يعرض 1 - 20 نتائج من 422 نتيجة بحث عن '(((( data boosting algorithm ) OR ( data models algorithm ))) OR ( elements magic algorithm ))', وقت الاستعلام: 0.14s تنقيح النتائج
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    Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology حسب Senyuk, Mihail

    منشور في 2023
    "…This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. …"
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    Boosting the visibility of services in microservice architecture حسب Ahmet Vedat Tokmak (17773479)

    منشور في 2023
    "…We utilized parameter optimization techniques, namely Grid Search, Random Search, Bayes Search, Halvin Grid Search, and Halvin Random Search to fine-tune the hyperparameters of our classifier models. Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…"
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    Predicting Dropouts among a Homogeneous Population using a Data Mining Approach حسب BILQUISE, GHAZALA

    منشور في 2019
    "…Our research relies solely on pre-college and college performance data available in the institutional database. Our research reveals that the Gradient Boosted Trees is a robust algorithm that predicts dropouts with an accuracy of 79.31% and AUC of 88.4% using only pre-enrollment data. …"
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    Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

    منشور في 2024
    "…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …"
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    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

    منشور في 2025
    "…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …"
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    Development of an Optimization Algorithm for Internet Data Traffic حسب Misbahuddin, Syed

    منشور في 2020
    "…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …"
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    Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

    منشور في 2021
    الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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    Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب Odat, Alhaj-Saleh A.

    منشور في 2024
    "…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …"
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    A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

    منشور في 2003
    "…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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    article
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    Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

    منشور في 2024
    "…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

    منشور في 2023
    "…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …"
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    Data mining approach to predict student's selection of program majors حسب SIDDARTHA, SHARMILA

    منشور في 2019
    "…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …"
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