Search Results - (( based optimization path algorithm ) OR ( feature classification problem algorithm ))

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

“…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…The average size of feature subset is eight for the ACOR-SVM and IACOR-SVM algorithms and four for the ACOMV-R and IACOMV-R algorithms. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…The motion planning problem poses the question of how a robot can move from an initial to a final position. Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

“…This leads to the classification accuracy and genes subset size problem. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

“…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

“…In this paper, another extension of SKF algorithm, which is called binary SKF (BSKF) algorithm, is applied for the same feature selection problem. …”
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…An enhanced graph clustering ant colony optimisation (EGCACO) algorithm is proposed to solve the three (3) MGCACO algorithm problems. …”
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MULTIPLE DRONES PATH OPTIMIZATION ALGORITHM FOR 3D SPACE PERFORMANCE USING CENTRALIZED VISUALIZATION PLATFORM by Teng, Chu Yao

“…The existing methods aim for planning optimal path of drone flight. In this report, a variant of A*, Theta* algorithm is proposed to find the optimal path within a grid-based environment. …”
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Multi-robot path planning based on the improved nutcracker optimization algorithm and the dynamic window approach by Zhao, Jiangrong, Ding, Hongwei, Zhu, Yuanjing, Yang, Zhijun, Hu, Peng, Wang, Zongshan

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A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

“…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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A Novel Integrating Between Tool Path Optimization Using An ACO Algorithm And Interpreter For Open Architecture CNC System by Yusof, Yusri, Latif, Kamran, Hatem, Noor, A. Kadir, Aini Zuhra, Mohammed, M.A

“…Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. …”
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Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm by Kasim Hawari, Mohd Zarifitri

“…The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle.…”
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method by Loo, C.K., Rajeswari, M., Wong, E.K., RaoTask, M.V.C.

“…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm by Machmudah, Affiani, Parman, Setyamartana, Abbasi, Aijaz, Solihin, Mahmud Iwan, Abd Manan, Teh Sabariah, Beddu, Salmia, Ahmad, Amiruddin, Wan Rasdi, Nadiah

“…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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