Search Results - (( developing function learning algorithm ) OR ( model application testing algorithm ))

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Chaos search in fourire amplitude sensitivity test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Chaos Search in Fourier Amplitude Sensitivity Test by Koda, Masato

“…This paper explores the characterization of learning functions involved in FAST and derives the underlying dynamical relationships with chaos search, which can provide new learning algorithms. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm by Lipu M.S.H., Ayob A., Saad M.H.M., Hussain A., Hannan M.A., Faisal M.

An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

“…The work is further extended to developing and integrating the idea of active control of flexible structures into an interactive learning environment. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali by Mohd Adli , Md Ali

“…Thus, development of an SOM algorithm for high energy physics datasets was performed. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Sentiment Analysis on COVID-19 Vaccine Tweets using Machine Learning and Deep Learning Algorithms by Tarun Jain, Tarun Jain, Vivek Kumar Verma, Vivek Kumar Verma, Akhilesh Kumar Sharma, Akhilesh Kumar Sharma, Bhavna Saini, Bhavna Saini, Nishant Purohit, Nishant Purohit, Bhavika, Bhavika, Hairulnizam Mahdin, Hairulnizam Mahdin, Masitah Ahmad, Masitah Ahmad, Rozanawati Darman, Rozanawati Darman, Su-Cheng Haw, Su-Cheng Haw, Shazlyn Milleana Shaharudin, Shazlyn Milleana Shaharudin, Mohammad Syafwan Arshad, Mohammad Syafwan Arshad

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Mobile application for blood donation using geolocation and rule-based algorithm / Muhammad Firzan Azrai Nuzilan and Mohd Ali Mohd Isa by Nuzilan, Muhammad Firzan Azrai, Mohd Isa, Mohd Ali

“…Iterative Waterfall model that consisting of requirement analysis, design, system development, testing, and documentation helped the process of developing the application effectively because it consists of step by step process. …”
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah by Abdullah, Nur Raudzah

“…Deep learning technique can also be used for more accurate prediction model.…”
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E-Handrawn Calculator by Mohamad, Syamimi

“…The purpose of this project is to demonstrate an application of back-propagation network (comparison of training their algorithms and transfer function) in order to developing e-Hand-Drawn Calculator. …”
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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil by Idris, Siti Aishah, Ahmad Fadzil, Ahmad Firdaus

“…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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Application of deep learning technique to predict downhole pressure differential in eccentric annulus of ultra-deep well by Krishna, S., Ridha, S., Ilyas, S.U., Campbell, S., Bhan, U., Bataee, M.

“…The data generated from this model, field data, and experimental data are used to train and test the FFBP-DNN networks. The network is developed used Kerasâ��s deep learning framework. After testing the models, the most optimal arrangement of FFBP-DNN is the ReLU algorithm as an activation function, 4-hidden layers, the learning rate of 0.003, and 2300 of training numbers. …”
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Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

“…Before this stage, the KNN algorithm is employed to construct the model using Google Form response data as part of the application development process. …”
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A Comprehensive Study On Developing Neural Network Models For Predicting The Coagulant Dosage And Treated Water Qualities For A Water Treatment Plant by Jayaweera, Chamanthi Denisha

“…In this work, three different neural network models, namely, the general regression neural network (GRNN), extreme learning machine single layer feed forward neural network (ELM-SLFN) and the extreme learning machine radial basis function neural network (ELM-RBF) were developed to predict the coagulant dosage, and their performances were compared with the commonly used multilayer perceptron neural network (MLP). …”
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Spear- phishing attack detection using artificial intelligence by Rajkumaradevan, Sanglidevan

“…Both applications underwent thorough functional, performance, and accuracy testing. …”
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Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

“…This research aims to develop an improved model for subspace clustering based on density connection. …”
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