Search Results - (( parameter classification problems algorithm ) OR ( basic optimization path algorithm ))

Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

“…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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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…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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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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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm by Machmudah A., Parman S., Abbasi A., Solihin M.I., Manan T.S.A., Beddu S., Ahmad A., Rasdi N.W.

Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

“…It makes use of three basic operations in order to optimize this problem. …”
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Path planning algorithm for a car like robot based on MILP method by Mohd Sadri, Mohd Pawzi

“…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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Mobile First-Person Shooter (FPS) Game Using Basic Theta* Algorithm / Muhammad Syurahbil Abd Rohaman by Abd Rohaman, Muhammad Syurahbil

“…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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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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Genetic algorithm optimization for coefficient of FFT processor by Pang, Jia Hong, Sulaiman, Nasri

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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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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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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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Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment by Nurul Atikah Janis

“…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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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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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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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACOMV-SVM algorithm is able to simultaneously tune SVM parameters and feature subset selection. …”
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Optimizing support vector machine parameters using continuous ant colony optimization 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 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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Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…One of the most powerful machine learning methods to handle classification problems is the decision tree. There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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