Search Results - (( simulation evaluation path algorithm ) OR ( parameter classification problems algorithm ))

Wide area measurement system in the IEEE-14 bus system using multiobjective shortest path algorithm for fault analysis by Awalin, Lilik J., Syahirah, Abd Halim, Jafferi, Jamaludin, Nor Azuana, Ramli

“…To evaluate the performance of the multi-objective shortest path algorithm, all sections of the IEEE-14 bus system were simulated with faults. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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Evaluation of robot path planning algorithms in global static environments: genetic algorithm vs ant colony optimization algorithm / Nohaidda Sariff and Norlida Buniyamin by Sariff, Nohaidda, Buniyamin, Norlida

“…Performances between both algorithms were compared and evaluated in terms of speed and number of iterations that each algorithm takes to find an optimal path within several selected environments. …”
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An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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Performance analysis of genetic algorithm (GA)-based multi-constrained path routing algorithm by Yussof S.

“…This paper proposed a solution to the MCP problem using genetic algorithm (GA). The effectiveness of the proposed algorithm is evaluated through simulation. …”

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…In order to create parameters, there are many problems arise in the process of fuzzy modeling. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

“…Experiments via WEKA tool and simulation prototype were conducted to evaluate the methods used. …”
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Integrated ACOR/IACOMV-R-SVM Algorithm by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…The first algorithm, ACOR-SVM, will tune SVM parameters, while the second IACOMV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. …”
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A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

“…The performance of the proposed algorithm was tested through simulation studies in different types of environments to evaluate its ability to achieve different planning goals. …”

Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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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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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Performance comparison of a and Dijkstra algorithms with bézier curve in 2D grid and OpenStreetMap scenarios by Yusuf, Zakariah, Mohamad, Sufian, Wan Ibrahim, Wan Suhaifiza

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A Continuous Overlay Path Probing Algorithm For Overlay Networks by Feily, Maryam

“…Several experiments were carried out using the OMNeT++ simulation framework. The designed algorithm was evaluated using experimental data. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Sampling-based motion planning is a class of randomized path planning algorithms with proven completeness. …”
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Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization by Nor Azmi, Siti Nur Lyana Karmila, Anwar Apandi, Nur Ilyana, Rafique, Majid, Muhammad, Nor Aishah

“…The proposed algorithm is tested within a simulated 2D occupancy grid environment using both a 4×4 map for controlled experiments and a 20×20 map for comparative evaluation against a prior Improved ACO (IACO) study. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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