Search Results - (( developing feature reduction algorithm ) OR ( java implication tree algorithm ))
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Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks
Published 2018“…Moreover, in term of overall performance for reduction in a number of data transmission reduction EDCD1 algorithm shows the highest ratios. …”
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Optimised content-social based features for fake news detection in social media using text clustering approach
Published 2025“…In addition, this thesis tackles the feature selection problem by designing a novel wrapper feature selection method based on the Hybrid Flower Pollination Algorithm (HFPA). …”
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A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi
Published 2015“…The third layer encompasses a dynamic model creation algorithm, termed Synchronous Targeted Feature Reduction (STFR). …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
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Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone
Published 2022“…In order to overcome these issues, a supervised Deep Neural Network (DNN) algorithm predicted constrained Wiener Filter (cWF) target mask algorithm based on extracted Gammatone filter bank power spectrum (GF-TF) features and trained model is developed. …”
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Dataset size and dimensionality reduction approaches for handwritten farsi digits and characters recognition / Mohammad Amin Shayegan
Published 2015“…Also, the number of features is decreased by proposing a new technique for dimensionality reduction. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The rdemonstrate that ISSA outperforms all baseline algorithms in terms of fitness values, accuracy, convergence curves, and feature reduction in most of the used datasets. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction
Published 2025“…The algorithm’s unique evolutionary mating mechanism with adaptive crossover rate (Cr = 0.85), enabled effective feature space exploration, resulting in a 38.3% reduction in RMSE and 6.0% improvement in R2 compared to models without feature selection. …”
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Investigation and modelling of building energy management system for sustainable energy usage
Published 2024text::Final Year Project -
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification
Published 2020“…Therefore, we conclude that the proposed BFOA-G is the best algorithm in the study, and PG approach is recommended for further development of BFOA as an IS algorithm.…”
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Multinomial logistic regression probability ratio-based feature vectors for Malay vowel recognition
Published 2021“…This study aims to improve MVR performance by proposing an algorithm that transforms MFCC FVs into a new set of features using Multinomial Logistic Regression (MLR) to reduce the dimensionality of the probabilistic features. …”
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Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification
Published 2020“…The wrapper K-Nearest Neighbors (KNN) classifier is used to evaluate the selected features. In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. …”
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An efficient AdaBoost algorithm for enhancing skin cancer detection and classification
Published 2024“…However, accurately distinguishing between skin cancer and benign tumors remains challenging, necessitating the extraction of pertinent features from image data for classification. This study addresses these challenges by employing Principal Component Analysis (PCA), a dimensionality-reduction approach, to extract relevant features from skin images. …”
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…Two different models for learning in data sets were proposed based on two different reduction algorithms. The split-condition-merge-reduct algorithm ( SCMR) was performed on three different modules: partitioning the data set vertically into subsets, applying rough set concepts of reduction to each subset, and merging the reducts of all subsets to form the best reduct. …”
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Fatigue Features Extraction of Road Load Time Data Using the S-Transform
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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