A Federated Learning Model for Detecting Cyberattacks in Internet of Medical Things Networks by Abdallah Ghourabi, Adel Alkhalil

“…The XGBoost models are further optimized using a Bayesian method and integrated with an aggregation algorithm to construct an adaptive global model. …”
Get full text

Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…It was determined that their integrated application provides an increase in the accuracy of reserve assessment by 15–20 % and a reduction in operating costs by 10–15 %. Key development trends are identified: integration of digital technologies, improvement of methods of collecting and processing geospatial data, introduction of machine learning algorithms for risk prediction. …”
Get full text

An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…This efficiency gain during optimization is attributed to the model's intrinsic stability, which reduces the number of divergent trials encountered by the search algorithm.DiscussionThe results indicate that the ESN-EICM framework is a viable method for the prediction of the tested chaotic time series. …”
Get full text

Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization) by Almira Budiyanto, Keisuke Azetsu, Nobutomo Matsunaga

“…When transfer learning is combined with fast computation, the efficiency of edge-level re-learning is improved. This paper proposes a formation change algorithm that allows easy and fast multi-robot knowledge transfer using SDPA combined with MAPPO (Multi-Agent Proximal Policy Optimization), compared to other methods. …”
Get full text

Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

“…The integration of BIM with other analytical algorithms also allows optimization of designs, such as the generative design that can parametrize the design. …”
Get full text

Advanced Deep Learning Approaches in Detection Technologies for Comprehensive Breast Cancer Assessment Based on WSIs: A Systematic Literature Review by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

Get full text

Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
Get full text

Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

Get full text

An English Diagnostic Intelligence Evaluation Model Based on Organizational Evolutionary Information Entropy by Haiying Sang

“…In order to realize the English diagnostic intelligence evaluation, improve the English learning ability, and construct the cognitive framework of English learning, this study proposes an English diagnostic intelligence evaluation model based on the organizational evolution information entropy. …”
Get full text

A Parameter Estimation Method of DC-link Capacitor Based on Pre-charge Process of Traction Converter by LYU Gexing, ZHU Qi

“…In order to improve the reliability of the estimation, different from the traditional parameter identification algorithm based on gradient descent, the genetic algorithm is used to search for the optimal value in the range of health parameter and estimate the real parameter. …”
Get full text

Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
Get full text

Accelerated Reconstruction of Scenes Using CUDA-Based Parallel Computing by Gui Zou, Jin Jiang, Qi Chen

“…Since the drone needs to use an embedded onboard computer and stereo matching algorithms require massive computing resources, this paper studies the optimization of CUDA-based stereo matching algorithms on embedded devices to improve the reconstruction effect of scenes and achieve rapid reconstruction, thereby reducing time costs, and enhancing drone efficiency.…”
Get full text

A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

“…Conclusions Compared with the baseline model, YAC-Net optimizes the model structure and simplifies the parameters while ensuring the detection performance. …”
Get full text

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. …”
Get full text

Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
Get full text

Diffusion Model With Gradient Descent Module Guiding Reconstruction for Single-Pixel Imaging by Chen Huang, Qiurong Yan, Jinwei Yan, Yi Li, Xiaolong Luo, Hui Wang

“…Inspired by the proximal gradient descent algorithm (PGD), we propose Diffusion Model with Gradient Descent Module Guiding Reconstruction for Single-Pixel Imaging. …”
Get full text

Research on multimodal social media information popularity prediction based on large language model by WANG Jie, WANG Zitong, PENG Yan, HAO Bowen

“…Finally, an improved direct preference optimization (DPO) algorithm IDPOP was developed by constructing preference data and adding a parameter-tuned penalty to the DPO loss function, resolving instability and non-convergence in RLHF and incorrect optimization in standard DPO for social media popularity prediction. …”
Get full text

Modeling vector control of the asynchronous drive of electric rolling stock auxiliary machines by Yu. M. Kulinich, S. A. Shukharev, V. K. Dukhovnikov, A. V. Gulyaev

“…The developed complex of an asynchronous motor and a vector control system enable to work out various algorithms for improving the energy efficiency of the operation of asynchronous auxiliary machines of an electric locomotive by applying the proposed algorithm for choosing the optimal value of the rotor flux linkage. …”
Get full text

Characterizing Wake Behavior of Adaptive Aerodynamic Structures Using Reduced-Order Models by Kyan Sadeghilari, Aditya Atre, John Hall

“…Hence, the development of better wake models is critical for better turbine design and controls. …”
Get full text

Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…Experimental results demonstrate that the proposed quantum model outperforms classical algorithmic models in handling higher complexity, achieving improved efficiency, reduced computation time, and superior predictive performance. …”
Get full text