Urban Microcirculation Traffic Network Planning Method Based on Fast Search Random Tree Algorithm by Ning YU

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NIRS identification of cashmere and wool fibers based on spare representation and improved AdaBoost algorithm by Zhu Yaolin, Li Zheng, Chen Xin, Chen Jinni, Zhang Hongsong

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Automated guided vehicle (AGV) path optimization method based on improved rapidly-exploring random trees by Zhigang Ren, Anjiang Cai, Feilong Xu

“…In response to the issues of low computational efficiency, slow convergence speed, curvy paths, and the tendency to fall into local optima in rapidly-exploring random tree (RRT) algorithms for automated guided vehicle (AGV) path planning, this article proposes an improved RRT algorithm that combines adaptive step-size optimization with K-dimensional tree (KD-Tree) based fast nearest neighbor search. …”
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Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. …”
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Machine learning classification algorithm screening for the main controlling factors of heavy oil CO2 huff and puff by Peng-xiang Diwu, Beichen Zhao, Hangxiangpan Wang, Chao Wen, Siwei Nie, Wenjing Wei, A-qiao Li, Jingjie Xu, Fengyuan Zhang

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Network Congestion Tracking and Detection in Banking Industry Using Machine Learning Models by Kingsley Ifeanyi Chibueze, Nwamaka Georgenia Ezeji, Nnenna Harmony Nwobodo-Nzeribe

“…It addresses the challenge of congestion management through machine learning (ML) models, aiming to enhance network performance and service quality. This research evaluates various ML algorithms, including Support Vector Machines, Decision Trees, and Random Forests, to identify the most effective approach for congestion detection. …”
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Landscape dynamics and its related factors in the Citarum River Basin: a comparison of three algorithms with multivariate analysis by Moh. Dede, Sunardi Sunardi, Kuok-Choy Lam, Susanti Withaningsih, Hendarmawan Hendarmawan, Teguh Husodo

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Research on vehicle scheduling for forest fires in the northern Greater Khingan Mountains by Jie Zhang, Junnan He, Shihao Ren, Pei Zhou, Jun Guo, Mingyue Song

“…Improvement of ordinary genetic algorithm, design of double population strategy selection operation, the introduction of chaotic search initialization population, to improve the algorithm’s solution efficiency and accuracy, through the northern pristine forest area of Daxing’anling real forest fire cases and generation of large-scale random fire point simulation experimental test to verify the effectiveness of the algorithm, to ensure that the effectiveness and reasonableness of the solution to the problem of forest fire emergency rescue vehicle scheduling program. …”
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Smart Chaining: Templing and Temple Search by Rajeev Ranjan Kumar Tripathi, Rahul Mishra, Shailesh Kumar Agrahari, Pradeep Kumar Singh, Sarvpal Singh

“…Experimental evidence illustrates the dominance of Templing and Temple Search as it delivers <inline-formula> <tex-math notation="LaTeX">$4.5x$ </tex-math></inline-formula> faster searches and <inline-formula> <tex-math notation="LaTeX">$3.5x$ </tex-math></inline-formula> faster insertions over plain chaining at equal space complexity. …”
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Integrating Machine Learning Techniques and the Theory of Planned Behavior to Assess the Drivers of and Barriers to the Use of Generative Artificial Intelligence: Evidence in Spain by Antonio Pérez-Portabella, Jorge de Andrés-Sánchez, Mario Arias-Oliva, Mar Souto-Romero

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Machine Learning-Based Approaches and Comparisons for Estimating Missing Meteorological Data and Determining the Optimum Data Set in Nuclear Energy Applications by Fatih Topaloglu

“…The first motivation of the study was to define the estimation of missing data in the meteorological data set and its usability in the nuclear energy industry by using Machine Learning (ML)-based Linear Regression (LR), Decision Trees (DT) and Random Forest (RF) algorithms. Its second motivation is to determine the optimum set/number of meteorological data required for nuclear energy projects using the best-performing ML algorithm. …”
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Development of a prediction model for acute respiratory distress syndrome in ICU patients with acute pancreatitis based on machine learning algorithms by REN Xia*，LIU Luojie，ZHA Junjie，YE Ye，XU Xiaodan，YE Hongwei，ZHANG Yan

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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review by Xiaojian Gai, Chang Xu, Yajia Liu, Qingchun Feng, Shubo Wang

“…This paper summarizes the key technologies used in current research, including heuristic algorithms, fast search rapidly exploring random trees, reinforcement learning algorithms, etc., and focuses on reviewing the present applications of cutting-edge reinforcement learning algorithms in agricultural robotic arms. …”
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Streamlining ICI Transformed as a Nonnegative System by David Hyland

“…The previous algorithm used initial conditions that were randomly assorted pixel intensities. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Illustration Design Model with Clustering Optimization Genetic Algorithm by Jing Liu, Qixing Chen, Xiaoying Tian

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Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

“…This research article mainly proposed an extension of the Random Forest classifier named “Weighted Random Forests” (wRF), which incorporates tree-level weights to provide much more accurate trees throughout the calculation as well as an assessment of vector relevance. …”
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Path Planning Algorithm for Manipulators in Complex Scenes Based on Improved RRT* by Xiqing Zhang, Pengyu Wang, Yongrui Guo, Qianqian Han, Kuoran Zhang

“…Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning method (abbreviated as HP-APF-RRT*) is proposed. …”
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Routing algorithm for heterogeneous computing force requests based on computing first network by ZHANG Gang, LI Xi

“…An optimized genetic algorithm to address this issue was proposed. This algorithm was designed from both local and global perspectives: to ensure fast convergence to the target solution locally, a single parameter satisfying the randomness strategy was used to initialize the population, making it widely dispersed in the solution space; adopting a multi-parameter solution (or path) balanced selection strategy for selection operations, making the selected population rich and diverse; adopting a two-layer crossover strategy for crossover operations, with the aim of expanding the breadth of global search; adopting a multi parameter random single point mutation strategy for mutation operations, with the aim of deepening local search capabilities. …”
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