Search Results - (( basic optimization _ algorithm ) OR ( learning implementation based algorithm ))
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1
A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…This work proposes the extreme learning machine (ELM) is one of the poplar machine learning algorithms which, easy to implement with excellent learning performance characteristics. …”
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2
Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…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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Thesis -
3
Web usage mining for UUM learning care using association rules
Published 2004“…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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Thesis -
4
Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation
Published 2000“…This thesis focuses on ways to improve the existing solutions in the algorithmic and implementation aspects. For the algorithmic aspect, the basic principles of motion compensated DCT block-based compression scheme was studied. …”
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5
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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6
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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7
A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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8
Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
10
Basic firefly algorithm for document clustering
Published 2015“…To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents.The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. …”
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11
Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers -
12
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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13
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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Article -
14
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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15
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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16
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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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Implementation of machine learning algorithm in preventing network congestion
Published 2023text::Final Year Project -
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Data Analysis using Particle Swarm Optimization Algorithm
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Final Year Project / Dissertation / Thesis -
20
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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