithm of intelligent robot based on ACO-SVM by Xueliang Kang

“…The experimental results showed that the average recognition rate of the multilevel SVM model optimized by genetic algorithm was as high as 81.26 %, which was 8.78 percentage points higher than that before optimization. …”
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