Search Results - (((( between learning algorithm ) OR ( pattern means algorithm ))) OR ( patterns path algorithm ))
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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Thesis -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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Undergraduates Project Papers -
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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10
Characterization of oil palm fruitlets using artificial neural network
Published 2014“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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11
Walking gait event detection based on electromyography signals using artificial neural network
Published 2019“…The mean absolute different values between artificial neural network and footswitch data for learned data were 16 ± 18 ms and 21 ± 18 ms for heel strike and toe off, respectively. …”
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MELODY TRAINING WITH SEGMENT-BASED TILT CONTOUR FOR QURANIC TARANNUM
Published 2021“…To identify similarity between a pair of verse-contours, the application employs a shape-based contour similarity algorithm. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Therefore, the present study aims: (1) to improve Indonesian text summary by enhancing the Sequence of Word (SoW) as text representation using Sequential Pattern Mining (SPM) with PrefixSpan algorithm since the effectiveness of SPM in Indonesian is proven useful for text classification and clustering; (2) to combine SPM and Deep Learning (DeepSPM) in text summarization with Indonesian text, as a result of its superior accuracy when trained with large amounts of data; and (3) to evaluate the readability of Indonesian text summary with several evaluation scenarios. …”
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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region
Published 2024“…Secondly, the research systematically assesses the effectiveness of different algorithms to identify the most precise method for establishing any potential relationship between field-measured AGB and predictor variables. …”
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Machine Learning Based Detection for Compromised Accounts on Social Media Networks
Published 2025“…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki
Published 2014“…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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Thesis -
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Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms
Published 2022“…In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. …”
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An automated learner for extracting new ontology relations
Published 2013“…Also we present a novel approach of learning based on the best lexical patterns extracted, besides two new algorithms the CIA and PS that provide the final set of rules for mining causation to enrich ontologies.…”
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Mean of correlation method for optimization of affective states detection in children
Published 2018“…The cues from the first order statistics are computed in the identified blood flow region and concatenated along with second order statistics cues, in order to construct feature vectors to administer the vital and distinguishable characteristic pattern between affective states in thermal images. Result from the fine k-NN classifier obtained promises the efficacy of the proposed approach to be applied in our future work in human–robot interaction for autistic children learning and training.…”
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Exploring students' performance in mathematics in Portugal using data analytics techniques: a data science use-case
Published 2024“…The purpose is to identify the key factors influencing academic performance, providing insights for targeted interventions and support systems. Machine learning algorithms, specifically Random Forest Regression and Decision Trees, are utilized to analyze the dataset and determine the most significant factor impacting student performance. …”
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