Search Results - (( java implementation clustering algorithm ) OR ( pattern using optimization algorithm ))

Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Enhancing Performance of Batik SMEs through Cleaner Production Adoption: Insights from Clustering Algorithm Analysis by Achmad, Fandi, Zulkarnain, Ibnu, Rumanti, Augustina Asih, Wiratmadja, Iwan Inrawan, Shuhidan, Shuhaida Mohamed

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A web-based implementation of k-means algorithms by Lee, Quan

“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

“…The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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Optimal point-to-point trajectory tracking of redundant manipulators using generalized pattern search by Ata, Atef A, Myo, ThiRein

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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA) by Chong, Shin Horng, Azahar, Arman Hadi, Mohamed Kassim, Anuar, Zainal Abidin, Amar Faiz, Harun, Mohamad Haniff, Nor Shah, Mohd Badril, Mohd Annuar, Khalil Azha, Manap, Mustafa, Rizman, Zairi Ismael

“…This paper presents the optimization process of Central Pattern Generator (CPG) controller for one legged hopping robot by using Genetic Algorithm (GA).To control the one legged hopping robot,a CPG controller is designed and integrated with a conventional ProportionalIntegral (PI) controller.Conventionally,the CPG parameters are tuned manually.But by using this method,the parameters produced are not exactly the optimum parameters for the CPG. …”
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Sheet C1 Pattern Number Recognition Using Artificial Immune System Optimization by Yuniarti Denita, Sari, Tri Basuki, Kurniawan, Edi Surya, Negara, Tata, Sutabri

“…In order to recognize the numerical patterns on sheet C1, we, therefore, require a method that uses the Artificial Immune System (AIS), specifically the CSA (Clonal Selection Algorithm) algorithm, which is one of the AIS system's algorithms for optimization. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

Optimal HE-PWM inverter switching patterns using differential evolution algorithm by Muhammad Ikram, Mohd Rashid, Hiendro, Ayong, Anwari, Makbul

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Linear array beampattern gain optimization techniques by Nagi F.

“…In the goal attaining algorithm the goal of optimization is set to the reference pattern. …”

Application of pattern search method to economic load dispatch with valve point loading / Siti Aisah Md. Sari by Md. Sari, Siti Aisah

“…The optimization of ED in power system is implemented through Optimization Toolbox in Matlab and PS technique is used as solver. …”
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Interference reduction by null-forming optimization based MVDR technique using gravitational search algorithm by Shahab, Suhail Najm, Ayib Rosdi, Zainun, Alabdraba, Waleed M. Sh., Nurul Hazlina, Noordin

“…In the present work, Gravitational Search Algorithm (GSA) is a new modern metaheuristic optimization technique used for optimizing the MVDR null-forming level by controlling the excitation weight coefficients in a linear antenna array radiation pattern synthesis. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…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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