Search Results - (( data optimization _ algorithm ) OR ( framework implementation learning algorithm ))
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1
Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Finally, the last experiment involves creating the complete optimized multilayered ensemble framework and implementation of the framework to find the suitable combination of methods in each layer to produce satisfactory sentiment analysis accuracy. …”
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Thesis -
2
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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3
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…An efficient iterative algorithm is developed to optimize the objective function of the proposed algorithm since it is non-smooth and difficult to solve. …”
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4
Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Article -
5
Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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6
Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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7
The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning
Published 2025“…Skyline technique relies on the concept of Pareto-optimal in which a data item from the set of dataset D is identified as skyline if and only if it is not worse than other data items in all dimensions (attributes) and strictly better in at least one dimension. …”
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Proceeding Paper -
8
Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification
Published 2023“…In this paper, we proposed a Constrained-Optimization-based ELM network structure implementing Bayesian framework in its hidden layer for learning and inference in a general form (denoted as C-BPP-ELM). …”
Conference Paper -
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics
Published 2024“…In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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Article -
11
A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The proposed project achieves overall accuracy level of 96.67% using Sequential Minimal Optimization classifier.…”
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Final Year Project Report / IMRAD -
12
Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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13
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. In the second stage, the model is fine-tuned or re-trained using labeled data with supervised learning. …”
text::Thesis -
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DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS
Published 2011“…The encoding and optimization process using genetic algorithms has been applied successfully. …”
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15
Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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16
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
17
Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…This study presents a post-pandemic machine learning-based analytical framework specifically designed for Malaysia’s ecommerce market. …”
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19
UiTM research supervisor recommendation system / Ahmad Adam Ahmad Muzzlini
Published 2022“…In terms of future work, an implementation of collaborative filtering can be used to learn data from past recommendation of users but would need a large dataset of users to work properly.…”
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20
A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis
Published 2014“…The use of feature selection as one of the important machine learning task is often disregarded in Writer Identification domain, with only a handful of studies implemented feature selection phase. …”
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