بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
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Development of an Optimization Algorithm for Internet Data Traffic
منشور في 2020"…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …"
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
منشور في 2024"…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …"
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
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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Practical single node failure recovery using fractional repetition codes in data centers
منشور في 2016"…FR codes consist of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …"
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conferenceObject -
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
منشور في 2019الموضوعات: احصل على النص الكامل
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory
منشور في 2025الموضوعات: -
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models
منشور في 2010"…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…"
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
منشور في 2023"…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …"
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Recent Advances of Chimp Optimization Algorithm: Variants and Applications
منشور في 2023"…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …"
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Efficient Approximate Conformance Checking Using Trie Data Structures
منشور في 2021الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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احصل على النص الكامل
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FarmTech: Regulating the use of digital technologies in the agricultural sector
منشور في 2023"…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …"
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Oversampling techniques for imbalanced data in regression
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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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
منشور في 2022"…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"
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