Search Results - (( using function path algorithm ) OR ( pattern classification colony algorithm ))
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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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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…The performance of the HPABC algorithm was investigated on four benchmark pattern-classification datasets and the results were compared with other algorithms. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…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 may be done experimentally through time consuming human experience.To overcome this difficulty, an approach such as Ant Colony Optimization can tune Support Vector Machine parameters.Ant Colony Optimization originally deals with discrete optimization problems. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal
Published 2017“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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Design of intelligent Qira’at identification algorithm
Published 2017“…To evaluate the algorithm, 350 samples for 10 types of Qira’at recitation are in used, and for justifying the best pattern classification, few algorithms are tested in the early preliminary evaluation with K-Nearest Neighbour, GMM and PPCA. …”
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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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A-star (A*) algorithm implementation for robotics path planning navigation
Published 2018“…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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Undergraduates Project Papers -
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Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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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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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
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Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group
Published 2014“…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
Published 2016“…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
Published 2017“…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The path computed using the classic Dijkstra's algorithm is the shortest; however, it may not be the most feasible. …”
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