Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Numerical Modeling on the Damage Behavior of Concrete Subjected to Abrasive Waterjet Cutting by Xueqin Hu, Chao Chen, Gang Wang, Jenisha Singh

“…In this study, a numerical framework based on a coupled Smoothed Particle Hydrodynamics (SPH)–Finite Element Method (FEM) algorithm incorporating the Riedel–Hiermaier–Thoma (RHT) constitutive model is proposed to investigate the damage mechanism of concrete subjected to abrasive waterjet. …”
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Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

“…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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Allocation of Interline Power Flow Controller-Based Congestion Management in Deregulated Power System by Muhammad Safdar Sial, Qinghua Fu, Talles Vianna Brugni

“…Therefore, an objective function is defined, including the stated parameter, minimizing the generation cost, congestion costs, power losses, and improving the voltage profile. Using the upgraded SWSO algorithm, a new approach to the optimal location of IPFC is presented. …”
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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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Achieving local differential location privacy protection in 3D space via Hilbert encoding and optimized random response by Yan Yan, Pengbin Yan, Adnan Mahmood, Yang Zhang, Quan Z. Sheng

“…Experiments on the real spatial location datasets show that the suggested method can reduce spatial location service quality loss, maintain the availability of perturbed spatial location and improve the operation efficiency of the spatial location perturbation algorithm.…”
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Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…At last, an adaptive recommendation of the engineering department is performed using DRNN, which is trained based on the Magnetic Invasive Weed Optimization (MIWO) algorithm. On the other hand, MBTI personality type categorization is done, wherein the correlation of courses with MBTI outcome is detected using MIWO-based DRNN. …”
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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…This efficient strategy consists of the inherent complexities, which is solved by the NSGA-II algorithm. The multi-objective approach of optimization procedure performs Pareto solution sets that reflects trade-offs between remaining load variations and operational costs. …”
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Machine Learning-Driven Optimization of Transport Layers in MAPbI₃ Perovskite Solar Cells for Enhanced Performance by Velpuri Leela Devi, Piyush Kuchhal, Debasis de, Abhinav Sharma, Neeraj Kumar Shukla, Mona Aggarwal

“…This research highlights the critical importance of precise material and structural optimization to improve PSC performance. The integration of ML with traditional simulation techniques provides a robust foundation for PSC research, supporting further experimental validation and potential large-scale applications, ultimately advancing more efficient and durable photovoltaic technologies.…”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Following feature extraction, the GWO algorithm, inspired by the social hierarchy and hunting behavior of grey wolves, is employed to optimize the feature set by selecting the most relevant features. …”
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A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

“…Compared with the traditional CAT methods, our approach gives better ability estimates and selects test items that are most appropriate for each student. The findings of the study show that the efficiency, accuracy and fairness of the tests have improved through experimentation.…”
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Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems by J. A. Montañez-Barrera, Kristel Michielsen

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $${\{{\gamma }_{i},{\beta }_{i}\}}_{i = 0}^{p-1}$$ { γ i , β i } i = 0 p − 1 . …”
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Enhancing grid connected wind energy conversion systems through fuzzy logic control optimization with PSO and GA techniques by Abdelhalim Borni, Noureddine Bessous, Layachi Zaghba, Abdelhak Bouchakour, Melkamu Sisay Agmas, Enas Ali, Sherif S. M. Ghoneim, Ayman Hoballah

“…Abstract This paper presents the design and simulation of an optimized fuzzy logic Maximum Power Point Tracking (MPPT) controller for grid-tied wind turbines, utilizing Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms by Rafael Pires de Lima, Yue Chen, Youzuo Lin

“…Furthermore, based on several kinds of linear and artificial neural networks algorithms, a list of models was constructed, trained, validated, and tested with 42‐month MeV electron observations from Van Allen Probes. …”
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Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions by Nivine Guler, Zied Ben Hazem, Ali Gunes, Firas Saidi

“…An inherent problem with most conventional global maximum power point tracking (GMPPT) algorithms is that they do not distinguish local and global peaks, and thus energy extraction may not be optimal. …”
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Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

“…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…Notably, the Thermal Exchange Optimization (TEO) algorithm resulted in the most significant improvement, increasing the accuracy of the original SVM model by 10% and exceeding the standard by 4.3%. …”
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Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. The optimized hybrid model exhibited a remarkable improvement, with an Acc. of 99.7%, Sen. of 99.7%, Spec. of 99.91%, Prec. of 99.98%, and F1-score of 99.98%, alongside significant improvements in other metrics. …”
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Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…These results indicate that MMDBO consistently outperforms most algorithms and provides accurate and reliable optimizer solutions. …”
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Method for EEG signal recognition based on multi-domain feature fusion and optimization of multi-kernel extreme learning machine by Shan Guan, Tingrui Dong, Long-kun Cong

“…Abstract In response to the current issues of one-sided effective feature extraction and low classification accuracy in multi-class motor imagery recognition, this study proposes an Electroencephalogram (EEG) signal recognition method based on multi-domain feature fusion and optimized multi-kernel extreme learning machine. Firstly, the EEG signals are preprocessed using the Improved Comprehensive Ensemble Empirical Mode Decomposition (ICEEMD) algorithm combined with the Pearson correlation coefficient to eliminate noise and interference. …”
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