Search Results - (( developing function learning algorithm ) OR ( learning implementation phase algorithm ))

Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics by Zamani, Abu Sarwar, Hassan Abdalla Hashim, Aisha, Shatat, Abdallah Saleh Ali, Akhtar, Md. Mobin, Rizwanullah, Mohammed, Mohamed, Sara Saadeldeen Ibrahim

“…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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Development of an Isolated Digit Speech Recognition Based on Multilayer Perceptron Model by Mohamad Hussin, Ummu Salmah

“…A typical or fixed sigmoid function method is used in learning phase. In the recognition phase, an adaptive sigmoid function is employed. …”
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Unified neural network controller of series active power filter for power quality problems mitigation by Ghazanfarpour, Behzad

“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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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

“…Last but not least, the application can be improved by implementing the machine learning that can help to predict the blood donor behavior and also the timing of the blood shortage.…”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Drone-based surveillance of palm tress ecosystems by Mansor, Ya’akob, Baki, Sharudin Omar, Sahwee, Zulhilmy, Mengyue, Cheng, Wu, Yuanyuan

“…Subsequently, the study proposes a second stage to enhance the accuracy and efficiency of palm tree health detection through the implementation of a deep learning approach using Faster R-CNN, addressing the limitations identified in the initial phase. …”
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Sales prediction for Adha Station by using predictive analytics by Mohd Mokhid, Muhammad Amier Latieff

“…This research presented a technique for projecting sales utilising current data through a machine learning algorithm. The CRISP-DM approach was employed to execute the project across the phases of business understanding, data preparation, modelling, assessment, and deployment. …”
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Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability by Rusdi, Nur ‘Afifah, Zamri, Nur Ezlin, Kasihmuddin, Mohd Shareduwan Mohd, Romli, Nurul Atiqah, Manoharam, Gaeithry, Abdeen, Suad, Mansor, Mohd. Asyraf

“…Additionally, a Hybrid Black Hole Algorithm was proposed in the retrieval phase to optimize the final neuron states. …”
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Terrain awareness mobility model to support outdoor mobility for people with vision impairment by Yousef, Malkawi Abeer Dirar

“…TAM2 contains three main components; user model, terrain detection model, and learning model. For the prototyping phase, the study employed the deep learning detection framework YOLOv4-tiny algorithm to implement a real-time terrain detection model. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

“…Additionally, we evaluated the learning phase, retrieval phase, and similarity analysis using various ratios of literals and clauses. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani by Ghani, Mazuraini

“…This project is all about implementing the back-propagation neural network algorithm in classification of face expression. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy by Leow S.Y., Wong S.Y., Yap K.S., Yap H.J.

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Bipartite graph approach to course timetabling problems / Hafizah A Razak by A Razak, Hafizah

“…The next phase is to design and implement the prototype based on the requirements from phase three. …”
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Web usage mining for UUM learning care using association rules by Ramli, Azizul Azhar

“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis by Mukhlis, Siti Farah Najwa

“…The project is completed by going through the preliminary study phase, data preparation phase, system design and implementation phase, and the evaluation and result analysis phase. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

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