Search Results - (( java implementation path algorithm ) OR ( programming capability selection algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun
Published 2000“…This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Besides DEA, Evolutionary Programming (EP), Firefly Algorithm (FA) and Cuckoo Search Algorithm (CS) were also incorporated in the sizing algorithm for performance comparison. …”
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11
Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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12
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim
Published 2006“…Pattern recognition techniques are used to automatically classify a variety of physical objects or abstract patterns. The capability of powerful personal computers and affordable and high resolution sensors (i.e.: CCD cameras, microphones and scanners) have fostered the development of pattern recognition algorithms in new application domains (i.e.: fuzzy logic, neural network and genetic algorithm). …”
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Research Reports -
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Optimizing Ram Testing Method For Test Time Saving Using Automatic Test Equipment
Published 2017“…A memory Build-in Self-test (BIST) design with capability of algorithm failing sequence capture have been developed to implement in the Automate Test Equipment (ATE) flow for production screen. 3 selected algorithm have been tested on the 8 detect units in ATE flow to prove the concept of this method. …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…The main objective of this research is to develop a computer program with capability of manipulating the onlooker bee approaches in ABC Algorithm for solving flowshop scheduling problem. …”
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Cognitive selection mechanism performance in IEEE 802.11 WLAN
Published 2013“…The results for the selection were evaluated respectively to see the variation in selection pattern when compared to the default selection algorithm. …”
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman
Published 2021“…Subsequently, the CI-based sizing algorithm, known as Evolutionary-Dolphin Echolocation Programming Sizing Algorithm (EDEPSA) is formulated to determine the optimal models of each system component such that either Performance Ratio (PR) or Levelized Cost of Electricity (LCOE) of the system is optimized. …”
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Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Research Reports -
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems. …”
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A New Mobile Botnet Classification based on Permission and API Calls
Published 2024“…As a result, 16 permissions and 31 API calls that are most related with mobile botnet have been extracted using feature selection and later classified and tested using machine learning algorithms. …”
Proceedings Paper
