Grid-Integrated Dual Wind Turbine System Using SEPIC Converter with Whale Optimized PI Controller by Kishore R.D., Sravani K., Sai Kumar N.D., Preetham C.G., Bentu B.2

“…In order to achieve the set goals, the following tasks were accomplished: integration of a Pulse Width Modulation (PWM) rectifier for AC to DC conversion, implementation of a SEPIC converter for voltage boosting, tuning of proportional integral (PI) controller parameters using whale optimization algorithm (WOA) for dynamic DC voltage regulation, and design of a 3Φ Voltage Source Inverter (VSI) for efficient management of active and reactive power to the grid. …”
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Intelligent Wireless Charging Path Optimization for Critical Nodes in Internet of Things-Integrated Renewable Sensor Networks by Nelofar Aslam, Hongyu Wang, Muhammad Farhan Aslam, Muhammad Aamir, Muhammad Usman Hadi

“…Our findings indicate that the outage-optimal distance achieved by WPCD-ACO is 6092 m, compared to 7225 m for the shortest path and 6142 m for Dijkstra’s algorithm. …”
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Stackelberg Game Optimization Strategy of Virtual Power Plants and Electric Vehicles Based on Conditional Value-at-Risk by MA Qianxin, JIA Heping, GUO Yuchen, LI Peijun, YANG Ye, LIU Dunnan, ZHAO Zhenyu

“…The lower-level model minimized user costs by responding to these prices using a utility function that captures both cost satisfaction and charging experience. A particle swarm optimization algorithm was employed to solve the coupled model and identify the equilibrium strategies.…”
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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…Response surface methodology (RSM) is used for predictive modeling, while enhanced hill climbing (EHC), non-dominated sorting genetic algorithm II (NSGA-II), and the multi-objective generalized normal distribution optimizer (MOGNDO) are applied for multi-objective optimization. …”
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Evaluating end-to-end autonomous driving architectures: a proximal policy optimization approach in simulated environments by Ângelo Morgado, Kaoru Ota, Mianxiong Dong, Nuno Pombo

“…The study uses the Proximal Policy Optimization (PPO) algorithm within the CARLA simulation environment. …”
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Optimal Economic Dispatch Strategy for Cascade Hydropower Stations Considering Electric Energy and Peak Regulation Markets by Fan Liu, Wentao Huang, Jingjing Ma, Jun He, Can Lv, Yukun Yang

“…Specifically, firstly, the strategy adopts multi-objective optimization. The objective function takes into account the generation capacity of the cascade hydropower stations, the benefits of the EEM, the influence of the spot market, the compensatory benefits of peaking, and the sharing expenses of peaking; secondly, the constraints at the level of the power grid, the level of the cascade hydropower stations, and the level of the market are taken into account comprehensively, and the Harris Hawk Algorithm is used to solve the model; lastly, by comparing different schemes, it is observed that under varying inflow conditions, the proposed dispatch strategy in this paper yields slightly lower revenue in the EEM than other schemes. …”
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Optimal scheduling of district heat pumps conceived for implementation in Energy Management Systems to participate in demand response by Roberto Rocca, Stefano Leonori, Gregorio Fernández Aznar, Riccardo Toffanin, Luis Luengo-Baranguan

“…To this end, this work proposes a novel formulation of the optimal scheduling problem of district-level HPs, conceived for EMS implementation, and based on a quadratic programming algorithm, with a specific objective function for IDR and DDR. …”
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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

“…Finally, with torque ripple, cogging torque, and output torque as optimization objectives, the particle swarm optimization algorithm was used to perform multi-objective optimization on the maximum magnetic pole thickness, minimum magnetic pole thickness, the width of magnetic pole, the depth and width of the rotor auxiliary slots, in order to determine the optimal parameters, and a prototype was then developed for experimental testing. …”
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Research and Optimization of White Blood Cell Classification Methods Based on Deep Learning and Fourier Ptychographic Microscopy by Mingjing Li, Junshuai Wang, Shu Fang, Le Yang, Xinyang Liu, Haijiao Yun, Xiaoli Wang, Qingyu Du, Ziqing Han

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Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis by Govindharaj I, Ramesh T, Poongodai A, Senthilkumar K. P, Udayasankaran P, Ravichandran S

“…A hybrid segmentation method combines Grey Wolf Optimization Algorithm with U-Shaped Networks to obtain precise extraction of the optic disc regions in retinal fundus images. …”
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Integrated GBR–NSGA-II Optimization Framework for Sustainable Utilization of Steel Slag in Road Base Layers by Merve Akbas

“…Subsequently, the Gradient Boosted Regressor model was integrated into a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) framework to explore optimal trade-offs between cost and emissions. …”
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Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…This study addresses these challenges by proposing FLSTMT-LAR (Federated Learning Long Short-Term Memory Trust-aware Location-aided Routing), a novel framework that integrates multiobjective optimization with LSTM-based trust prediction for robust routing decisions, implements a decentralized federated learning mechanism for collaborative trust model updates while preserving node privacy, incorporates dynamic trust assessment using LSTM networks for accurate temporal behavior pattern analysis, and provides an adaptive routing decision mechanism that effectively balances multiple performance objectives including trustworthiness, energy efficiency, and network latency. …”
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Improving energy efficiency and routing reliability in wireless sensor networks using modified ant colony optimization by Medhat A. Tawfeek, Ibrahim Alrashdi, Madallah Alruwaili, Leila Jamel, Gamal Farouk Elhady, Haitham Elwahsh

“…In this study, we introduce a Modified Ant Colony Optimization Algorithm (MACOA) to address these challenges. …”
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Using Surrogate Models in the Construction of a Pareto-Optimal Positioning Electropneumatic Actuator with Discrete Pneumatic Valves by M. O. Sheykin, S. N. Cherkasskikh, D. V. Shilin, V. V. Fedenkov

“…Using classical methods for constructing a Pareto set for multicriteria optimization requires significant computational resources, which complicates their practical application.The research objective is to develop a methodology for multicriteria optimization of the parameters of a positioning electropneumatic actuator with discrete distributors based on the construction of a Pareto set using surrogate models, which provides finding the optimal balance between switching frequency and positioning accuracy.Materials and Methods. …”
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Frequency regulation reserve optimization of wind-PV-storage power station considering online regulation contribution by Changping Sun, Xiaodi Zhang, Wei Zhang, Jiahao Liu, Zubing Zou, Leying Li, Cheng Wang

“…This method helps in overcoming the capacity-based reserve static setting. Finally, an optimization model was developed, along with the proposal of the linearized solving algorithm. …”
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Integrated optimization and coordination of cascaded reservoir operations: Balancing flood control, sediment transport and ecosystem service by Xinmiao Cao, Teng Lin, Jiahui Li, Ting Zhou

“…To address the optimization model, an elite mutation‐based multi‐objective particle swarm optimization (MOPSO) algorithm that integrates genetic algorithms (GA) is developed. …”
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Efficient optimal power flow learning: A deep reinforcement learning with physics-driven critic model by Ahmed Sayed, Khaled Al Jaafari, Xian Zhang, Hatem Zeineldin, Ahmed Al-Durra, Guibin Wang, Ehab Elsaadany

“…Deep reinforcement learning (DRL) has emerged as a powerful tool for optimizing power system operations. However, most existing DRL approaches rely on approximated data-driven critic networks, requiring numerous risky interactions to explore the environment and often facing estimation errors. …”
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Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India by Imran Khan, Sarwar Nizam, Apoorva Bamal, Abdul Majed Sajib, Mir Talas Mahammad Diganta, Mohd Azfar Shaida, S.M. Ashekuzzaman, Stephen Nash, Agnieszka I. Olbert, Md Galal Uddin

“…Ensuring access to safe, affordable drinking water while implementing sustainable management practices is vital for achieving the United Nations Sustainable Development Goals-2030. …”
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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. …”
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