Search Results - (( java application optimisation algorithm ) OR ( pattern identification learning algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…The data was trained against 6 machine learning algorithms namely Decision Tree, Logistic Regression, Naive Bayes, Random Forest, Neural Networks and KNN. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms by Anuar N.K., Bakar A.A., Ahmad A.R., Yussof S., Rahim F.A., Ramli R., Ismail R.

Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

“…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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Personal identification by Keystroke Pattern for login security by Abdullah, Norhayati

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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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Early Detection Of ADHD Among Children Using Machine Learning by Nur Atiqah, Kamal

“…Machine learning algorithms can analyze fMRI data and identify biomarkers indicative of ADHD, enabling accurate classification. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida by Nanyonga , Aziida

“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network by Asirvadam , Vijanth Sagayan, McLoone, Sean

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APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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Advancing machine learning for identifying cardiovascular disease via granular computing by Ku Muhammad Naim, Ku Khalif, Noryanti, Muhammad, Mohd Khairul Bazli, Mohd Aziz, Mohammad Isa, Irawan, Mohammad Iqbal, ., Muhammad Nanda, Setiawan

“…Early-stage cardiovascular illness can benefit from machine learning models in drug selection. The integration of granular computing, specifically z-numbers, with machine learning algorithms, is suggested for CVD identification. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

“…Further enhancements might involve including machine learning algorithms to improve the prototype's accuracy by learning from a larger dataset, which would eventually improve the prototype's ability to offer deep understanding into handwriting patterns related to dyslexia.…”
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DNA enhancer prediction using machine learning techniques with novel feature representation by Fong, Pui Kwan

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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…The existing CNN based approaches can only capture the similar region-wise patterns within an image but not the structural patterns of a plant composed of varying number of plant views images composed of one or more organs. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Feature selection for Malaysian medicinal plant leaf shape identification and classification by Sainin, Mohd Shamrie, Alfred, Rayner

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Preserving the topology of self-organizing maps for data analysis: A review by Bariah, Yusob, Zuriani, Mustaffa, Siti Mariyam, Shamsuddin

“…This paper presents detail explanation on SOM learning algorithm and its applications. Some issues related to SOM's architecture are also discussed, namely the formulation of training data from input samples, and the Best Matching Unit (BMU) identification for better visualization of large datasets, and improvement made to the SOM algorithm.…”
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Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

“…Multilevel Perception neural network utilizes the back-propagation learning algorithm is suitable to discover relationships and patterns in the dataset. …”
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