Hybrid Feature-Based Disease Detection in Plant Leaf Using Convolutional Neural Network, Bayesian Optimized SVM, and Random Forest Classifier by Ashutosh Kumar Singh, SVN Sreenivasu, U.S.B. K. Mahalaxmi, Himanshu Sharma, Dinesh D. Patil, Evans Asenso

“…Binary particle swarm optimization plays a crucial role in hybrid feature selection; the purpose of this Algorithm is to obtain the suitable output with the least features. …”
Get full text

Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

“…Furthermore, an angle preference-based multi-objective particle swarm optimization algorithm is introduced to incorporate the preferences of decision-makers and yield flexible and tailored optimal sizing solutions. …”
Get full text

Optimized physics-informed neural networks for deciphering of external source pollutants in a swirling flow induced by a constant torsional motion by Shridhar M, Umair Khan, Rahul Makwana, Ankur Kulshreshta, N.B. Naduvinamani

“…The flow, heat and mass transport attributes are assessed using the Physics-informed neural network (PINN). This model is optimized by a hybrid genetic algorithm and particle swarm optimization to address the flow, heat and mass transport attributes via neural networks. …”
Get full text

Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

“…The proposed algorithm combines the strengths of particle swarm optimization (PSO) and the ant lion optimizer (ALO), which are enhanced by the Eagle strategy to systematically fine-tune the FOPID controller parameters. …”
Get full text

Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

“…Furthermore, a parallel PSO-RF algorithm combining Particle Swarm Optimization (PSO) and Random Forest (RF) is designed to enhance classification performance and computational efficiency. …”
Get full text

Research on the Range of Stiffness Variation in a 2D Biomimetic Spinal Structure Based on Tensegrity Structures by Xiaobo Zhang, Zhongcai Pei, Zhiyong Tang

“…Ultimately, the PSO (Particle Swarm Optimization) algorithm is employed to identify the optimal combination of structural parameters for maximizing the stiffness ratio, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>K</mi></mrow><mrow><mi>θ</mi><mo>_</mo><mi>t</mi><mi>i</mi><mi>m</mi><mi>e</mi></mrow></msub></mrow></semantics></math></inline-formula>, of SBTDTS under different constraint conditions. …”
Get full text

Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…Therefore, in order to solve the AMT vibration monitoring problem and enhance the diagnostic efficiency, this study proposes an AMT fault diagnosis model based on particle swarm optimization (PSO) to optimize the parameters of wavelet packet transform (WPT) and support vector machine (SVM).The optimal vibration signal acquisition point is determined by finite element analysis to ensure high signal quality. …”
Get full text

Deployment scheme of RSU based on connection time in VANET by Zhengchao DING, Zhenchun WEI, Lin FENG

“…For the roadside unit (RSU) placement problem in vehicular Ad Hoc network (VANET),the deployment scheme of RSU based on connection time was proposed.The scheme find the optimal positions of RSU for maximizing the number of vehicles while ensuring a certain level of connection time under the limited number of RSU.The problem was modeled as a maximum coverage problem,and a binary particle swarm algorithm was designed to solve it.The simulation experiment was carried out with the real Beijing road network map and taxi GPS data.The simulation results show that the algorithm is convergent,stable and feasible.Compared with the greedy algorithm,the proposed scheme can provide continuous network service for more vehicles.…”
Get full text

Deployment scheme of RSU based on connection time in VANET by Zhengchao DING, Zhenchun WEI, Lin FENG

“…For the roadside unit (RSU) placement problem in vehicular Ad Hoc network (VANET),the deployment scheme of RSU based on connection time was proposed.The scheme find the optimal positions of RSU for maximizing the number of vehicles while ensuring a certain level of connection time under the limited number of RSU.The problem was modeled as a maximum coverage problem,and a binary particle swarm algorithm was designed to solve it.The simulation experiment was carried out with the real Beijing road network map and taxi GPS data.The simulation results show that the algorithm is convergent,stable and feasible.Compared with the greedy algorithm,the proposed scheme can provide continuous network service for more vehicles.…”
Get full text

Forecast-Aided Converter-Based Control for Optimal Microgrid Operation in Industrial Energy Management System (EMS): A Case Study in Vietnam by Yeong-Nam Jeon, Jae-ha Ko

“…The forecasted load data is then used to optimize charge/discharge schedules for energy storage systems (ESS) using a Particle Swarm Optimization (PSO) algorithm. …”
Get full text

Performance evaluation of an optimized simplified nonlinear active disturbance rejection controller for rotor current control of DFIG-based wind energy system by Ahmed Sobhy, Medhat Hegazy Elfar, Ahmed Refaat, Mahmoud Fawzi

“…Due to the inherent nonlinear dynamics of DFIG, which increase the system's complexity, conventional proportional-integral (PI) controllers often face limitations in maintaining optimal performance. To address these challenges, an optimized simplified nonlinear active disturbance rejection (SNADR) control strategy, enhanced through the Particle Swarm Optimization (PSO) algorithm for parameter tuning, is proposed. …”
Get full text

Research on the Optimal Scheduling of Multi-Microgrid Double-Layer Game Considering Fair Carbon Trading Strategy in the Green Certificate Trading Market by Shuaibo Zhang, Fei He, Baofeng Li

“…The proposed method involves the development of a two-layer optimal scheduling model using the Mixed Integer Chaotic Particle Swarm Optimization algorithm (MICPSO). …”
Get full text

Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…The maximum performance of predicting the mechanical loading on the fruits (R2 = 0.91) was obtained by combining the RF with the particle swarm optimization. Also, feature selection results showed that miRNA1917, miRNA172, and miRNA156, as inputs to the optimized RF model could predict the storage temperature, storage period, and mechanical loading on the fruits with R2 values of 0.94, 0.93, and 0.93, respectively. …”
Get full text

Cloud-based real-time enhancement for disease prediction using Confluent Cloud, Apache Kafka, feature optimization, and explainable artificial intelligence by Abdulaziz AlMohimeed

“…The first phase aims to propose a stacking model, apply a genetic algorithm (GA) and Particle swarm optimization (PSO) as feature selection, and explore a stacking model with the best features with explainable artificial intelligence (XAI). …”
Get full text

A Reliable Approach for Solving Transmission Network Expansion Planning with Objective of Planning Cost Reduction by Yongqiu Liu

“…The particle swarm optimization algorithm searches for optimal planning to reach the fitness requirement. transmission expansion planning problem involves a decision on the location and number of new transmission lines. …”
Get full text

Multiobjective optimization of CO2 injection under geomechanical risk in high water cut oil reservoirs using artificial intelligence approaches by Fankun Meng, Jia Liu, Gang Tong, Hui Zhao, Chengyue Wen, Yuhui Zhou, Vamegh Rasouli, Minou Rabiei

“…Therefore, a hybrid optimization framework was designed that combines artificial intelligence methods (Support Vector Regression with the Gaussian kernel, Gaussian-SVR or Long Short-Term Memory, LSTM) and multi-objective optimization algorithms (multiple objective particle swarm optimization, MOPSO or Non-dominated Sorting Genetic Algorithm II, NSGA-II) to find the optimal CO2 injection and production strategies under different water cut. …”
Get full text

Optimizing intelligent reflecting surface assisted visible light communication networks under blockage and practical constraints using TLBO for IoT applications by Vipul Dixit, Ajit Kumar, Nishant Sharan, Shikha Pandey, Atul Kumar, Ram Sewak Singh

“…Additionally, detailed convergence analysis demonstrates that TLBO performs better than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in terms of convergence speed, higher fitness value and lower sensitivity to initial conditions, making it most suitable for real-time IRS-VLC based IoT applications.…”
Get full text

CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…Moreover, the performance of IHO was proven to be optimal compared to HO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), and Sparrow Search Algorithm (SSA) by calculating twelve test functions. …”
Get full text

Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
Get full text

Railway Safety Risk Assessment and Control Optimization Method Based on FTA-FPN: A Case Study of Chinese High-Speed Railway Station by Qi Zhang, Yanhui Zhuang, Yuguang Wei, Hao Jiang, Hao Yang

“…Then, it builds up a bi-objective risk control model, making the minimum safety risk level and minimum necessary cost as the objectives, and it designs discrete particle swarm optimization algorithm to solve the risk control model. …”
Get full text