Leveraging genetic algorithms and neural networks for stiffness and weight optimisation of an unmanned aerial vehicle (UAV) support arm by Iuri H. Müller, José Humberto S. Almeida Jr, Sandro C. Amico, Maikson L.P. Tonatto

“…The ANN predicts mass and stiffness with over 99% accuracy while reducing computational time by 95% compared to full FE simulations. …”
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Improvement of the TEB Algorithm for Local Path Planning of Car-like Mobile Robots Based on Fuzzy Logic Control by Lei Chen, Rui Liu, Daiyang Jia, Sijing Xian, Guo Ma

“…TEB (timed elastic band) can efficiently generate optimal trajectories that match the motion characteristics of car-like robots. …”
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Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations by Yong Li, Xin Sun, Yongtao Qu, Shuling Yang, Yueyi Zhai, Yan Qu

“…Chi-square and Mann-Whitney U tests examined variables, and multivariate logistic regression determined ONIHL risk factors. Machine learning algorithms like Logistic Regression and Random Forest were developed, optimized, and evaluated. …”
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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…The algorithm employs discrete relaxation, transforming the discrete problem of band selection into a continuous optimization task, which enables gradient-based search across the spectral dimension. …”
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K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers by Herayati Herayati, Andronias Siregar, Hariyanto Hariyanto

“…The results of the first cluster iteration distance calculation consisted of 84 viewers who were very satisfied, while the second cluster consisted of 16 viewers with relatively low satisfaction levels. …”
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What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…We further assessed the training sample size effect to understand the optimal duration of field calibration for achieving good accuracy. …”
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High-fidelity learning-based motion cueing algorithm by bypassing worst-case scenario-based tuning technique by Mohammad Reza Chalak Qazani, Houshyar Asadi, Zoran Najdovski, Shehab Alsanwy, Muhammad Zakarya, Furqan Alam, Hassen M. Ouakad, Chee Peng Lim, Saeid Nahavandi

“…Data samples are regenerated to cover various motion signal levels, and three classical washout filters are tuned to extract optimal motion signals. A multilayer perceptron (MLP) is trained with these extracted datasets, forming an AI-based MCA that provides high-fidelity driving motions for any scenario while optimising the platform workspace. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

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Improved Estimation Procedure of Cage-Induction-Motor-Equivalent Circuit Parameters Based on Two-Stage PSO Algorithm by Jovan Vukašinović, Saša Štatkić, Nebojša Arsić, Nebojša Mitrović, Bojan Perović, Andrijana Jovanović

“…The first approach assumes that the starting rotor leakage reactance is equal to the stator leakage reactance, while the second considers them as distinct. Improvement of the algorithm consists of increasing the accuracy of the approximations of parameter changes on the rotor. …”
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Comparative study of indirect and direct feature extraction algorithms in classifying tea varieties using near-infrared spectroscopy by Xuefan Zhou, Xiaohong Wu, Bin Wu

“…The findings revealed that the classification accuracies of indirect feature extraction algorithms consistently exceeded those of direct feature extraction algorithms, with the former generally surpassing 90.0 %, while the latter remained lower. …”
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Multiple-to-single maximum power point tracking for empowering conventional MPPT algorithms under partial shading conditions by Njimboh Henry Alombah, Ambe Harrison, Wulfran Fendzi Mbasso, Hamid Belghiti, Hilaire Bertrand Fotsin, Pradeep Jangir, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…By eliminating oscillations and hotspot risks through voltage regulation, the framework retains algorithmic simplicity while enhancing performance under complex shading scenarios. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…ObjectiveIn the artificial bee colony (ABC) algorithm, employed bees search the entire search space while onlooker bees concentrate their efforts near high-quality food sources. …”
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Multi-objective optimization of design parameters for tractor hydro-mechanical continuously variable transmissions by Zhen Zhu, Rui Hou, Hongwei Zhang, Dehai Wang, Long Chen

“…In this paper, an independently designed hydro-mechanical CVT transmission is taken as the research object, and the transmission design parameters are optimized based on the tractor’s whole life-cycle speed usage rate, and the Multi-Objective Genetic Algorithm(MOGA) is used for optimization and solution. …”
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Event-Triggered Discrete-Time Distributed Consensus Optimization over Time-Varying Graphs by Qingguo Lü, Huaqing Li

“…Under the assumption that the network topology is uniformly strongly connected and weight-balanced, the novel event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converging to an optimal solution of the convex optimization problem. …”
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Emergency Optimization Decision-Making with Incomplete Probabilistic Information under the Background of COVID-19 by Ming Fu, Lifang Wang, Jiaming Zhu, Bingyun Zheng

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Optimizing Beam Stiffness and Beam Modal Response with Variable Spacing and Extrusion (VaSE) by Patrick N. Murphy, Richard A. Vittum, Bashir Khoda

“…This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. …”
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A New Approach to Circulatory System-Based Optimization for the Shape and Sizing Design of Truss Structures by Ibrahim Behram Ugur, Sadik Ozgur Degertekin

“…This paper presents a new approach to the circulatory system-based optimization algorithm called NCSBO. The proposed method incorporates an adaptive parameter-tuning strategy and a refined mutation approach to improve the performance of optimizing the shape and size of truss structures. …”
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Value chain optimization in large scale gas network considering elevation and transmission direction by Xifeng Ning, Jinfeng Qiu, Dejun Yu

“…Numeric experiments demonstrate the method’s efficiency in generating high-quality solutions for the optimization problem.…”
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Optimizing high-speed train tracking intervals with an improved multi-objective grey wolf by Lin Yue, Meng Wang, Peng Wang, Jinchao Mu

“…The optimized speed profile of the MOGWO algorithm is smoother and more stable and meets the target requirements of energy saving, punctuality and comfort while maximally respecting the speed limit profile. …”
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