Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning by Yasser Abduallah, Jason T. L. Wang, Prianka Bose, Genwei Zhang, Firas Gerges, Haimin Wang

“…Experimental results show that the proposed Dst Transformer outperforms related machine learning methods in terms of the root mean square error and R-squared. …”
Get full text

Out-of-Step Protection for a Synchronous Generator via Energy Function-Based Stability Assessment Using a Single Local Speed Measurement by Jongju Kim

“…By employing individual machine energy functions, this approach establishes a theoretical foundation for determining synchronization thresholds from the perspective of a single generator. …”
Get full text

Driving-Cycle-Adaptive Energy Management Strategy for Hybrid Energy Storage Electric Vehicles by Zhaocheng Lu, Tiezhu Zhang, Rui Li, Xinyu Ni

“…Dynamic programming is employed to optimize the rule-based control strategy, while the grey wolf optimizer (GWO) is utilized to enhance the least squares support vector machine (LSSVM) driving cycle recognition model. The optimized driving cycle recognition model is integrated with the improved rule-based control strategy, facilitating adaptive adjustment of control parameters based on driving cycle identification results. …”
Get full text

Sustainable improvement and application of multilingual english translation quality using T5 and MAML by Hongping Sun, Biao Kong

“…The experimental results show that compared to the baseline models Open Neural Machine Translation (OpenNMT), Transformer, and Open Parallel Corpus-Machine Translation (Opus-MT), the mean BLEU Score of the model in this article is 6.05%, 2.59%, and 2.05% higher, respectively. …”
Get full text

Decoding Brain Signals in a Neuromorphic Framework for a Personalized Adaptive Control of Human Prosthetics by Georgi Rusev, Svetlozar Yordanov, Simona Nedelcheva, Alexander Banderov, Fabien Sauter-Starace, Petia Koprinkova-Hristova, Nikola Kasabov

“…Current technological solutions for Brain-machine Interfaces (BMI) achieve reasonable accuracy, but most systems are large in size, power consuming and not auto-adaptive. …”
Get full text

Building Fire Location Predictions Based on FDS and Hybrid Modelling by Yanxi Cao, Hongyan Ma, Shun Wang, Yingda Zhang

“…Different scenarios were built to simulate the spatial and temporal distributions of key parameters such as temperature, smoke, and CO concentration during the fire process. …”
Get full text

Experimental Study on Factors Affecting Waterproof Failure of Shield Tail Sealing System by JIANG Peifeng

Get full text

Combined Rough Sets and Rule-Based Expert System to Support Environmentally Oriented Sandwich Pallet Loading Problem by Piotr Sawicki, Hanna Sawicka, Marek Karkula, Krzysztof Zajda

Get full text

Advanced Control Strategy for Induction Motors Using Dual SVM-PWM Inverters and MVT-Based Observer by Omar Allag, Abdellah Kouzou, Meriem Allag, Ahmed Hafaifa, Jose Rodriguez, Mohamed Abdelrahem

“…An advanced observer using sector nonlinearity (SNL) and time-varying parameters from convex theory is developed to manage state observer error dynamics effectively. …”
Get full text

An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…Then we combine the TRSMA with Support Vector Machines (SVM) and propose the TRSMA-SVM model to select the joint feature and classifier parameters. …”
Get full text

Research on an Intelligent Prediction Method for the Carbon Emissions of Prefabricated Buildings During the Construction Stage, Based on Modular Quantification by Yang Yang, Xiaodong Cai, Xinlong Ma, Gang Yao, Ting Lei, Hongbo Tan, Ying Wang

“…This study clarifies the system boundary of carbon emissions and the parameters of influence in carbon emissions predictions. …”
Get full text

QoS-Aware Link Adaptation for Beyond 5G Networks: A Deep Reinforcement Learning Approach by Ali Parsa, Neda Moghim, Sachin Shetty

Get full text

Software complex for simulation modelling of single nucleotide genetic polymorphism sites by M. M. Yatskou, D. D. Sarnatski, V. V. Skakun, V. V. Grinev

“…A software complex has been developed for simulation modelling and identification of single nucleotide polymorphism sites using machine learning methods. The methods for the approach to simulation modelling and analysis of single nucleotide polymorphism sites in DNA molecules are implemented based on the beta or normal distributions, the parameters of which are determined from the available experimental data, and machine learning models trained on simulated data and used to accurately identify single nucleotide polymorphism sites. …”
Get full text

Models of user experience quality in computer information systems by П. Р. Пелех, В. М. Юзевич

“…The model incorporates three synergistic components: a Fuzzy Inference System (FIS) to interpret imprecise or ambiguous user feedback; Multi-Criteria Decision Analysis (MCDA), used to normalize and prioritize heterogeneous parameters in real time; a regression-based machine learning model for dynamic adjustment of input weights based on contextual variations. …”
Get full text

A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

“…To address these limitations, we propose a novel model combining a two-dimensional convolutional restricted Boltzmann machine (2D Conv-RBM) with a long short-term memory (LSTM) network. …”
Get full text

Optimizing Cold Box Core Making in Cast Iron Foundry: A Sustainable Approach with Taguchi Technique and Desirability Function by G.R. Chate, P.H. Kulkarni, A. Gramopadhye, A. Kalbhairav, S. Chungade, H. Patil, A.M. Kono, N. Rangaswamy

“…The present work focuses on studying the effect of a cold box core shooter machine's process parameters on producing high-quality cores with maximum core hardness and minimum gas evolution. …”
Get full text

Multi-Step Prediction of TBM Tunneling Speed Based on Advanced Hybrid Model by Defu Liu, Yaohong Yang, Shuwen Yang, Zhixiao Zhang, Xiaohu Sun

“…The accurate prediction of tunneling speed in tunnel boring machine (TBM) construction is the basis for the timely adjustment of the operating parameters of TBM equipment to ensure safe and efficient tunneling. …”
Get full text

CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…Extensive numerical experiments were conducted to optimize model parameters and evaluate performance, ensuring high accuracy, stability, and superior AUC values for reliable predictions. …”
Get full text

Surrogate Modeling for Building Design: Energy and Cost Prediction Compared to Simulation-Based Methods by Navid Shirzadi, Dominic Lau, Meli Stylianou

“…Overall, the findings demonstrate that machine learning-based surrogate models can serve as fast, accurate, and interpretable alternatives to traditional simulation methods, supporting efficient decision-making during early-stage building design.…”
Get full text

An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

Get full text