Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…HTOA, inspired by the physical phenomenon of heat transfer, identifies an optimal subset of topological features to feed XGBoost machine learning model. …”
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Book Recommendation Using Collaborative Filtering Algorithm by Esmael Ahmed, Adane Letta

“…Moreover, using hyperparameter tuning with SVD also has an improvement on model performance compared with the existing SVD algorithm.…”
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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

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
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Steganographic model to conceal the secret data in audio files utilizing a fourfold paradigm: Interpolation, multi-layering, optimized sample space, and smoothing by Daffa Tristan Firdaus, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Didacienne Mukanyiligira, Louis Sibomana

“…To address these limitations, this study offers valuable insights to guide researchers in developing high-performing audio steganography models. The proposed method seeks to improve stego audio quality by implementing a smoothing-based technique and optimizing the sample space through linear interpolation, followed by a multi-layering process. …”
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An efficient patient’s response predicting system using multi-scale dilated ensemble network framework with optimization strategy by Nalini Manogaran, Nirupama Panabakam, Durai Selvaraj, Koteeswaran Seerangan, Firoz Khan, Shitharth Selvarajan

“…The Repeated Exploration and Exploitation-based Coati Optimization Algorithm (REE-COA) is employed to select the features. …”
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QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

“…In this paper, a new approach for improvement of DNA computing is proposed. This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). …”
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Comparison of clustering methods and conventional approaches for geological fracture analysis: A case study in northern Shiraz, Iran by HAJAR KAZEMI, KOUROS YAZDJERDI, ABDOLMAJID ASADI, MOHAMMAD REZA MOZAFARI

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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

“…By leveraging data from 88 stopes at Guangxi Tongkeng Mine over a decade, we constructed a comprehensive dataset encompassing drilling, charging, blasting, ventilation, support, ore drawing, and maintenance. The XGBoost algorithm was employed to model factors influencing stope production capacity (PC), with its parameters optimized using the Marine Predator Algorithm (MPA). …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…First, preprocessed industrial operation data are fed into the model, and hyperparameter optimization is conducted using the Optuna framework to improve training efficiency and generalization capability. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

“…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…After selecting the best features, these were used to train the three ML algorithms, and hyper-parameter optimization was implemented to boost model performance. …”
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The Application of Artificial Intelligent Algorithms in Electric Propulsion by Tian Bin, An Bingchen, Xie Kan, Yang Sulan

“…These algorithms can not only train models based on data to optimize the performance of electric thrusters, but also analyze and solve the mathematical and physical models of plasmas within electric thrusters. …”
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Advanced hybrid computational analysis of febuxostat solubility using machine learning in supercritical processing method by Turki Al Hagbani, Rami M. Alzhrani, Majed Ahmed Algarni

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An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

“…The XGBoost algorithm was then used to optimize the feature parameters and improve the classification model. …”
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Matching heterogeneous ontologies with adaptive evolutionary algorithm by Xingsi Xue, Haolin Wang, Xin Zhou, Guojun Mao, Hai Zhu

“…Ontology matching technique uses the similarity measure to determine the correspondences between two heterogeneous ontology entities. In order to improve the quality of ontology alignment, it is necessary to combine different kinds of similarity measures, and how to optimize the aggregating weights is called the ontology meta-matching problem. …”
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Optimization of Low-Loss, High-Birefringence, Single-Layer, Annular, Hollow, Anti-Resonant Fiber Using a Surrogate Model-Assisted Gradient Descent Method by Lihong Zhai, Sijie Zhang, Jiyang Luo, Gang Huang, Zihan Liu

“…This paper proposes a novel optimization method for hollow-core, anti-resonant fiber based on a gradient descent algorithm assisted via a radial basis-function surrogate model. …”
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CRIMINALISTIC CHARACTERISTICS OF CRIMES RELATED TO ILLEGAL ACCESS TO COMPUTER INFORMATION by KHARISOVA Zarina Irekovna

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Modeling 5G-NR User Blocking Probability in Conditional Handover-Enabled Heterogeneous Networks by Amiraslan Haghrah, Javad Musevi Niya, Jafar Pourrostam

“…To demonstrate the practical applicability of the proposed model, we present a case study involving a multi-objective optimization problem solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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