Squirrel search algorithm-support vector machine: Assessing civil engineering budgeting course using an SSA-optimized SVM model by He Yanqing, Shi Ling, Yao Xiaoqin, Zhang Haojie, Al-Barakati Abdullah A.

“…The above results reveal that the proposed optimization algorithm and course evaluation model have good performance. …”
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Prediction Model For Students' On-Time Graduation Using Algorithm Support Vector Machine (SVM) Based  Particle Swarm Optimization (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

“…This research aims to create a prediction model for graduating on time using the Support Vector Machine (SVM) method based on Particle Swarm Optimization (PSO) with feature selection. information gain, so that the attributes selected and used are Semester Achievement Index 1, Semester Achievement Index 2, Semester Achievement Index 3, Semester Achievement Index 4, Grade Point Average (GPA) 1, Grade Point Average (GPA) 2, Grade Point Average (GPA) 3, Grade Point Average (GPA) 4, Semester Credit Units 1, and Semester Credit Units 4. …”
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Geostatistics and artificial intelligence coupling: advanced machine learning neural network regressor for experimental variogram modelling using Bayesian optimization by Saâd Soulaimani, Saâd Soulaimani, Ayoub Soulaimani, Kamal Abdelrahman, Abdelhalim Miftah, Mohammed S. Fnais, Biraj Kanti Mondal

“…The improved reliability of the Bayesian-optimized regressor demonstrates its superiority over traditional, non-optimized regressors, indicating that incorporating Bayesian optimization can significantly advance experimental variogram modelling, thus offering a more accurate and intelligent solution, combining geostatistics and artificial intelligence specifically machine learning for experimental variogram modelling.…”
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Optimized Machine Learning-Augmented Hybrid Empirical Models for AlGaN/GaN HEMTs: A Comprehensive Analysis by Ahmad Khusro, Saddam Husain, Mohammad Hashmi

“…This article presents robust hybrid equivalent circuit (EC)–machine learning (ML) frameworks for significantly streamlining the extraction of small-signal model parameters of AlGaN/GaN HEMTs. …”
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Multi-Agent Communication for Dynamic Job-Shop Scheduling: A Robust Single-Machine Scheduling Model With Genetic Algorithm Optimization by Hong-Phuc Nguyen, Quang-Hieu Ngo, van-Can Nguyen

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A machine learning model with crude estimation of property strategy for performance prediction of perovskite solar cells based on process optimization by Dan Li, Ernie Che Mid, Shafriza Nisha Basah, Xiaochun Liu, Jian Tang, Hongyan Cui, Huilong Su, Qianliang Xiao, Shiyin Gong

“…This study establishes a machine learning model incorporating a crude estimation of property (CEP) strategy to enhance prediction accuracy and precisely control process parameters. …”
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A Cloud-Based Optimized Ensemble Model for Risk Prediction of Diabetic Progression—An Azure Machine Learning Perspective by V. K. Daliya, T. K. Ramesh

“…The proposed model uses various optimization techniques, such as 10 fold cross validation, grid search method etc. to get the best results out of the ensemble model. …”
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PREDICTION MODEL FOR STUDENTS' ON-TIME GRADUATION USING ALGORITHM SUPPORT VECTOR MACHINE (SVM) BASED  PARTICLE SWARM OPTIMIZATION (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

“…This research aims to create a prediction model for graduating on time using the Support Vector Machine (SVM) method based on Particle Swarm Optimization (PSO) with feature selection. information gain, so that the attributes selected and used are Semester Achievement Index 1, Semester Achievement Index 2, Semester Achievement Index 3, Semester Achievement Index 4, Grade Point Average (GPA) 1, Grade Point Average (GPA) 2, Grade Point Average (GPA) 3, Grade Point Average (GPA) 4, Semester Credit Units 1, and Semester Credit Units 4. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). …”
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Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers by Firman Aziz, Mutia Maulida, Jafar Jafar, Nurafni Shahnyb, Norma Nasir, Ampauleng Ampauleng

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Determination of disintegration time using formulation data for solid dosage oral formulations via advanced machine learning integrated optimizer models by Mohammed Ghazwani, Umme Hani

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Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines by Emmanuel Ahishakiye, Fredrick Kanobe

“…These algorithms are (1) an optimized support vector machine (SVM), and (2) a deep Gaussian Process (DGP) model. …”
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Advanced Machine Learning Techniques for Energy Consumption Analysis and Optimization at UBC Campus: Correlations with Meteorological Variables by Amir Shahcheraghian, Adrian Ilinca

“…This study is presented as a solution to these challenges through a detailed analysis of energy consumption across UBC Campus buildings using a variety of machine learning models, including Neural Networks, Decision Trees, Random Forests, Gradient Boosting, AdaBoost, Linear Regression, Ridge Regression, Lasso Regression, Support Vector Regression, and K-Neighbors. …”
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System-Level Optimization in Switched Reluctance Machine Design—Current Trends, Methodologies, and Future Directions by Aristotelis Tzouvaras, Georgios Falekas, Athanasios Karlis

Subjects: “…system-level design optimization…”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

Subjects: “…Machine learning…”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

Subjects: “…machine learning…”
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Behavior Modeling-Based QoS Preserving Model With Intelligent Trust Ranking for 6G by Santosh Sharma, Rakesh Kumar Jha, Anil Kumar

“…The suggested SVM (Support Vector Machine) based prediction model preserves the three-way trade-off between QoS, accuracy, and processing time. …”
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Survey of research on application of heuristic algorithm in machine learning by Yanping SHEN, Kangfeng ZHENG, Chunhua WU, Yixian YANG

“…Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.…”
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Comparative analysis and application of rockburst prediction model based on secretary bird optimization algorithm by Tengjie Yang, Tengjie Yang, Xinqiang Gao, Xinqiang Gao, Lichuan Wang, Yongqing Xue, Haobo Fan, Zhengguo Zhu, Zhengguo Zhu, Jingbo Zhao, Beiyi Dong, Beiyi Dong

“…Five rockburst prediction models [support vector machine (SVM), least-squares support vector machine (LSSVM), kernel extreme learning machine (KELM), Random Forest (RF), and XGBoost] were established by employing the Secretary Bird Optimization (SBO) algorithm and 5-fold cross-validation to optimize performance. …”
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Brown bear optimized random forest model for short term solar power forecasting by Rathika Senthil Kumar, P.S. Meera, V. Lavanya, S. Hemamalini

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