GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…The high penetration of renewables into the active distribution network (ADN) brings voltage deviation and difficulties to the optimal power flow (OPF) problem. The optimal operation of the distribution grid aims to efficiently manage the flow of electricity from sources to end-users, ensuring a resilient and sustainable grid. …”
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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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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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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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Pseudorandom Function from Learning Burnside Problem by Dhiraj K. Pandey, Antonio R. Nicolosi

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A Study on an Anti-Multiple Periodic Frequency Modulation (PFM) Interference Algorithm in Single-Antenna Low-Earth-Orbit Signal-of-Opportunity Positioning Systems by Lihao Yao, Honglei Qin, Hao Xu, Deyong Xian, Donghan He, Boyun Gu, Hai Sha, Yunchao Zou, Huichao Zhou, Nan Xu, Jiemin Shen, Zhijun Liu, Feiqiang Chen, Chunjiang Ma, Xiaoli Fang

“…This paper proposes a Signal Adaptive Iterative Optimization Resampling (SAIOR) algorithm, which leverages the periodicity of PFM jamming signals and the characteristics of LEO constellation signals. …”
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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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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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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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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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Distribution Generation Network Arrangement by Capacitor Placement and Sizing in Renewable Energy Sources with Uncertainties Based on Self-adaption Kho-Kho Optimizer by Lu Xingxing

“…Post-optimization results indicated a reduction in power loss costs from 4.11 × 10^5 to 1.05 × 10^5 units, representing a 25.54% decrease. …”
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Dynamic Gesture Recognition and Interaction of Monocular Camera Based on Deep Learning by SUNBo wen, YU Feng

“…Through convolution and fullconnected network structure, as well as optimization of parameter selection and prevention of overfitting, combined with fingertip detection and elimination algorithm, the recognition accuracy is improved. …”
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Does mean arterial pressure augmentation improve neurological recovery of blunt spinal cord injuries: an EAST multicenter trial by Jeffry Nahmias, Ryan Peter Dumas, Brian Daley, Dalier R Mederos, Bradley M Dennis, Michael Steven Farrell, Stephanie Scott, Gregory Schaefer, Asanthi Ratnasekera, Alison Smith, Scott Armen, Joshua Hill, Carlos H Palacio, Caitlin Anne Fitzgerald, Stephanie Doris, Claudia Alvarez, John D Berne, Lindsey Perea, Aimee LaRiccia, James Bardes, Bhairav Shah, Tanisha Kashikar, Erik Teicher, Jennifer Huber, Malia Eischen, H Akin Erol, Lauren Colom, Melissa Moncrief, William DeVoe, William Brigode, Melissa Linskey Dougherty, Emily Alberto, Stephen Gadomski, Salina Wydo, Jennifer Schweinsburg, M Chance Spalding

“…Patients were divided into two groups: neurological improvement and no improvement, based on their change in ASIA score from arrival to hospital discharge.Results A total of 19 centers contributed 222 patients of those, 164 had pre-ASIA and post-ASIA scores. …”
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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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Calculation method of line loss rate of substation areas considering tidal current variation with photovoltaic power generation access by Shengbo Sun, Chao Cheng, Shujun Ji, Wei Cui, Wei Ge, Shifang Hao

“…The proposed method employs an improved K-medoids clustering algorithm for substation area classification, optimized by an enhanced Cuckoo algorithm to minimize classification errors. …”
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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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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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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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