Search Results - (( evolution classification problem algorithm ) OR ( program implementation path algorithm ))
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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Thesis -
2
Vision-based robot indoor navigation
Published 2022“…A navigation robot is built to test the workability and efficiency of the algorithms. In general, the algorithm can provide the nearest path to navigate around the environment without manual assistance. …”
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Final Year Project / Dissertation / Thesis -
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Implementation of Autonomous Vehicle Navigation Algorithms Using Event-Driven Programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This algorithm has been tested and implemented successfully via a dual beam optical scanning system.…”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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6
Implementation of an autonomous mobile robot navigation algorithm using C language
Published 2009“…The problem can basically be divided into positioning and path planning. This report basically discusses the study and also work that has been done from previous of the chosen topic, which is Implementation of an Autonomous Mobile Robot Navigation Algorithm using 'C' language. …”
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Final Year Project -
7
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Article -
8
Implementation of autonomous vehicle navigation algorithms using event-driven programming
Published 2012“…By using FSM to describe the behaviour of a navigating mobile robot, an equivalent algorithm can be developed. The algorithm can be relatively easy translated to a suitable program with event-driven programming technique. …”
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9
GPS boundary navigation of DrosoBots using MATLAB simulation
Published 2010“…To implement this, region recognition and several path planning algorithms have been utilized. …”
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Proceeding Paper -
10
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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An improved algorithm in test case generation from UML activity diagram using activity path
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13
Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems. The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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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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17
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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19
Development of obstacle avoidance technique in web-based geographic information system for traffic management using open source software
Published 2014“…Pg Routing as an extension of Postgre SQL/Post GIS database is an open source library that implements the Dijkstra shortest path algorithm. However, the functionality to avoid obstacles in that analysis is still limited. …”
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Development of Path Loss Models for Smooth and Convex Surfaces Terrains in Malaysian Environment
Published 2004“…This program consists of four algorithms which are conversion formulas, smooth terrain, single convex surface terrain and double convex surfaces terrain.…”
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