Search Results - (( using composition clustering algorithm ) OR ( java application optimisation algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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Detection of tube defect using the autoregressive algorithm by Abd Halim, Zakiah, Jamaludin, Nordin, Junaidi, Syarif, Syed Yusainee, Syed Yahya

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Data redundancy reduction scheme for data aggregation in wireless sensor network by Adawy, Mohammad Ibrahim

“…This research proposes Data Redundancy Reduction Scheme (DRRS) which includes three algorithms namely, Metadata Classification (MC), Selection Active Nodes (SAN) and Anomaly Detection (AD) algorithms that works before data aggregation, when multiple composite events simultaneously occur in the different locations within the cluster. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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On the earthquake distribution modeling in Sumatra by Cauchy cluster process : comparing log-linear and log-additive intensity models by Susanto, Tabita Yuni, Choiruddin, Achmad, Purnomo, Jerry Dwi Trijoyo

“…The estimation procedure follows the standard two-step estimation technique, where the first step adapts the method for the Generalized Additive Models (GAMs) using penalized iteratively reweighted least squares (PIRLS) algorithm, and the second step employs the second-order composite likelihood. …”
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Simple algorithm for estimating the effects of reinforcement loadings and arrangements on composite properties by Wan Ibrahim, W. M. A, Yeoh, C. K., Teh, P.L., Khairel Rafezi, Ahmad, Ruhiyuddin , Mohd Zaki

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Hybrid of fuzzy clustering neural network over NSL dataset for intrusion detection system by Ahmad Zainaddin, Dahlia Asyiqin, Mohd Hanapi, Zurina

“…In recent years, data mining approach for intrusion detection have been advised and used. The approach such as Genetic Algorithms , Support Vector Machines, Neural Networks as well as clustering has resulted in high accuracy and good detection rates but with moderate false alarm on novel attacks. …”
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Quantitative Analysis And Mapping Of Concrete Scanning Electron Microscope (SEM) Images by Maizul, Elly Nur Myaisara

“…By spatial segmentation of K-Means algorithms, the cluster groups generated were carefully reviewed before proceeding to the final analysis. …”
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Unsupervised colour segmentation of white blood cell for acute leukaemia images by A. S., Abdul Nasir, Mohd Yusoff, Mashor, Prof. Dr., H., Rosline

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Sustainable Location Identification Decision Protocol (SuLIDeP) For Determining The Location Of Recycling Centres In A Circular Economy by Mohamed Sultan, Al Amin, Mativenga, Paul Tarisai

“…More significantly, this process could be used for clustering and reducing supply chains complexity to enable the setting up of multiple and optimally located recycling centres. …”
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Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

“…Computer modeling allows such electrical stimulations using statistics, bioinformatics and advanced machine-learning algorithms. …”
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Dietary patterns and health outcomes among African American maintenance hemodialysis patients by Tallman, Dina A., Latifi, Eno, Kaur, Deepinder, Sulaheen, Ayesha, Ikizler, T. Alp, Chinna, Karuthan, Mat Daud, Zulfitri 'Azuan, Karupaiah, Tilakavati, Khosla, Pramod

“…Implausible energy intake reports were screened out by comparing reported energy intake (rEI) with predicted total energy expenditure (pTEE). Cluster analysis, using the k-means algorithm, identified two distinct dietary patterns in the study population: a high “sugar sweetened beverage” pattern (hiSSB) and a low “sugar sweetened beverage pattern” (loSSB). …”
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