Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…Abstract The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification by Junwen Ding, Xu Wu, Jie Tian, Yuanpeng Li

“…To overcome these limitations, this paper proposes RE-BPFT, an enhanced consensus algorithm that integrates a nuanced node credibility model considering direct interactions, indirect reputations, and historical behavior. …”
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Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods by Qiankun Jiang, Haiyan Wang

“…After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. …”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

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Advanced control scheme for harmonic mitigation and performance improvement in DC-AC microgrid with parallel voltage source inverter by Buddhadeva Sahoo, Subhransu Ranjan Samantaray, Mohammed M. Alhaider

“…The system integrates an incremental conductance-based maximum power algorithm (IC-MPA) to achieve efficient PV energy extraction and a bidirectional converter model to regulate battery charging/discharging operations, maintaining DC-link voltage stability. …”
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Optimized Grasshopper Optimisation Algorithm enabled DETR (DEtection TRansformer) model for skin disease classification. by Shakti Kundu, Yogesh Kumar Sharma, Khan Vajid Nabilal, Gopalsamy Venkatesan Samkumar, Sultan Mesfer Aldossary, Shanu Kuttan Rakesh, Nasratullah Nuristani, Arshad Hashmi

“…Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy. …”
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ONBOARD FUEL PUMP FAULT DIAGNOSIS BASED ON IMPROVED SUPPORT VECTOR MACHINE AND EXPERIMENTAL RESEARCH by LIANG Wei, JING Bo, JIAO XiaoXuan, QIANG XiaoQing, LIU XiaoDong

“…Meanwhile,the fault feature vectors are used to train and validate this classification model. The experimental results show that this method not only can improve the classification accuracy on fault diagnosis,but also can optimize the use of sensors by using only one vibration sensor and one pressure sensor to recognize the fault signals.…”
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Error Analysis and Compensation of 3‒PTT Parallel Robot by CHEN Mingfang, LIANG Hongjian, WEI Songpo, HE Chaoyin

“…Then, the improved particle swarm optimization algorithm is utilized to optimize the error correction objective function, where the slider compensation is obtained, and the servo driver is utilized to complete the error compensation. …”
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Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC by Zhihui Wang, Yonghua Zhou, Deng Liu

“…Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. …”
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Landing scheduling for carrier aircraft fleet considering bolting probability and aerial refueling by Genlai Zhang, Lei Wang, Zhilong Deng, Xuanbo Liu, Xichao Su, Haixu Li, Chen Lu, Kai Liu, Xinwei Wang

“…Aiming at an efficient solution, an improved firefly algorithm is designed by integrating multiple evolutionary operators. …”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation Study by João Lopes, Tiago Guimarães, Júlio Duarte, Manuel Santos

“…By implementing these AI-driven strategies, hospitals can minimize patient wait times, maximize resource use, and enhance surgical outcomes through improved planning. This development highlights how AI algorithms can effectively adapt to changing health care environments, having a transformative impact.…”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…The extensive outcome highlighted the improvements of the developed AWRC-DLMLO technique with other existing models.…”
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Optimization Management of Storage Location in Stereoscopic Warehouse by Integrating Genetic Algorithm and Particle Swarm Optimization Algorithm by Shuhong Zhang, Xianghui Zheng, Fan Xu, Suzhen Wang, Qixia Zhang, Yuan Cao

“…At the same time, the study introduced the GA-PSO algorithm to solve the mathematical model and optimize the goods location planning. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Exploring multiple optimization algorithms in transfer learning with EfficientNet models for agricultural insect classification by Hoang-Tu Vo, Nhon Nguyen Thien, Kheo Chau Mui, Huan Lam Le, Phuc Pham Tien

“…This study investigates the impact of multiple optimization algorithms within transfer learning, employing EfficientNet models for the classification of agricultural insects. …”
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Anomaly Detection and Performance Analysis With Exponential Smoothing Model Powered by Genetic Algorithms and Meta Optimization by Ali Kerem Guler, Huseyin Fuat Alsan, Taner Arsan

“…This study employs a genetic algorithm to optimize the parameters of the Third Order Exponential Smoothing model for predicting on the real-time traffic datasets of the Numenta Anomaly Benchmark (NAB). …”
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Application model of “Internet+Marketing service” virtual robot under dung beetle optimizer algorithm by HE Wei, ZHOU Yutian, YU Yang, KANG Yumeng, ZHU Meng, QIAN Xusheng

“…In order to deal with the situation of power marketing service under the new situation and improve the service of power grid in the internet era, a virtual robot model of "Internet+Marketing service" was designed by the dung beetle optimizer (DBO) algorithm. …”
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State-of-the-Art Review: Models and Algorithms for Optimal Power System Design, Stabilization, and Reliability Enhancement by Senele Njabulo Zwane, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…In this study, a state-of-the-art review of models and algorithms for optimal power system design, stabilization, and reliability enhancement is conducted. …”
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Modelling and optimization of well hole cleaning using artificial intelligence techniques by Nageswara Rao Lakkimsetty, Hassan Rashid Ali Al Araimi, G. Kavitha

“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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