Showing 1 - 20 results of 98 for search 'feature optimization algorithm', query time: 0.07s Refine Results
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    Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

    Published 2023
    “…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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    Arithmetic optimization algorithm: a review and analysis by Abualigah, Laith

    Published 2024
    “…As a result, it can perform diverse optimization tasks in different search spaces. This article reviews the behaviors of mathematics operations that inspire the main features of AOA, which is a metaheuristic algorithm. …”
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    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

    Published 2019
    “…A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. Lastly, the emotion of each subject is represented using the histogram of the vocabulary set collected from the raw-feature of a single channel. …”
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    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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    An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

    Published 2024
    “…To assess the efficacy of the I-GKSO, it has been subjected to comparisons with multiple different algorithms. The trials conducted using FS datasets yield a quantitative consideration of the I-GKSO's capacity to attain the most optimal subset of features. …”
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    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. …”
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    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 1992
    “…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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    masterThesis
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    StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

    Published 2024
    “…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”
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    Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations by Mansour, Nashat

    Published 1992
    “…Three optimization methods derived from natural sciences are considered for allocating data to multicomputer nodes. …”
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    article
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    A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text by M. Ghoniem , Rania

    Published 2019
    “…Second, a hybrid genetic-whale optimization algorithm was proposed to optimize ontology learning from Arabic text. …”
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    Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

    Published 2023
    “…The picture histogram was used to construct the candidate solutions in the modified algorithms, which were then updated according to the algorithm's features. …”
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    Multi-Classifier Tree With Transient Features for Drift Compensation in Electronic Nose by Atiq Ur Rehman (8843024)

    Published 2020
    “…In this paper, these two problems of `sensors long term drift' and `delayed response' are solved simultaneously to propose a robust and fast electronic nose system, with following merits: (i) only initial transient state features are used in the proposed system without waiting for the sensors to reach a steady state, (ii) a modified boxplot approach is used to handle noisy/drifted data points as a preprocessing step before the classification setup, (iii) a heuristic tree classification approach with optimized transient features is proposed, (iv) the proposed approach only relies on adapted ML methods contrary to the traditional approaches like system recalibration or sensors replacement for handling sensors drift, and (v) the proposed ML model does not require any target domain data and uses only the source domain data for learning the classifier, opposed to the other ML solutions available in the existing literature. …”