Leveraging Azure Automated Machine Learning and CatBoost Gradient Boosting Algorithm for Service Quality Prediction in Hospitality by Avisek Kundu, Seeboli Ghosh Kundu, Santosh Kumar Sahu, Nitesh Dhar Badgayan

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Research on a dynamic self-learning efficient intrusion detection model by YANG Wu1, ZHANG Bing2, ZHOU Yuan2, WANG Wei1

“…A dynamic self-learning efficient intrusion detection model was proposed based on inductive reasoning.Ap-plying the method of inductive reasoning into intrusion detection,an incremental inductive reasoning algorithm for intru-sion detection was proposed.This model produced by this algorithm can make self-learning over the ever-emerged new network behavior examples and dynamically modify behavior profile of the model,which overcomes the disadva-ntage that the traditional static detecting model must relearn over all the old and new examples,even can not relearn because of limited memory size.And at the same time,the learning efficiency and detecting efficiency of intrusion detection model are improved greatly.…”
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A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation by Jeridi Ahmed, Moulahi Mohamed Hedi, Khaterchi Hechmi, Zaafouri Abderrahmen

“…The effectiveness of the WSO-HO algorithm was rigorously evaluated through intensive testing on three different solar panels, including the RTC France solar cell using the single diode model (SDM) and the double diode model (DDM), over 30 iterations. …”
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Research on the Photovoltaic MPPT Method Based on Improved BP-SVM-ELM Combination Prediction by DAI Bowang, ZHAO Xianggui, ZHU Qiliang

“…Through experimental simulation analysis, the combined forecasting method can use the advantages of each algorithm, effectively avoiding their deficiencies, and fundamentally improve the performance of the predictive model. …”
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Multi-level model describing phase transformations of polycrystalline materials under thermo-mechanical impacts by Peter Trusov, Elena Makarevich, Nikita Kondratev

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Short-Term Power Load Forecasting Method based on Glowworm Swarm Optimization Algorithm by Haihong FAN

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Donor Segmentation Analysis Using the RFM Model and K-Means Clustering to Optimize Fundraising Strategies by Rezki ., Nouval Trezandy Lapatta, Rizka Ardiansyah, Wirdayanti ., Dwi Shinta Angreni

“…This study aims to segment donors using the Recency, Frequency, Monetary (RFM) model and the K-Means algorithm to optimize fundraising strategies. …”
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Optimization of deep learning architecture based on multi-path convolutional neural network algorithm by Chuan Zhou, Yan Liu, Xinghan An, Xiyao Xu, Hao Wang

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Rainfall Prediction in Khorasan Razavi Stations Using a Hybrid Neural Network and Genetic Algorithm Approach by Mahdi Naseri, Mahsa Mardani

“…This study proposes a novel hybrid approach, combining the Non-linear Auto Regressive with eXogenous inputs (NARX) neural network with a Genetic Algorithm (GA) for parameter optimization, aiming to improve daily rainfall prediction in Khorasan Razavi province, Iran. …”
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Scheduling Algorithm: Tasks Scheduling Algorithm for Multiple Processors with Dynamic Reassignment by Pradeep Kumar Yadav, M. P. Singh, Harendra Kumar

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Evaluation and Application of Machine Learning Techniques for Quality Improvement in Metal Product Manufacturing by Katarzyna Antosz, Lucia Knapčíková, Jozef Husár

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Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique by Hao Huang, Zhaoli Wang, Yaoxing Liao, Weizhi Gao, Chengguang Lai, Xushu Wu, Zhaoyang Zeng

“…In order to reveal the intrinsic mechanism of prediction by such architectures, we adopted a coupled CNN-LSTM model based on the explainability technique SHapley Additive exPlanations (SHAP) to predict the rainfall-runoff process and identify key input feature factors, and took the Beijiang River Basin in China as an example, so as to improve the explainability and credibility of this black-box model. …”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

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Advanced AI approaches for the modeling and optimization of microgrid energy systems by Mohammed Amine Hoummadi, Badre Bossoufi, Mohammed Karim, Ahmed Althobaiti, Thamer A. H. Alghamdi, Mohammed Alenezi

“…These AI models maximize the use of renewable energy, reduce wastage, and improve microgrid resilience and responsiveness to supply and demand fluctuations. …”
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MSKT: multimodal data fusion for improved nursing management in hemorrhagic stroke by Ting Zhou, Dandan Li, Jingfang Zuo, Aihua Gu, Li Zhao

“…Results The proposed MSKT-NSGP model outperformed traditional algorithms in prediction accuracy, computational efficiency, and uncertainty handling. …”
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A Study on Improving of Adaptive Sensorless Control Performance via Funnel Control by Jun-Seo Han, Gyung-Jae Cho, Hyeon-Ji Jin, Geun-Ho Lee

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Energy-saving optimization solution for multiple freight trains based on maFOA algorithm by LAN Li, LI Le, MA Ruijie

“…Additionally, a multi-strategy adaptive fruit fly optimization algorithm for population partitioning (maFOA) was proposed, to address the challenges faced by existing algorithms in solving complex nonlinear “train-track-grid" models, which often result in low convergence accuracy. …”
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A Learning-Enhanced Metaheuristic Algorithm for Multi-Zone Orienteering Problem with Time Windows by Hongwu Li, Yongqi Luo, Yanru Chen, Yangsheng Jiang

“…The HACO algorithm combines the global search capabilities of a population-based algorithm with the parallel decision-making abilities of the Pointer Network learning model. …”
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A fuzzy finite element algorithm based on response surface method for free vibration analysis of structure by Nguyen Hung Tuan, Le Xuan Huynh, Pham Hoang Anh

“… This paper introduces an improved response surface-based fuzzy finite element analysis of structural dynamics. …”
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Electrical Fault Diagnosis Method for Tunneling Equipment Based on Fault Simulation and Optimized Particle Swarm Algorithm by Huan Zou, Xueping Zhang, Xin Wang, Yu Li

“…To address the challenges of scarce training data and poor adaptability to dynamic working conditions in electrical fault diagnosis for tunneling equipment, this study proposes an intelligent diagnosis model based on fault simulation and Improved Particle Swarm Optimization (IPSO). …”
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