Multi-objective operation optimization method of microgrid considering the influence of electric vehicle by Tiefeng Xu, Xiaofang Meng, Fangfang Zheng, Yiduo Zhang, Xin Wu, Mingyang Li

“…Taking the minimum total operating cost and the minimum peak-valley difference of the microgrid in one day as the optimization objective, and considering many constraints such as power balance constraints and output constraints of distributed generation units, the multi-objective optimization function is transformed into a single-objective optimization function by linear weighting method, and the model is solved by particle swarm optimization algorithm. …”
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Optimizing mRNA Vaccine Degradation Prediction via Penalized Dropout Approaches by Hwai Ing Soon, Azian Azamimi Abdullah, Hiromitsu Nishizaki, Latifah Munirah Kamarudin

“…A novel tetramer-label encoding approach (4-mer-lbA) was proposed, integrating biological relevance with data-driven analysis to enhance predictive accuracy. To further optimize model performance, two advanced hyperparameter optimization (HPO) techniques—Dropout-Enhanced Technique (DEet) and Hyperparameter Optimization Algorithm Penalizer (HOPeR)—are proposed to mitigate overfitting, address inefficiencies in conventional HPO algorithms (HPOAs), and accelerate model convergence. …”
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Aerodynamic analysis and ANN-based optimization of NACA airfoils for enhanced UAV performance by Sanan H. Khan, Mohd Danish, Md. Ayaz, Afsar Husain, Shamma Saeed, Shamma Abdulla, Shama Shaheen, Alia Saeed, Ahmed Thaher

“…This study analyzed three National Advisory Committee for Aeronautics (NACA) airfoil profiles: NACA 2412, NACA 4415, and NACA 0012, using a combination of computational fluid dynamics (CFD), XFOIL simulations, and a hybrid artificial neural network-genetic algorithm (ANN-GA) model. This study aimed to evaluate and optimize the aerodynamic performance of these airfoils under various flight conditions. …”
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Resolving Contrast and Detail Trade-Offs in Image Processing with Multi-Objective Optimization by Daniel Molina-Pérez, Alam Gabriel Rojas-López

“…This trade-off is tackled using a multi-objective optimization approach. Specifically, the proposal’s model integrates the sigmoid transformation function and unsharp masking highboost filtering with the NSGA-II algorithm. …”
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Collision-inducing method for UAV evasive maneuvers based on receding horizon optimization by Haonan Tang, Zhigong Tang, Gong Chen, Jifeng Guo

“…The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle, while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method. …”
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Study on the Evolutionary Characteristics of Spatial and Temporal Patterns and Decoupling Effect of Urban Carbon Emissions in the Yangtze River Delta Region Based on Neural Network... by Xichun Luo, Chaoming Cai, Honghao Zhao

“…To improve the performance of neural network models, the Aquila Optimizer (AO) algorithm is introduced to optimize the hyper-parameter values in the back-propagation (BP) neural network model in this research due to the appealing searching capability of AO over traditional algorithms. …”
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Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI by Priyadharshini Babu, Mythili Asaithambi, Sudhakar Mogappair Suriyakumar

“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Businesses across industries face challenges in improving customer retention and reducing churn, making predictive models essential for identifying at-risk customers and enhancing revenue. …”
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Optimal scheduling of BIES with multi-energy flow coupling based on deep RL by XIA Xuhua, YANG Jiandi, SHI Yongtao

“…Secondly， the state space， action space， and reward function for the operational dispatch strategy are designed using deep RL， and a low-carbon economic and optimal dispatch framework is constructed using the ​soft actor-critic （SAC） algorithm.​ …”
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Hybrid Gradient Descent Grey Wolf Optimizer for Machine Learning Performance Enhancement by Sri Rossa Aisyah Puteri Baharie, Sugiyarto Surono, Aris Thobirin

“…Advancements in machine learning have enabled the development of more accurate and efficient health prediction models. This study aims to improve diabetes prediction performance using the Support Vector Machine (SVM) model optimized with the Hybrid Gradient Descent Gray Wolf Optimizer (HGD-GWO) method. …”
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Parking Demand Prediction Method of Urban Commercial-Office Complex Buildings Based on the MRA-BAS-BP Algorithm by Xiang Tang, Jianxiao Ma, Shun Zhou, Tianci Shan

“…In this paper, a two-level and ten-category index system is established and then mixed with the BP algorithm through the MRA model to improve the overall robustness and accuracy of the algorithm. …”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…To address these challenges, this study proposes a deep reinforcement learning-based control scheme, leveraging DRL’s capabilities to optimize system performance. Specifically, the TD3 algorithm, featuring a dual-critic structure, is employed to enhance control precision within predefined state and action spaces. …”
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Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot by Ruijie Wu

“…Therefore, this paper aimed to design an intelligent logistics management system based on ROS robot and proposed to use the A-star algorithm to calculate the shortest path of the robot so as to achieve the optimal path. …”
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Medium and short-term load forecasting based on NPMA-LSSVM algorithm in the case of unbalance and minority sample data by YANG Qiuyu, KUANG Shusen, ZHENG Xiaogang, YE Guoqi, ZHANG Zhongxin

“…Finally, the least square support vector machine (LSSVM) load forecasting model is established, and the improved mayfly algorithm with nonlinear inertia factor and polynomial variation is used to optimize the model parameters to achieve accurate load forecasts. …”
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A Novel Hybrid Metaheuristic MPA-PSO to Optimize the Properties of Viscous Dampers by Elmira Shemshaki, Mohammad Hasan Haddad, Mohammadreza Mashayekhi, Seyyed Meisam Aghajanzadeh, Ali Majdi, Ehsan Noroozinejad Farsangi

“…Structural modeling and dynamic analyses are performed using OpenSees 3.5.0 software, and damper parameter optimization is performed through a new combination of two marine predator algorithms (MPA) and particle swarm optimization (PSO). …”
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Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data by Niko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak

“…The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. …”
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Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries by Harish Venu, Manzoore Elahi M. Soudagar, Tiong Sieh Kiong, N. M. Razali, Hua-Rong Wei, Armin Rajabi, V. Dhana Raju, T. M. Yunus Khan, Naif Almakayeel, Erdem Cuce, Huseyin Seker

“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
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A hybrid PKI and spiking neural network approach for enhancing security and energy efficiency in IoMT-based healthcare 5.0 by Dipalee D․Rane Chaudhari, Manisha S. Bhende, Aadam Quraishi, Azzah AlGhamdi, Ismail Keshta, Mukesh Soni, Brajesh Kumar Singh, Haewon Byeon, Mohammad Shabaz

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EFFICACY OF OPTIMIZED REMINERALIZING THERAPY IN POST-COVID-19 PATIENTS: EVALUATION OF RESULTS by N.M. Savielieva, M.E. Diasamidze

“…To correct the identified disorders and prevent the occurrence and development of carious lesions, we applied an improved algorithm of prophylaxis of dental enamel diseases using remineralizing therapy. …”
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Extraction of Optimal Measurements for Drowsy Driving Detection considering Driver Fingerprinting Differences by Yifan Sun, Chaozhong Wu, Hui Zhang, Yijun Zhang, Shaopeng Li, Hongxia Feng

“…Finally, we selected measurements calculated by IDBCPs that can distinguish drowsy driving to constitute individual drivers’ optimal drowsiness-detection measurement set. To verify the advantages of IDBCPs, the measurements calculated by UCPs and IDBCPs were, respectively, used to build driver-specific drowsiness-detection models: DF_U and DF_I based on the Fisher discriminant algorithm. …”
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