Showing 1 - 20 results of 91 for search 'collected control set algorithm', query time: 0.12s Refine Results
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    Predicting Financial Distress through Ranking Working Capital Management Components Using Random Forest Algorithm by Pouya Sadeghi, Daryush Farid, Hamid Reza Mirzaei, Abolfazl Dehghani

    Published 2025-03-01
    “…Subsequently, the predictive power of 7 key working capital management components in forecasting financial distress was tested using Python software and the random forest algorithm.The random forest method is based on ensemble learning, wherein the data are split into training and testing sets. …”
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    Mission Re-Planning of Reusable Launch Vehicles Under Throttling Fault in the Recovery Flight Based on Controllable Set Analysis and a Deep Neural Network by Keshu Li, Wanqing Zhang, Han Yuan, Jing Zhou, Ying Ma

    Published 2025-02-01
    “…To quantify the influence of throttling capability, the concept of “controllable set (CS)” is introduced. The CS is defined as the collection of all feasible initial states that can achieve a successful powered landing and is computed using polyhedron approximation and convex optimization. …”
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    Walking detection for Parkinson’s disease patients and healthy control subjects measured with a smartphone accelerometer using mean amplitude deviation algorithm by Milla Juutinen, Jari Ruokolainen, Juha Puustinen, Anu Holm, Mark van Gils, Antti Vehkaoja

    Published 2025-05-01
    “…The sensitivity of the algorithm in a controlled measurement setting was 100% and 98.7% for healthy adults and a combined dataset of Parkinson’s disease patients and control subjects, respectively. …”
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    An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

    Published 2025-04-01
    “…An optimal machine learning algorithm was developed by training it with 10 machine learning algorithms and the block data collected in the field. …”
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    Application of the spectral bisection algorithm for the analysis of criminal communities in social networks by K. M. Bondar, V. S. Dunin, P. B. Skripko, N. S. Khokhlov

    Published 2024-07-01
    “…Experimental evaluations of the algorithm showed its positive capabilities as part of a set of tools for researching social networks. …”
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    Regression Test Suite Minimization Using Modified Artificial Ecosystem Optimization Algorithm by Abhishek Singh Verma, Ankur Choudhary, Shailesh Tiwari

    Published 2021-01-01
    “…To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. …”
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    Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms by Shikha Sharda, Sumit Kumar, Raj Setia, Prince Dhiman, N. R. Patel, Brijendra Pateriya, Ali Salem, Ahmed Elbeltagi

    Published 2025-07-01
    “…This study presented a systematic approach for detecting the wheat lodging occurred during the end of March and April 2023 in the Ludhiana district of Punjab (India) from multi-temporal Sentinel-2 data using the machine learning algorithms. The ground control points for healthy and lodged areas were collected during March and April 2023. …”
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    Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

    Published 2025-12-01
    “…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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    A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

    Published 2024-08-01
    “…Results from simulations conducted in environments set up using Matlab showed that in the task training of train operation on long steep downhill with randomly generated entry speeds, cumulative rewards gradually converged over training runs, which verified the convergence and generalization of the proposed algorithm. …”
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