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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Mobile First-Person Shooter (FPS) Game Using Basic Theta* Algorithm / Muhammad Syurahbil Abd Rohaman
Published 2020“…The downside is the computation time on Basic Theta* using grid is way higher compared to A* using NavMesh. …”
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3
Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Computer A will be sent the data to computer B through the internet/LAN using JAVA program. …”
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Monograph -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Monograph -
8
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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9
A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences
Published 2008“…The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. …”
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Article -
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CSC099: Foundation Computing II / Centre of Foundation Studies
Published 2022“…This course introduces basic computer programming algorithm, problem solving, structured programming language, selection structure, repetition structure, function and array. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…Using a proper test-bed, after 10000 run times, we compared our newly proposed algorithm with the basic algorithm in terms of reliability and availability. …”
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CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences
Published 2023“…This course is an introduction to problem solving using a computer programming language. It emphasizes on algorithm development and writing computer programs, as well as common good practices in writing programs. …”
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Travelling Salesman Problem using Prim Algorithm in High Performance Computing
Published 2007“…This preliminary report emphasizes on the basic terms of the efficient job scheduling algorithm for traveling salesman problem in high performance computing. …”
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Final Year Project -
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Examination timetabling using genetic algorithm case study: KUiTTHO
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Adaptive routing algorithms and implementation for TESH network
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Computing the autopilot control algorithm using predictive functional control for unstable model
Published 2009“…One basic Ballistic Missile model (10) is used as an unstable model to formulate the control law algorithm using PFC. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
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19
AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
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