Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…For each datasheet, both Current–Voltage (I/V) and Power–Voltage (P/V) characteristics of the PEMFCs scenarios closely aligned with those observed in experimental data, affirming AOAAO’s superior accuracy, robustness, and time efficiency for real-time fuel cell modeling. In terms of computational efficiency, AOAAO runtime is significantly faster than all compared algorithms, demonstrating an efficiency improvement of approximately 98%.…”
Get full text

Estimating Nurse Workload Using a Predictive Model From Routine Hospital Data: Algorithm Development and Validation by Paul Meredith, Christina Saville, Chiara Dall’Ora, Tom Weeks, Sue Wierzbicki, Peter Griffiths

“…ObjectiveThe objective of this study is to explore whether an algorithm could estimate ward workload using existing routinely recorded data. …”
Get full text

Modeling and Solving the Knapsack Problem with a Multi-Objective Equilibrium Optimizer Algorithm Based on Weighted Congestion Distance by Ziqian Wang, Xin Huang, Yan Zhang, Danju Lv, Wei Li, Zhicheng Zhu, Jian’e Dong

Get full text

Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
Get full text

A Multi-Algorithm Machine Learning Model for Predicting the Risk of Preterm Birth in Patients with Early-Onset Preeclampsia by Xu Y, Zu Y, Zhang Y, Liang Z, Xu X, Yan J

“…The ensemble prediction model demonstrates the best predictive performance, helping obstetricians identify high-risk patients and perform early intervention to improve perinatal outcomes.Keywords: machine learning, preterm birth, early-onset preeclampsia, clinical prediction model…”
Get full text

Basic principals of the tiltrotors flight control system architecture and algorithms by M. I. Myasnikov, I. R. Ilyin

Get full text

A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

“…Specifically, the Marine Predators Optimization algorithm is introduced to facilitate the model’s solution process. …”
Get full text

Quantum Algorithm for Solving the Wave Equation on a Hexagonal Grid by Roman Novak

Get full text

Lightweight Tea Shoot Picking Point Recognition Model Based on Improved DeepLabV3+ by HU Chengxi, TAN Lixin, WANG Wenyin, SONG Min

“…[Conclusions]This study effectively implements an efficient and accurate tea shoot recognition method through targeted model improvements and optimizations, furnishing crucial technical support for the practical application of intelligent tea picking robots. …”
Get full text

Reply to Comment on “Improving Bayesian Model Averaging for Ensemble Flood Modeling Using Multiple Markov Chains Monte Carlo Sampling” by Jasper Vrugt by Tao Huang, Venkatesh Merwade

Get full text

Methods and Algorithms for Decision-Making in Agro-Industrial Environmental Management by Olga Ivashchuk, Vyacheslav Fedorov, Zhanat Kenzhebayeva, Oleg Ivashchuk, Moldir Allaniyazova, Kaiyrbek Makulov, Gulnar Kaziyeva

Get full text

Heat Pump Temperature Trajectory Planning Algorithm for Bus Voltage Sag Suppression by Yangyang ZHAO, Lan LIU, Wei ZHAO, Shuang ZENG, Anqi LIANG, Hanqiu WANG, Kai MA

“…The simulation results show that the proposed algorithm can significantly suppress the transient sag of DC bus voltage in the process of heat pump temperature regulation, which are well suited to the smooth control and improving stability of building’s DC microgrid system.…”
Get full text

Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
Get full text

Improving the accuracy of thermal power determination of VVER by V. I. Borysenko, D. V. Budyk, V. V. Goranchuk

“…In the article, the main factors influencing the errors of determination of RTP in different ways are considered: according to the thermal parameters of the 1st and 2nd contours and the parameters of the neutron flux in the Neutron Flux Monitoring System (NFMS) and In-core Monitoring System (ICMS). In order to improve the accuracy of determination of RTP in the NFMS, we propose a model that considers the influence on the signal of the ionization chamber of the following parameters: temperature and concentration of boric acid in the coolant, the position of the control rods, burning of fuel, etc. …”
Get full text

Enhanced genetic algorithm for indoor low-illumination stereo matching energy function optimization by Zhang Hongjin, Wei Hui

Get full text

Algorithm of passive “Beidou”/INS closed-loop integrated using two level filter by GAO Fa-qin, TAN Zhan-zhong

“…One scheme of integrated navigation Kalman filter positioning algorithm was put forward to apply to “Beidou” and INS（intertial navigation system）.Using the pseudo-range’s velocity of changing as observations,on the basis of the high stable clock,a closed loop Kalman filtering model that can revise the attitude error of INS was put out,its biggest optimism was that it could change between the close-loop method and open-loop method steadily.Finally,by computer simulation,it explain that our scheme improve the positioning precision effectively when the satellites in sight are less then two ones,and it also show that our scheme can revise the attitude error of INS effectively and estimate the user’s velocity in high precision.…”
Get full text

Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm by Ying-Chun CHANG, Min-Chie CHIU, Meng-Ru WU

“…With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). Consequently, the discharged muffler which is optimally shaped will improve the automotive exhaust noise.…”
Get full text

Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

Get full text

Feedforward Factorial Hidden Markov Model by Zhongxing Peng, Wei Huang, Yinghui Zhu

“…Consequently, we propose two algorithms for these FFHMM models to estimate their respective hidden states. …”
Get full text

Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

“…For both datasets, the experimented three feature selection methods consistently improved the accuracy of the models. For EEG Emotion dataset, RF with LASSO achieved the best result among all the experimented methods increasing the accuracy from 98.78% to 99.39%. …”
Get full text