Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression by Stephen M. Akandwanaho, Aderemi O. Adewumi, Ayodele A. Adebiyi

“…The comparisons were performed with Genetic Algorithm and Simulated Annealing. The proposed approach demonstrates superiority in finding good traveling salesman problem (TSP) tour and less computational time in nonstationary conditions.…”
Get full text

Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…Subsequently, the backward reduction algorithm (BRA) is employed to streamline the resulting scenarios into a more feasible and representative subset, therefore mitigating excessive computational effort. …”
Get full text

Improving Model-Based Deep Reinforcement Learning with Learning Degree Networks and Its Application in Robot Control by Guoqing Ma, Zhifu Wang, Xianfeng Yuan, Fengyu Zhou

“…This model’s performance also suffers due to low utilization of training data, while the model-based reinforcement learning (MBRL) algorithm improves the efficiency of the data, MBRL locks into low prediction accuracy. …”
Get full text

Removal mechanism and damage evolution of SiCp/Al composites based on FEM-MD model considering 3D random polyhedral particles in orthogonal cutting by Ming Li, Qingguang Li, Xianchao Pan, Jiaqi Wang, Zixuan Wang, Shengzhi Xu, Yunguang Zhou, Lianjie Ma, Tianbiao Yu

“…Experimental validation confirmed the multi-scale model's predictive accuracy for machining-induced surface damage. …”
Get full text

Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…By employing regression machine learning algorithms, the research evaluates and enhances system performance, achieving remarkable R-squared accuracy levels of 98.86 % for heating output and 99.89 % for power output predictions. …”
Get full text

Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain by Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang, Hongbin Liang, Gang Zhao

“…This algorithm is based on opposition-based learning and its dominant strength. …”
Get full text

SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…The results show significant improvements in energy efficiency (21.6% reduction), throughput (14.5% increase), security strength (15.3% enhancement), latency (33.9% decrease), and packet loss rate (12.9% reduction) compared to state-of-the-art approaches. …”
Get full text

A Method of Intelligent Driving-Style Recognition Using Natural Driving Data by Siyang Zhang, Zherui Zhang, Chi Zhao

“…Finally, a comparative evaluation of SVM, Random Forest, and KNN recognition indicates the superiority of the SVM algorithm and highlights the effectiveness of dimensionality reduction in optimizing characteristic parameters. …”
Get full text

Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

“…Using the heuristic optimization algorithm and entropy-weighted method, the framework achieved average energy savings of 56.62%, a reduction in carbon emissions of 51.60%, and a 24.27% decrease in life-cycle costs. …”
Get full text

Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
Get full text

Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
Get full text

The impact of artificial intelligence on the economic productivity of enterprises by Šović Milena, Brkić Ivana

“…The study examines key AI implementation strategies at Amazon, including algorithmic recommendations, predictive analytics and robotic logistics operations. …”
Get full text

Applicability of machine learning technique in the screening of patients with mild traumatic brain injury. by Miriam Leiko Terabe, Miyoko Massago, Pedro Henrique Iora, Thiago Augusto Hernandes Rocha, João Vitor Perez de Souza, Lily Huo, Mamoru Massago, Dalton Makoto Senda, Elisabete Mitiko Kobayashi, João Ricardo Vissoci, Catherine Ann Staton, Luciano de Andrade

“…Among the tested models, he linear extreme gradient boosting was the best algorithm, with the highest sensitivity (0.70 ± 0.06). …”
Get full text

Path Tracking Control Strategy Based on Adaptive MPC for Intelligent Vehicles by Chenxu Li, Haobin Jiang, Xiaofeng Yang, Qizhi Wei

“…Initially, based on the traditional model predictive control (MPC) theory, the lateral speed stability boundary concerning the vehicle yaw rate is derived to establish the constraint conditions. …”
Get full text

Estimation of the Time of Occurrence of the Maximum Electrical Demand by Selecting the Optimal Classification Model and Making Use of Unbalanced Data by César Aristóteles Yajure, Valesca M. Fuenzalida Sánchez

“…The most important conclusion drawn by the study is that the model obtained with the support vector machine algorithm turned out to be optimal, and successfully predicted the time of maximum demand on 15 of the 17 test days. …”
Get full text

Pinna anthropometry in sex estimation: a machine learning-based approach by Emre Söylemez, Suna Tokgöz Yılmaz

“…We aimed to investigate the feasibility of sex prediction using anthropometric measurements of the pinna in machine learning. …”
Get full text

Preventing Stillbirth: A Review of Screening and Prevention Strategies by Laure Noël, Conrado Milani Coutinho, Basky Thilaganathan, Yiyuan Jiang, Dandan Shi

“…There is currently no equivalent to predict and prevent late-onset placental dysfunction, although algorithms combining an ultrasound-based estimation of fetal weight, assessment of maternal and fetal Doppler indices, and maternal serum biomarkers show promise as emerging new screening tools to optimize pregnancy monitoring and timing of delivery to prevent stillbirth. …”
Get full text

Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions by Elias Dritsas, Maria Trigka

“…While these tools enhance analytical capacity, they raise critical concerns about algorithmic bias, transparency, and ethical accountability. …”
Get full text

Ambulance Siren Detection using Artificial Intelligence in Urban Scenarios by Muhammad Usaid, Muhammad Asif, Tabarka Rajab, Munaf Rashid, Syeda Iqra Hassan

“…With this validated algorithm, researchers can develop a real-time hardware-based model to detect emergency vehicles and make them arrive at the hospital as soon as possible. …”
Get full text

矿用自卸车盘式制动器热固耦合研究 by 解淑英

“…In order to further study the dump truck disc brake thermal-structural coupling characteristics,by analyzing the major impact parameter of brake pressure,brake initial speed,plate/sheet friction coefficient and the equivalent moment of inertia on the disc brake performance and using orthogonal experiment principle,the GA-BP network training sample is formed,a GA-BP network model with traditional genetic algorithm BP neural network combined with the introduction of disc brakes thermal-structural coupling finite element predictive model is proposed.The study results show that for the temperature and stress time history results,the overall trend of the training results and finite element simulation results are basically the same,but in the individual condition curve,there are some differences in local curves.Aiming at the specific conditions,the main characteristics of the temperature-time history is basiclly predicted by the GA-BP Network,the data extreme values of stress time history prediction effect and other major information are consistent with the finite element results.The training network has higher approximation performance and better prediction performance,the maximum error of prediction and simulation is only 8%,the computational accuracy is higher.…”
Get full text