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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Monograph -
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Book Section -
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Herbs recognition based on chemical properties using machine learning algorithm
Published 2023“…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
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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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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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Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin
Published 2019“…Boundary extraction and corner point detection are basic step for many image processing applications including image enhancement, object detection and pattern recognition. Traditional learning-based boundary extraction algorithms classify each pixel edge separately and then get boundaries from the local decisions of a classifier. …”
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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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Multilevel learning in Kohonen SOM network for classification problems
Published 2006“…Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…Using metrics, this study evaluates Random Forest, ElasticNet, and Decision Tree algorithms. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…Multiple deep-learning models are proposed for segmentation. Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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EEG-based fatigue detection using binary pattern analysis and KNN algorithm
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Proceeding Paper -
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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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Music Recommender System Using Machine Learning Content-Based Filtering Technique
Published 2022“…These algorithms identify hidden patterns or data groupings without the assistance of a human. …”
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Undergraduates Project Papers -
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm
Published 2023“…The primary goal is to use the Random Forest algorithm, an effective machine learning technique, to predict instances of cheating based on the behavioural patterns of participants. …”
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Final Year Project Report / IMRAD -
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches
Published 2024“…Statistical models and machine learning algorithms automatically learn and improve based on data. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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