Search Results - (( program implementation tree algorithm ) OR ( learning implementation developing algorithm ))
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1
Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
Conference Paper -
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Lightning fault classification for transmission line using support vector machine
Published 2023“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. …”
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Ensemble deep learning approach for apple fruitlet detection from digital images
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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Thesis -
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A...
Published 2023“…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. …”
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Comparison Of Phylogenetic Trees Using Difference Distance Function Method
Published 2005“…The pre-processing is implemented using the Microsoft Visual C++. The phylogenetic tree is build using the PHYLlP (the PHYlogeny Inference Package), a package of programs for inferring phylogenies (evolutionary trees). …”
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Final Year Project Report / IMRAD -
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…The objective was to identify and implement the most accurate algorithm for the KPTM dataset and to come up with a good prediction model using decision tree technique. …”
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Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
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Mobile machine vision for railway surveillance system using deep learning algorithm
Published 2021“…In this paper, object detection model is developed and implemented with deep learning algorithm. …”
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Proceedings -
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…Additionally, this paper explains comparisons of results between two platforms of rapid software; the proposed software and Python program. The machine learning model in the two platforms were tested on breast cancer and tax avoidance datasets with Decision Tree algorithm. …”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…This research aims to design and develop VR in learning programming algorithms. The ADDIE model is applied in this study to develop products through the stages of analysis, design, development, implementation, and evaluation. …”
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…To our knowledge, there is still no implementation of machine learning models on green building valuation features for building price prediction compared to conventional building development. …”
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IMPLEMENTATION OF IMAGE TEXTURE ANALYSIS USING GRAY LEVEL RUN LENGTH APPROACH
Published 2006“…The objective of this project is to develop algorithms inMATLAB and be able to implement image texture analysis by using the developed algorithms. …”
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Final Year Project
