Search Results - (( developing learning process algorithm ) OR ( data visualization learning algorithm ))
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…An Intelligent Learning System for the turning process was developed. …”
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2
Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…In order to develop an intelligent agent, various programming techniques are used in achieving the property of self learning, information retrieval and searching algorithm. …”
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3
Stock price monitoring system
Published 2024“…As stock price is time series data, a time series prediction algorithm is being utilized to build a deep learning model, namely Long Short-Term Memory (LSTM). …”
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Assessment of crops healthiness via deep learning approach: Python / Mohamad Amirul Asyraf Mohd Ramli
Published 2023“…By leveraging image processing techniques, statistical analysis and machine learning algorithms, Python enables the extraction of relevant features and patterns from data. …”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Unsupervised machine learning algorithm K-means was used to cluster the data, and these results were analyzed and labeled with labels and descriptions. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Data from an academic institution were collected and pre-processed by encoding relevant features before applying various machine learning predictive models. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves
Published 2024“…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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Vehicle Detection in Deep Learning
Published 2019“…The objective of this project is vehicle detection with deep learning, so, vehicles data set from highway, urban road and housing area had been collected and applied to the deep learning and computer vision algorithms. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…This study proposed an integrated system for EEG signals pre-processing by using machine learning algorithms in the identification of artifactual components during the process of Wavelet-ICA. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…Using a dataset from Kaggle comprising 13 attributes and 5000 rows of bank customer data, the research addresses the challenge of processing overwhelming customer information by leveraging machine learning models. …”
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Low-light image analysis and contrast enhancement using gaussian process / Loh Yuen Peng
Published 2018“…The second contribution is an in-depth analysis of the collected data, specifically, by studying the global and local pixel intensities, followed by the performance and visualizations of hand-crafted and learned features. …”
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
Published 2025“…In the development phase, Convolutional Neural Network model was designed and trained using sophisticated techniques of data augmentation, dropping out and hyperparameter tuning under the supervised learning methodology to increase the performance of the system. …”
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13
Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization
Published 2023“…Data from an academic institution were collected and pre-processed by encoding relevant features before applying various machine learning predictive models. …”
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Cabbage disease detection system using k-NN algorithm
Published 2022“…Plant disease study means the study of disease patterns that can be visually seen on plants. The main objective of this research is to develop a prototype system with the help of machine learning to detect cabbage diseases which are Alternaria Leaf Spot disease, Mosaic Virus disease, Downy Fungus disease, Bacterial Soft Rot disease, and Black Rot disease . …”
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Academic Exercise -
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…A critical step in developing such intelligent systems is the feature extraction process. …”
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins
Published 2024“…To forecast unexpected flood occurrences, faster flood prediction necessitates computational prediction models such as Machine Learning (ML) algorithms, which are extensively utilized around the world. …”
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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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Sentiment analysis of customer review for Tina Arena Beauty
Published 2025“…Three machine learning algorithms Naive Bayes, Random Forest, and Support Vector Machine (SVM) were evaluated, and SVM achieved the highest accuracy and was selected as the final classifier. …”
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Sentiment analysis of customer reviews for Konda Kondi Cafe & Bistro
Published 2025“…Machine learning algorithms such as Support Vector Machine (SVM), Naive Bayes (NB), and Decision Tree (DT) were applied using RapidMiner to build classification models. …”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics
Published 2023“…This analysis involved the implementation of machine learning (ML) algorithms, including decision trees, random forests, and stacking, to classify soybean FLS severity levels. …”
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