Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
Get full text

Review of Icing Prediction Model and Algorithm for Overhead Transmission Lines Considering Time Cumulative Effects by Chuanqi WANG, Liwen WU, Zhibin DENG, Weifeng DENG, Bin YANG

Get full text

Concentric Circular Antenna Array Synthesis Using Biogeography Based Optimization by Urvinder Singh, Tara Kamal

“…The results obtained by BBO are compared with the Real coded Genetic Algorithm (RGA), Craziness based Particle Swarm Optimization (CRPSO) and Hybrid Evolutionary Programming (HEP). …”
Get full text

A Review of Smart Camera Sensor Placement in Construction by Wei Tian, Hao Li, Hao Zhu, Yongwei Wang, Xianda Liu, Rongzheng Yang, Yujun Xie, Meng Zhang, Jun Zhu, Xiangyu Wang

“…This comprehensive review navigates through the complexities of camera and environment models, advocating for advanced optimization techniques like genetic algorithms, greedy algorithms, Swarm Intelligence, and Markov Chain Monte Carlo to refine CSP strategies. …”
Get full text

Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…Furthermore, by integrating Particle Swarm Optimization (PSO), the algorithm intelligently tunes the pheromone and heuristic factors of ACO, achieving automatic parameter optimization. …”
Get full text

Optimal Scheduling of Multi-energy System Considering Economy and Energy Conservation by Chenxi Wu, Hanxiao Hong, Suoyin Ni, Y. L. Lou

“…SAA is compared with the particle swarm optimization (PSO) algorithm in solving the optimal scheduling strategy. …”
Get full text

Data-Driven Cooperative Localization Algorithm for Deep-Sea Landing Vehicles Under Track Slippage by Zhenzhuo Wei, Wei Guo, Yanjun Lan, Ben Liu, Yu Sun, Sen Gao

Get full text

Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The DDPG optimization method significantly reduced the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) of the WPC, and its optimization effect was significantly better than the GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) methods.…”
Get full text

An Optimization Method for Indoor Pseudolites Anchor Layout Based on MG-MOPSO by Xiaohu Liang, Shuguo Pan, Shitong Du, Baoguo Yu, Shuang Li

“…To address the challenge of optimizing the layout of pseudolite anchor points in complex indoor environments with significant occlusions, this paper proposes a multi-objective particle swarm optimization algorithm (MG-MOPSO). …”
Get full text

Energy Management Strategy Optimization of HEV based on Driving Pattern Recognition by Liu Yonggang, Xie Qingbo, Qin Datong, Lei Zhenzhen

“…The 23 typical driving cycles are chosen from ADVISOR software and five categories are divided by using clustering analysis method,the key parameters of each category are optimized by using particle swarm algorithm,with the goal of reducing fuel consumption,relevant optimized results are saved in database,an energy management strategy optimization method of HEV based on driving pattern recognition is proposed.Finally,the simulation analysis for the energy management is carried out under a comprehensive test cycle,simulation results show that vehicle fuel consumption is cut down 12. 77%,and the deviation of the battery SOC have greatly decrease compare with other energy management strategy which based on driving pattern recognition.…”
Get full text

Research on Multi-Objective Reactive Power Optimization of Distribution Grid with Photovoltaics by Lie Xia, Xiaojin Lin, Rongrong Zhou, Kanjian Zhang

“…Aiming at the two objectives of the network loss and voltage fluctuation rate, the improved multi-objective particle swarm optimization algorithm is used to solve the model under the condition that the output of each device does not exceed the constraint and the optimal solution that can reduce the distribution grid loss and improve the voltage stability of the distribution grid is obtained. …”
Get full text

Optimizing Feature Selection for IOT Intrusion Detection Using RFE and PSO by zahraa mehssen agheeb Alhamdawee

“…Two feature selection mechanisms, which are Particle Swarm Optimization Algorithm (PSO) and Correlation-based Feature Selection Recursive Feature Elimination (RFE) have been used to compare their performances. …”
Get full text

AI-based routing algorithms improve energy efficiency, latency, and data reliability in wireless sensor networks by Rahul Priyadarshi, Ravi Ranjan Kumar, Rakesh Ranjan, Padarti Vijaya Kumar

“…Abstract This paper proposes a modular Artificial Intelligence (AI)-based routing framework for Wireless Sensor Networks (WSNs) that integrates reinforcement learning (RL), supervised learning, and swarm intelligence techniques such as genetic algorithms (GA) and particle swarm optimization (PSO). …”
Get full text

Simultaneous Optimal Allocation of EVCSs and RESs Using an Improved Genetic Method by Majid Farjamipur, Hossein Lotfi, Mohammad Hassan Nikkhah

“…In this research, the improved nondominant sorting genetic algorithm is proposed to solve the problem, and the results of the proposed method are also compared with the conventional genetic and particle swarm optimization algorithms. …”
Get full text

Distributed hybrid energy storage photovoltaic microgrid control based on MPPT algorithm and equilibrium control strategy by Yanlong Qi, Rui Liu, Haisheng Lin, Junchen Zhong, Zhen Chen

“…The novelty of this study is that the improved Grey Wolf optimization algorithm enhances the global search ability by introducing the random jump mechanism of Levy flight algorithm and the combination of particle swarm optimization algorithm and Grey Wolf optimization algorithm to avoid falling into the local optimal. …”
Get full text

Design of an Optimal SMC Controller for a Twin Rotor Aerodynamic System by Marwa Rasheed Ali, Omer Waleed Abdulwahhab

“…To evaluate the performance of the proposed controller, a comparison with a previous study—that used Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA) algorithms—has been conducted. …”
Get full text

Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
Get full text

Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This paper seeks to elucidate the efficacy of deep learning models in medical diagnostics by employing concepts and strategies derived from biological system ontologies, such as genetic algorithms, particle swarm optimization, ant colony optimization, artificial immune systems, and swarm intelligence. …”
Get full text

Optimized planning of electric vehicle charging infrastructure for grid performance improvement by Mohammad Reza Maghami, Ka Fei Thang, Arthur G. O. Mutambara, Ali Akbar Firoozi, Elnaz Yaghoubi, Mehdi Zareian Jahromi, Elaheh Yaghoubi

“…This paper presents a multi-objective optimization framework developed using particle swarm optimization (PSO) algorithm to determine optimal placement and capacity of EV charging infrastructures. …”
Get full text

Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…Based on the new evaluation model, an objective function is constructed to minimize the system’s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
Get full text