Search Results - (( pattern selection max algorithm ) OR ( java application clustering algorithm ))

Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

“…Owing to a number of salient features which include the ability of learning incrementally and establishing nonlinear decision boundary with hyperboxes, the Fuzzy Min-Max (FMM) network is selected as the backbone for designing useful and usable pattern classification models in this research. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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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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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Application-Programming Interface (API) for Song Recognition Systems by Murtadha Arif Sahbudin, Chakib Chaouch, Salvatore Serrano

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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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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Constrained clustering approach to aid in remodularisation of object-oriented software systems / Chong Chun Yong by Chong, Chun Yong

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Improving neural networks training using experiment design approach by Chong, Wei Kean

“…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. …”
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A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods by Teoh, Shen Khang

“…The proposed model is designed with single column architecture using single filter size and max pooling size. Fast lane connection and sample selective algorithms have been designed specifically to tackle the issue of vanishing gradient and enhance the quality of the model. …”
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FRGS-13-081-0322/ design and modelling of novel dynamic bandwidth aggregation scheme in heterogeneous wireless network (hwn) for mission critical applications by Anwar, Farhat, Huda Adibah, Mohd

“…This research aims to model and analyze the RAT section methods, resource allocation policy and packet reordering pattern. A multi criteria selection based method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been applied to select the most suitable RAT in HWN. …”
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An integrated model of automated elementary programming feedback using assisted and recommendation approach by Safei, Suhailan

“…Meanwhile, similar difficulty groups of the computer programs were generated using a K-Means clustering algorithm that was enhanced with ranking consideration. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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