Search Results - (( pattern classification search algorithm ) OR ( basic optimization path algorithm ))
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1
Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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2
Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The comparison between euler's path and Bipartite graph Algorithm [14] will be made at the end this of this report to see which one give optimal chaining .…”
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3
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 -
4
Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2021“…To solve the redundancy resolution, meta-heuristic optimizations, namely Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA), are applied to search optimal trajectories inside local orientation angle boundaries. …”
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5
Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim
Published 2007“…It makes use of three basic operations in order to optimize this problem. …”
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7
Path planning algorithm for a car like robot based on MILP method
Published 2013“…This project is presents an algorithm for path planning optimal routes mobile robot “like a car” to a target in unknown environment. …”
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8
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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9
Mobile First-Person Shooter (FPS) Game Using Basic Theta* Algorithm / Muhammad Syurahbil Abd Rohaman
Published 2020“…This study shows that Basic Theta* is able to produce the true shortest path compared to A* which produced slightly longer path. …”
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10
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…The aim of data mining is to search and find undetermined patterns in huge databases. …”
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11
Genetic algorithm optimization for coefficient of FFT processor
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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13
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2023“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…The coarser level is used to estimate the position of singular points. The algorithm will only search for singular points in the finer level in a particular region if and only if there is a hit. …”
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15
Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment
Published 2018“…Jump Point Search is one of the path finding algorithm with huge advantage of maintaining zero memory overhead as no preprocessing process involved. …”
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16
Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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A derivative-free optimization method for solving classification problem
Published 2010“…For optimization generalized pattern search method has been applied. The results of numerical experiments allowed us to say the proposed algorithms are effective for solving classification problems at least for databases considered in this study.…”
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18
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…The purpose of choosing parameters is to get the best generalization performance. Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
Conference Paper -
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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