Search Results - (( using function _ algorithm ) OR ( using vector problem algorithm ))

Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

“…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

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Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions by Badaruddin, Muhammad, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Mohd Riduwan, Ghazali, Kian, Sheng Lim, Sophan Wahyudi, Nawawi, Nor Azlina, Ab. Aziz, Marizan, Mubin, Norrima, Mokhtar

“…The VEGSA algorithms use a number of populations of particles. …”
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Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions by Kian, Sheng Lim, Zuwairie, Ibrahim, Salinda, Buyamin, Anita, Ahmad, Faradila, Naim, Kamarul Hawari, Ghazali, Norrima, Mokhtar

“…The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. …”
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Performance evaluation of vector evaluated gravitational search algorithm II by Muhammad, B., Ibrahim, Z., Ghazali, K.H., Ghazali, M.R., Mubin, M., Mokhtar, M.

“…The VEGSAII algorithm uses a number of populations of particles. …”
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A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport by Toh , Yi Feng

“…To solve the problem, a test vector minimizer algorithm is proposed to eliminate redundant test vectors that do not contribute to reproduction of a test failure, hence, improving the debug throughput. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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An Improved VEPSO Algorithm for Multi-objective Optimisation Problems by Kamarul Hawari, Ghazali, Zuwairie, Ibrahim, Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Sophan Wahyudi, Nawawi, Norrima, Mokhtar

“…The vector evaluated particle swarm optimisation algorithm is widely used for such purpose, where this algorithm optimised one objective using one swarm of particles by the guidance from the best solution found by another swarm. …”
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Convergence and Diversity Evaluation for Vector Evaluated Particle Swarm Optimization by Mohd Zaidi, Mohd Tumari, Zuwairie, Ibrahim, Ismail, Ibrahim, Mohd Falfazli, Mat Jusof, Faradila, Naim, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Salinda, Buyamin, Anita, Ahmad

“…Hence, in this study, the performance of VEPSO algorithm is investigated by measuring the convergence and diversity by using standard test functions. …”
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Hand gesture recognition for autism diagnosis using Support Vector Machine (SVM) Algorithm / Muhammad Asyraf Mohamad Zain by Mohamad Zain, Muhammad Asyraf

“…To counter this problem, a system has been proposed to detect the hand gesture using one of the machine learning technique which is Support Vector Machine (SVM) Algorithm. …”
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Evaluation of Vector Evaluated Particle Swarm Optimisation Enhanced with Non-dominated Solutions and Multiple Nondominated Leaders based on WFG Test Functions by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Mohd Falfazli, Mat Jusof, Kian, Sheng Lim

“…One of MOO algorithms is Vector Evaluated Particle Swarm Optimization (VEPSO) algorithm. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization originally deals with discrete optimization problems. Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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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Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

“…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders by Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Mohd Ibrahim, Shapiai, Marizan, Mubin, Dong, Hwa Kim

“…The vector evaluated particle swarm optimisation (VEPSO) algorithm was previously improved by incorporating nondominated solutions for solving multiobjective optimisation problems. …”
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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…The smooth function is used to replace the plus function to obtain a smooth support vector machine (SSVM). …”
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Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

“…These techniques have been used to optimize control points and weights in the description of spline functions used. …”
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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms by Bundak, Caceja Elyca

“…Additionally, the effect of signal weighting function is investigated further using multiple K values of K nearest neighbour (KNN) algorithm. …”
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