An adaptive hybrid framework for IIoT intrusion detection using neural networks and feature optimization using genetic algorithms by Mohammad Zubair Khan, Aijaz Ahmad Reshi, Shabana Shafi, Ibrahim Aljubayri

“…Additionally, Genetic Algorithms were employed to optimize feature selection, further refining the ANN’s input space to improve computational efficiency without sacrificing predictive power. …”
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Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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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. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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Focused Crawler for Event Detection Using Metaheuristic Algorithms and Knowledge Extraction by Hossein Moradi, Fatemeh Azimzadeh

“…By integrating this method with machine learning algorithms, the proposed technique exhibits improvements in experiments, including decreased execution time and enhancements in metrics such as Root Mean Square Error (RMSE) and accuracy score. …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

“…Accurate prediction can help passengers make travel plans and improve travel efficiency. Given the nonlinearity, randomness, and complexity of bus arrival time, this paper proposes the use of a wavelet neural network (WNN) model with an improved particle swarm optimization algorithm (IPSO) that replaces the gradient descent method. …”
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RELIABILITY OPTIMIZATION DESIGN ON SHEARER’S RANGING ARM GEAR TRANSMISSION SYSTEM by LI FengJiang, ZHANG Jie, LIAO YingHua, LI QingChen

“…In the process of design shearer ’s ranging arm gear transmission system,by using the method of reliability design theory,derived gear strength and stress assumed to obey normal distribution when tooth surface contact fatigue strength and tooth root bending fatigue strength were taken as constraint conditions,and the volume of gear system as objective function,then genetic algorithm optimization toolbox of MATLAB was used to solve the optimization mathematic model. …”
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DynaFusion-SLAM: Multi-Sensor Fusion and Dynamic Optimization of Autonomous Navigation Algorithms for Pasture-Pushing Robot by Zhiwei Liu, Jiandong Fang, Yudong Zhao

“…The results indicate that when the RTAB-Map algorithm fuses with the multi-source odometry, its performance is significantly improved in the laboratory-simulated ranch scenario, the maximum absolute value of the error of the map measurement size is narrowed from 24.908 cm to 4.456 cm, the maximum absolute value of the relative error is reduced from 6.227% to 2.025%, and the absolute value of the error at each location is significantly reduced. …”
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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

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Algorithms and probabilistic models of parameters of operation of in-plant power supply by E. I. Gracheva, O. V. Naumov, A. N. Gorlov, Z. M. Shakurova

“…To investigate the operability of low-voltage shop networks of radial, trunk and mixed structure in optimal operating conditions of the equipment when modeling the impact of external factors, such as the root-mean-square load factor of the equipment, the temperature of the shop room and the calculated time interval on the operating parameters of the system. …”
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A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batt... by Mehrdad Shoeibi, Anita Ershadi Oskouei, Masoud Kaveh

“…Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.…”
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An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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Multi-strategy improved runge kutta optimizer and its promise to estimate the model parameters of solar photovoltaic modules by Serdar Ekinci, Rizk M. Rizk-Allah, Davut Izci, Emre Çelik

“…By aligning experimental and model-based estimated data, our approach seeks to reduce errors and improve the accuracy of PV system performance. We conduct meticulous analyses of two compelling case studies and the CEC 2020 test suite to showcase the versatility and effectiveness of our improved RUN (IRUN) algorithm. …”
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SIMULATION ANALYSIS AND OPTIMIZATION OF AIR SUSPENSION SYSTEM OF A LIGHT COMMERCIAL VEHICLE (MT) by WANG Lei, HUANG ZhaoMing, LI HaiYu, CHEN Tian

“…The simulation results of ride comfort after optimization show that: under random input, the root mean square value of weighted acceleration at the driver is reduced by 13.6%, and that at the passenger is reduced by 25.6%; under pulse input, the maximum vertical acceleration at the driver is reduced by 15.9%, and that at the passenger is reduced by 29.4%, and the ride comfort of the whole vehicle is significantly improved.…”
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Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

“…An error analysis—based on the Root Mean Square Error (RMSE) and confidence ellipses—confirms that the inclusion of mechanical measurements significantly improves the accuracy of the identified parameters and the reliability of the algorithm compared to approaches relying just on electrochemical data. …”
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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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Structural Optimization-Based Enhancement of the Dynamic Performance for Horizontal Axis Wind Turbine Blade by Ahmed Zarzoor, Alaa Jaber, Ahmed Shandookh

“…It employs a complex optimization framework that combines aerodynamics and structural analysis via MATLAB and a genetic algorithm. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm by Hadeer Khalifa, Mohamed Ebeed, Gaber Magdy, Sherif A. Khaleel, Mohamed I. Shehata, Moataz M. Salah, Francisco Jurado, Hossam Hassan Ali

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