MSCSO: A Modified Sand Cat Swarm Algorithm for 3D UAV Path Planning in Complex Environments with Multiple Threats by Zhengsheng Zhan, Dangyue Lai, Canjian Huang, Zhixiang Zhang, Yongle Deng, Jian Yang

“…To improve the global search efficiency and dynamic adaptability of the Sand Cat Swarm Optimization (SCSO) algorithm for UAV path planning in complex 3D environments, this study proposes a Modified Sand Cat Swarm Optimization (MSCSO) algorithm by integrating chaotic mapping initialization, Lévy flight–Metropolis hybrid exploration mechanisms, simulated annealing–particle swarm hybrid exploitation strategies, and elite mutation techniques. …”
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Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses by da Pan

“…Experimental results demonstrate that SA achieves superior performance compared to genetic algorithms (GA), greedy approaches, ant colony optimization (ACO), and particle swarm optimization (PSO). …”
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Assessing generalizability of Deep Reinforcement Learning algorithms for Automated Vulnerability Assessment and Penetration Testing by Andrea Venturi, Mauro Andreolini, Mirco Marchetti, Michele Colajanni

“…To this purpose, we define a novel VAPT environment through which we devise multiple evaluation scenarios. While evidencing the limited capabilities of shallow RL approaches, we consider three state-of-the-art deep RL agents, namely Deep Q-Network (DQN), Proximal Policy Optimization (PPO), and Advantage Actor–Critic (A2C), and use them as bases for VAPT operations. …”
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A Vehicle Path Planning Algorithm Based on Mixed Policy Gradient Actor-Critic Model with Random Escape Term and Filter Optimization by Wei Nai, Zan Yang, Daxuan Lin, Dan Li, Yidan Xing

“…In addition, filter optimization has been innovatively introduced in this paper, and the step size of each iteration of the model is selected through the filter optimization algorithm to achieve the better iterative effect. …”
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Vehicle scheduling optimization for demand responsive transit with flexible stops by SHEN Zikang, JIN Wenzhou, ZHENG Yajing

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Sensor Field Segmentation and Parameter Optimization for Electrical Capacitance Tomography System by ZHANG Jin-rong, WANG Li-li, YANG Bo-Tao, LIU Xiao

“…From the comparative analysis of the experimental results，the accuracy of the reconstructed image of the sensor designed by orthogonal experiment is higher than that of the reference sensor，while the imagingeffect of the sensor optimized by ＲBF neural network and chaotic simulated annealing particle swarm optimization algorithm is better than the orthogonal experimental design. …”
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Geospatial parametric approach for identifying optimal sites for wind-solar hybrid energy systems by Nyange Augustine Mbufua, Pascalin Tiam Kapen, François Ngapgue, Armand Nzeukou Takougang

“…However, it requires a careful and optimized selection of the installation site to fully harness the available energy resources. …”
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A Design-Oriented Model for Transmission Loss Optimization in Marine DOCs by Jan Kašpar, Francesco Mauro, Marco Biot, Giovanni Rognoni, Giada Kyaw Oo D’Amore

“…This study aims to develop an ad hoc optimization methodology that uses combined Computational Fluid Dynamics (CFD)–Finite Element Method (FEM) simulations, surrogate models, and Genetic Algorithms to optimize the acoustic properties of EGCSs while considering the limits imposed by the efficiency of chemical reactions for the abatement of NO_x and SO_x. …”
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Evolutionary Topological Optimization Method for Local Rib Addition in Single-Layer Shell Structures by WANG Rungu, DONG Xiao, GONG Jinghai

“…Using steel consumption as the evaluation index, a topological optimization method based on the evolutionary structural optimization algorithm is proposed for single-layer reticulated shell structures. …”
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Hidden-layer configurations in reinforcement learning models for stock portfolio optimization by Patrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik Faturohman

“…These findings suggest that the effectiveness of hidden-layer configurations depends on the specific algorithm used. While A2C and DDPG benefit from increased complexity, simpler architectures may be more suitable for PPO and TD3. …”
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Unveiling the optimal factor model in Pakistan: a machine learning approach using support vector regression and extreme gradient boosting algorithms by Rizwan Ullah, Muhammad Naveed Jan, Muhammad Tahir

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Research on the connectivity reliability analysis and optimization of natural gas pipeline network based on topology by Xiuxuan Yang, Kun Chen, Minghui Liu

“…Second, an adaptive genetic algorithm (AGA) is designed to optimize network topology, dynamically adjusting crossover and mutation rates (0.8≤ $$\:{p}_{c}$$ ≤0.01, 0.01≤ $$\:{p}_{m}$$ ≤ 0.8) based on population diversity, while enforcing constraints through penalty functions (node degree $$\:{k}_{max}$$ =4, pipeline length $$\:{l}_{max}$$ =120 km). …”
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Advanced control and optimization techniques for DFIG wind energy systems: A case study using pelican algorithm and CTID-PID controller by P. V. S. S. A. Parimala, Narendra Babu P

“…The RSC is controlled using the pelican optimization technique, a nature-inspired algorithm that effectively tunes control parameters to achieve optimal dynamic response and minimize power losses, enabling maximum wind power capture while maintaining stability. …”
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Engine performance and emission optimization with waste cooking oil biodiesel/diesel blend using ANN and RSM techniques coupled with ACKTR-DE and HHO algorithms by Mehmet Ali Biberci, Mustafa Bahattin Çelik, Esma Ozhuner

“…By applying the developed model, the brake thermal efficiency (BTE) response was optimized to its maximum value, while all other responses were minimized. …”
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UAVRM-A*: A Complex Network and 3D Radio Map-Based Algorithm for Optimizing Cellular-Connected UAV Path Planning by Yanming Chai, Yapeng Wang, Xu Yang, Sio-Kei Im, Qibin He

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An Enhanced NSGA-II Algorithm with Parameter Categorization for Computational-Efficient Multi-Objective Optimization of Active Glass Curtain Wall Shading Systems by Dezhao Tang, Zhiyong Wang

“…To address the limitations of the Non-Dominated Sorting Genetic Algorithm (NSGA-II) in optimizing active glass curtain wall shading systems—particularly its suboptimal convergence efficiency and high computational demands—this study proposes an improved NSGA-II algorithm incorporating parameter categorization. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…The effectiveness of the compact network is increased by using the Flexible Coyote Optimization Algorithm (FCOA), which plays a vital role in optimizing parameters and accelerating convergence. …”
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Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…To address this issue, this study fully exploits the fast response and flexible operation of variable-speed pumped storage (VS-PS) by developing a day-ahead scheduling model for a wind–photovoltaic–thermal–VS-PS system. The optimization model aims to minimize system operating costs, carbon emissions, and thermal power output fluctuations, while maximizing the regulation flexibility of the VS-PS plant. …”
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Implementation of real-time optimal load scheduling for IoT-based intelligent smart energy management system using new decisive algorithm by Challa Krishna Rao, Sarat Kumar Sahoo, Franco Fernando Yanine

“…Abstract This paper presents the implementation of a real-time optimal load scheduling system for an IoT-based intelligent smart energy management system (SEMS) using a novel decisive algorithm. …”
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GA-Attention-Fuzzy-Stock-Net: An optimized neuro-fuzzy system for stock market price prediction with genetic algorithm and attention mechanism by Burak Gülmez

“…The model's performance is evaluated across multiple temporal horizons using sliding windows (5-day, 10-day, 20-day) to capture varying market dynamics. Genetic algorithms optimize the hyperparameters, including learning rates and network architectures, while the attention mechanism enhances the model's ability to focus on relevant temporal patterns. …”
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