Explanation and Optimizing Multi‐Model Blending Algorithm Using Random Variables Theory by Yu Wang, Yong Cao, Yue Shen, Ruixia Zhao, Xiaoqing Zeng, Li Yao, Kan Dai

“…This improvement may be attributed to modeling the actual forecast error as a normally distributed unified parameter and applying a consistent correlation coefficient across the annual data set.…”
Get full text

An optimization model of computer network security based on GABP neural network algorithm by Jiangang Wang, Xiaoyan Wang

“…Objective This research proposed the investigation of the Genetic Algorithm with Back Propagation Neural Network (GA-BPNN) model for computer network safety. …”
Get full text

Construction of multi-style face models based on artistic image generation algorithms by Xu Zhaoyi

“…The research results indicated that the new algorithmic model could improve the data metrics of face models. …”
Get full text

ECAPM: An Enhanced Coverage Algorithm in Wireless Sensor Network Based on Probability Model by Sun Zeyu, Wang Huanzhao, Wu Weiguo, Xing Xiaofei

“…To address this problem, this paper proposes ECAPM, that is, Enhanced Coverage Algorithm Based on Probability Model. Given an area to monitor, ECAPM can calculate the minimum number of sensor nodes to cover that area. …”
Get full text

Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model. by Kanes Sumetpipat, Duangkamon Baowan

Get full text

Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

“…The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
Get full text

Approximation Algorithms for Maximum Link Scheduling under SINR-Based Interference Model by Zi-Ao Zhou, Chang-Geng Li

“…To date, several approximation algorithms have been proposed to solve MLS under the SINR-based interference model. …”
Get full text

Research on an internal model control algorithm and parameter tuning for metro traction PMSMs by SI Junmin, YUE Xuelei, TIAN Di, XU Kelei

Get full text

Integrating Artificial Intelligence and Computational Algorithms to Optimize the 15-Minute City Model by Marwa Abouhassan, Samah Elkhateeb, Raneem Anwar

“…Furthermore, it elaborates on how the integration of artificial intelligence (AI) and computational tools can be utilized in optimizing the 15-minute city model. We reveal how AI-driven algorithms, machine learning techniques, and advanced data analytics can enhance urban planning, improve accessibility, and foster social integration. …”
Get full text

Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

“…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
Get full text

Construction of prognostic scoring model for ovarian cancer based on deep learning algorithm by Xiaolin Zhong, Hongyang Xiao, Weihong Lu, Jiayuan Chen, Fan Chao, Ruiqin Tu

“…Accurate prognostic prediction and timely treatment are critical for improving patient outcomes. The aim of this study was to develop a prognostic prediction model for ovarian cancer based on pathological images. 158 In-house and 105 TCGA-OV pathological slides were processed with Macenko’s algorithm for stain normalization and patch extraction (256 × 256 pixels). …”
Get full text

Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms by Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga, Ana Gómez

“…This study presents a methodology to optimize concrete mixtures by integrating machine learning (ML) and genetic algorithms. ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. …”
Get full text

MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…Among the models, the XGBoost algorithm demonstrated the highest performance, providing precise predictions that closely aligned with the actual groundwater levels. …”
Get full text

Enhancing Performance of Credit Card Model by Utilizing LSTM Networks and XGBoost Algorithms by Kianeh Kandi, Antonio García-Dopico

“…This paper conducts an extensive literature review, comparing various machine learning methods, and proposes an innovative framework that compares LSTM with XGBoost to improve fraud detection accuracy. LSTM, a recurrent neural network renowned for its ability to capture temporal dependencies within sequences of transactions, is compared with XGBoost, a formidable ensemble learning algorithm that enhances feature-based classification. …”
Get full text

Fine-Pruning: A biologically inspired algorithm for personalization of machine learning models by Joseph Bingham, Saman Zonouz, Dvir Aran

Get full text

Problems of Algorithms Development to Determine Quality of Topic Models Ensembles for Make Rubricators by A. P. Shiryaev, A. R. Fedorov, P. A. Fedorov, L. G. Gagarina, E. M. Portnov

“…The concept for quality evaluation of thematic models ensemble, which uses the simple voting algorithm, was explored and proposed for further researches.…”
Get full text

Control algorithm for an elastic-viscoplastic model to study processes of shock interaction of bodies by V. L. Lapshin, Е. V. Zenkov

“…The research objective is to develop a more accurate shock simulation algorithm through the controlled transformation of the mechanorheological shock process model from elasticviscous to elastic-viscoplastic.Materials and Methods. …”
Get full text

Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…First, the variable mode decomposition method is used to decompose the historical data of carbon emissions in Zhejiang Province, enabling an analysis of its cyclicality fluctuations. Second, the LASSO algorithm is employed to identify the key influencing factors of carbon emissions. …”
Get full text

Long tunnel group driving fatigue detection model based on XGBoost algorithm by Huazhi Yuan, Kun Zhao, Ying Yan, Li Wan, Zhending Tian, Xinqiang Chen

“…In addition, a significant correlation exists between the driving duration index and driving fatigue, which can provide a reference for improving the tunnel safety. Using the mean value of blink duration and driving duration as the characteristic indexes, the accuracy of the driving fatigue detection model based on the XGBoost algorithm reaches 98%. …”
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

“…Conclusion The intelligent Continuous Kidney Replacement Therapy nursing feedback model improves prediction accuracy while reducing redundant information. …”
Get full text