Kinematic analysis of wire stripping for distribution robots based on wire stripping and cutting force control algorithm under cylindrical gear transmission by Juan Liu, Ziqiang Qiao

“…Meanwhile, the impedance force error curve of the research method was more stable, while the general impedance force error curve fluctuated greatly. …”
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A requirements model for AI algorithms in functional safety-critical systems with an explainable self-enforcing network from a developer perspective by Klüver Christina, Greisbach Anneliesa, Kindermann Michael, Püttmann Bernd

“…This trend is further intensified by the fact that AI-based algorithms are finding their way into safety-related systems or will do so in the future. …”
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Optimizing Pile Bearing Capacity Prediction Using Specific Random Forest Models Optimized by Meta-Heuristic Algorithms for Enhanced Geomechanically Applications by Nengyuan Chen

“…The effective incorporation of meta-heuristic algorithms establishes a strong basis for significantly enhancing the accuracy and effectiveness of PBC estimation. …”
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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…Abstract At present, the internet of things (IoT) plays a vital part in the growth of programmed electrical power stations while presenting magnificent chances, particularly cybersecurity. …”
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Enhancing Customer Segmentation Through Factor Analysis of Mixed Data (FAMD)-Based Approach Using K-Means and Hierarchical Clustering Algorithms by Chukwutem Pinic Ufeli, Mian Usman Sattar, Raza Hasan, Salman Mahmood

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A Novel Algorithm for a Low-Cost, Curvature-Continuous Smooth Path with Multiple Constraints on a Cost-Assigned Flat Map by Xu Du, Lu Yang

“…The method is divided into two stages: In the first stage, the graph structure is constructed by generating points on the map, and uses Dijkstra’s Algorithm to obtain the connection order of the landmark points. …”
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Optimizing Pharmaceutical Inventory and Investment Strategies During Pandemics: A Dynamic Approach Integrating Environmental Emission Rates and Advanced Optimization Algorithms by Vinita Dwivedi, Mamta Keswani, Uttam Kumar Khedlekar, Lalji Kumar

“…Advanced optimization algorithms, including Ant Colony and Cuckoo Search, determine optimal pricing, investment costs, and replenishment schedules. …”
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HiGMA-DADCN: Hirudinaria granulosa multitropic algorithm optimised double attention enabled deep convolutional neural network for psoriasis classification by Soumya C S, Jayanna H S

“…The HiGMA algorithm plays a crucial role in identifying and extracting the most relevant regions of affected skin through optimal segmentation. …”
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Online Core Temperature Estimation for Lithium-Ion Batteries via an Aging-Integrated ECM-1D Coupled Model-Based Algorithm by Yiqi Jia, Lorenzo Brancato, Marco Giglio, Francesco Cadini

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An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date by Pedro Palominos, Mauricio Mazo, Guillermo Fuertes, Miguel Alfaro

“…This study evaluates the efficiency of a swarm intelligence algorithm called marriage in honey-bee optimization (MBO) in solving the single-machine weighted earliness/tardiness problem, a type of NP-hard combinatorial optimization problem. …”
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Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…It was proven  through the experimental results that  the proposed distance measure Weighted Euclidean distance  had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and )  which confirms that (WED) is the best.…”
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A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques by Cong Peng, Cheng Gong, Xiaoya Zhang, Duxian Liu

“…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …”
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Land surface temperature assessment in relation to land-use/land-cover (A case study: Isfahan City, Central Iran) by Sayyad Asghari Saraskanrood, Bahareh Asadi, Ehsan Ghale

“…The results of land-use classification and change detection indicated that urban areas have increased, while agriculture has declined. The results of validation of the three temperature recovery methods demonstrated that due to using two thermal bands simultaneously, the Split-Window method functions better and in these three algorithms, water bodies and wet soils exhibit minimum surface temperatures. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…Existing academic research on China’s urban-rural integration lacks a comprehensive exploration that integrates “factors and pathways” while providing a dynamic depiction of how different driving forces influence the urban-rural integration process. …”
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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…Similarly, RF-DE was evaluated against six popular feature selection algorithms, yielding accuracies of 98.9%, 99.3%, and 99.7%, respectively. …”
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FASTSeg3D: A Fast, Efficient, and Adaptive Ground Filtering Algorithm for 3D Point Clouds in Mobile Sensing Applications by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…Methods: This study proposes FASTSeg3D, a novel two-stage algorithm for real-time ground filtering. First, Range Elevation Estimation (REE) organizes point clouds efficiently while filtering outliers. …”
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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Methodology for Evaluating the Performance of a New Pulse Oximeter Model and Pulse Oximetry Algorithm in Neonates in a Clinical Trial (Exploratory Study) by T. S. Adylov, E. V. Shestak, V. Yu. Starkov

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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…STATA version 17 was used for data cleaning and descriptive statistics, while Python 3.9 was employed for machine learning predictions. …”
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