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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour
Published 2022“…With a combination of Naive Bayes and k-NN algorithms, the accuracy value is increasing to 86%. …”
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Proceeding Paper -
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An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique
Published 2021“…The valuate of performance HDDETS algorithm comparison to existing hybrid-based algorithms, namely: Biogeography-Based Optimization Tabu Search (BBOTS), Whale Algorithm with Tabu Search (WAITS), Hybrid Ant System (HAS), Lexisearch and Genetic Algorithms (LSGA), and Golden Ball Simulated Annealing (GBSA) algorithms. …”
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Thesis -
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Conference or Workshop Item -
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Article -
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The adaptability of Industrial Revolution 4.0 technology in valuation field / Asmida Shafina Osman
Published 2023“…The study reveals that the majority of valuers have embraced IR4.0 technologies, finding them beneficial for simplifying work processes and making informed decisions. Drones and GIS systems have been utilized for property inspections and site analysis, while Al and ML algorithms have automated data analysis, leading to improved decision-making. …”
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Thesis -
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The adaptability of Industrial Revolution 4.0 in valuation field / Asmida Shafina Osman and Nor Azalina Yusnita Abdul Rahman
Published 2023“…The study reveals that the majority of valuers have embraced IR4.0 technologies, finding them beneficial for simplifying work processes and making informed decisions. Drones and GIS systems have been utilized for property inspections and site analysis, while AI and ML algorithms have automated data analysis, leading to improved decision-making. …”
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Conference or Workshop Item -
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Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
Published 2016“…In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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Article -
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Evaluation of boruta algorithm in DDoS detection
Published 2023“…As traffic grows over time, detecting a Distributed Denial of Service (DDoS) assault is a challenging task. …”
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A comprehensive fault location estimation using voltage sag profile for non-homogenous distribution networks
Published 2010“…In line with this objective, a fault location method for a distribution network is proposed in this paper. …”
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Article -
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…The DE is integrated with CS at the population initialization by distributing the population linearly. This linear distribution gives the population a unique, stable, and progressive distribution process. …”
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Thesis -
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Analyzing customer reviews for ARBA Travel using sentiment analysis
Published 2025“…The project entails gathering a dataset of customer reviews from Google Reviews and Facebook, cleaning the text to eliminate any noise, and analyzing sentiments using three machine learning algorithms; Naive Bayes, Support Vector Machine, and Logistic Regression. …”
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Student Project -
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules
Published 2023“…The accuracy value shows that the KNN algorithm is better when compared to the Naïve Bayes algorithm. …”
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Thesis -
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Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
Published 2013“…Property valuation is an area of interest for property owners, real estate agents, government bodies and researchers. …”
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Thesis -
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Spatial analysis of infant mortality in Peninsular Malaysia over three decades using mixture models
Published 2013“…Bayes theorem was used to determine the probability of belonging to each district in every components of the mixture distribution. …”
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Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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UMK Etheses -
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Mitigating imbalanced classification problems in academic performance with resampling methods / A’zraa Afhzan Ab Rahim and Norlida Buniyamin
Published 2023“…This can create problems when predicting academic performance using machine learning algorithms, which assume that the datasets have a balanced distribution across all classes. …”
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