Privacy-Preserving Diabetes and Heart Disease Prediction via Federated Learning and WCO by Sachikanta Dash, Sasmita Padhy, Preetam Suman, Sandip Mal, Lokesh Malviya, Amrit Suman, Jaydeep Kishore

“…This study introduces the Federated Learning with Weighted Conglomeration Optimization (FLWCO) model as a solution to these challenges. …”
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Synergistic Integration of LQR Control and PSO Optimization for Advanced Active Suspension Systems Utilizing Electro-Hydraulic Actuators and Electro-Servo Valves by Trong Tu

“…This research remarks the fundamentals of the experimental validation and further refinement of these control algorithms to adapt to various driving conditions and vehicle models, ultimately aiming to transition these optimized controllers from theoretical frameworks to practical, real-world applications. …”
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Hyperspectral Anomaly Detection by Spatial–Spectral Fusion Based on Extreme Value-Entropy Band Selection and Cauchy Graph Distance Optimization by Song Zhao, Yali Lv, Wen Zhang, Lijun Wang, Zhiru Yang, Gaofeng Ren, Bin Wang, Xiaobin Zhao, Tongwei Lu, Jiayao Wang, Wei Li

“…This method replaces the traditional covariance matrix with a significance-weighted Cauchy distance graph, reducing the influence of the target on the background and improving the model’s robustness in complex environments. …”
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Analysis of the sports action recognition model based on the LSTM recurrent neural network by Chen Ping, Peng Jiangui

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Feasibility of machine learning–based modeling and prediction to assess osteosarcoma outcomes by Qinfei Zhao, Weiquan Hu, Yu Xia, Shengyun Dai, Xiangsheng Wu, Jing Chen, Xiaoying Yuan, Tianyu Zhong, Xuxiang Xi, Qi Wang

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Offline System for 2D Indoor Navigation Utilizing Advanced Data Structures by Jorge Luis Veloz, Leo Sebastián Intriago, Jean Carlos Palma, Andrea Katherine Alcívar-Cedeño, Álvaro Antón-Sacho, Pablo Fernández-Arias, Edwan Anderson Ariza, Diego Vergara

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Fault Diagnosis of Oil Pumping Machine Retarder Based on Sound Texture-Vibration Entropy Characteristics and Gray Wolf Optimization-Support Vector Machine by Shutao Zhao, Ke Chang, Erxu Wang, Bo Li, Kedeng Wang, Qingquan Wu

“…Finally, joint eigenvectors were constructed and fed into SVM for learning. The gray wolf optimization (GWO) algorithm was used to optimize the parameters of the SVM model based on mixed kernel function, which reduces the impact of sensor frequency response, environmental noise, and load fluctuation disturbance on the accuracy of retarder fault diagnosis. …”
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A Fault Diagnosis Method for Oil Well Electrical Power Diagrams Based on Multidimensional Clustering Performance Evaluation by Xingyu Liu, Xin Meng, Ze Hu, Hancong Duan, Min Wang, Yaping Chen

“…Through simulations and experiments on 10 UCI datasets, the proposed effectiveness function accurately evaluates the clustering results and determines the optimal number of clusters, significantly improving the performance of the clustering algorithm. …”
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Student employment forecasting model based on random forest and multi-features fusion by Zhenguo Xing, Xiao Wu, Jiangjiang Li

“…Secondly, in order to improve the accuracy of the prediction model, a feature selection model combining principal component analysis and random forest algorithm is used to select the optimal subset from the original features. …”
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A new method for recognizing geometric parameters of industrial robots by Bin Kou, Yi Zhang

“…Following this, we improve the accuracy of global optimization of the particle swarm optimization (PSO) algorithm by drawing on the wandering behavior of the wolf pack algorithm and hybridization behavior of the genetic algorithm. …”
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Research on Tracking Control of Unmanned Mine Trucks Based on Adaptive Preview by HUANG Yaoran, LIU Zhicong, KANG Yuanrong

“…In the view that lateral tracking accuracy of mine trucks is not high under the condition of complex path and muddy road, in order to improve the adaptability of the control algorithm to the complex driving environment in the mining area, an adaptive preview tracking control algorithm considering multi-factor fusion is proposed in this paper. …”
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A Comparative Study Between Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) Algorithms for Solar PV MPPT Control Under Partial Shading Conditions by Sampson E. Nwachukwu, Komla A. Folly, Kehinde O. Awodele

“…However, due to the intermittent nature of PV arrays, the Maximum Power Point Tracking (MPPT) algorithm is typically employed to optimize the system’s energy production. …”
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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.…”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…Various parameters such as obstacle size and complexity influence the agent's performance, promoting efficient learning and policy optimization using both DQN and DDQN algorithms under different configurations. …”
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Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model by Dongge Cui, Chuanqu Zhu, Qingfeng Li, Qiyun Huang, Qi Luo

“…Against with low accuracy and limited applicability of a single model in forecasting, a PSO-GM-BP model was established, which used the PSO optimization algorithm to optimize and improve the GM (1, 1) model and the BP network model, respectively. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The Poak-Ribiére conjugate gradient back propagation algorithm (PRBP) of numerical optimization technology was used, and 21 rainstorm and flood processes from 1997 to 2022 in the upper reaches of Chongyang River basin were studied. …”
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Research on PRBP Neural Network Flood Forecasting Model in Chongyang River Basin by SI Qi, JIN Baoming, LU Wangming, CHEN Zhaoqing

“…The Poak-Ribiére conjugate gradient back propagation algorithm (PRBP) of numerical optimization technology was used, and 21 rainstorm and flood processes from 1997 to 2022 in the upper reaches of Chongyang River basin were studied. …”
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A Capacity Optimization Configuration Method for Photovoltaic and Energy Storage System of 5 G Base Station Considering Time-of-Use Electricity Price by Ziyan HAN, Shouxiang WANG, Qianyu ZHAO, Zhijie ZHENG

“…Then, the quantum-behaved particle swarm optimization algorithm is used to calculate the minimum comprehensive cost of the photovoltaic and energy storage system of 5G base station in a typical day to determine the optimal capacity of photovoltaic power generation and energy storage. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Active Magnetic Bearing Rotor Model Updating Using Resonance and MAC Error by Yuanping Xu, Jin Zhou, Long Di, Chen Zhao, Qintao Guo

“…Modelling error is minimized by applying a numerical optimization Nelder-Mead simplex algorithm to properly adjust FE model parameters. …”
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