Search Results - (( developing small clustering algorithm ) OR ( java implication force algorithm ))

Evaluation of FCV and FCM clustering algorithms in cluster-based compound selection by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli

“…One of most used clustering method is cluster-based compound selection, which involves subdividing a set of compounds into clusters and choosing one compound or a small number of compounds from each cluster. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

“…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The modified graph clustering ant colony optimisation (MGCACO) algorithm is an effective FS method that was developed based on grouping the highly correlated features. …”
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Development of a genetic-based hierarchical agglomerative clustering technique for parallel clustering of bilingual corpora based on reduced terms by Rayner Alfred, Jason Teo, Chung, Seng Kheau

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Application of fuzzy clustering analysis to compound datasets for drug lead identification by Sinarwati, Mohamad Suhaili, Mohamad Nazim, Jambli, Abdul Rahman, Mat

“…However, there are little study on overlapping method such as fuzzy cmean (FCM) and fuzzy c-varieties (FCV) clustering algorithms. Therefore, these two clustering algorithms are applied and their performance is compared based on the effectiveness of the clustering results in terms of separation between actives and inactives (Pa) into different clusters and mean intercluster molecular dissimilarity (MIMDS). …”
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

“…Many clustered routing algorithms have been developed to address various issues like energy efficiency, network lifetime, and hotspot problems. …”

SMALL-SCALE PRIMARY SCHOOL TIMETABLING PROBLEM by Yong, Phang How

“…A two staged timetabling heuristic approaches are proposed in this study. Clustering is the first phase of this approach which is a method of clustering a set of objects into the same group. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

“…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor by Mohd Noor, Nur Qamarina

“…The third experiment is performed to concurrently test an array of small embedded RAMs which is developed on a FPGA device. …”
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The development of level of detail (LOD) technique in 3D computer graphics application by Ismail, Nor Anita Fairos, Daman, Daut, Mohd. Rahim, Mohd. Shafry

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A spark-based parallel fuzzy C median algorithm for web log big data by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Sarkar, Rashal, Chalil, Aboosalih Kakkat

“…Clustering techniques for small datasets have led to the development of numerous successful clustering techniques. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

“…R-GIS(R software) and clustering algorithm were used for year 2014 with several weeks to develop the relation between the visualization and prediction of reported incidences. …”
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

“…Hence, the aims of this study are proposing an algorithm of hybrid to generate artificial samples adopts Small Johnson Data Transformation and Box-Whisker Plot which is introduced in previous studies. …”
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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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Development of real and reactive power allocation methods for deregulated power system by Shareef, Hussain

“…The second method is mainly applied for real power allocation. The method first clusters the system into small groups of buses. Then an appropriate conventional power flow tracing procedure is adopted to obtain the contribution factors within each cluster of buses. …”
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Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

“…All these achieved because the proposed algorithm targets those users located at the cluster borders who more likely cause rank deficiency. …”
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Position-based multicast routing in mobile ad hoc networks: an analytical study by Qabajeh, Mohammad M., Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Qabajeh, Liana K.

“…The results show that the used virtual clustering is very useful in improving scalability and outperforms other clustering schemes. …”
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Defect Detection And Classification Of Silicon Solar Wafer Featuring Nir Imaging And Improved Niblack Segmentation by Mahdavipour, Zeinab

“…The classification combines the analysis of defect intensity features, the application of unsupervised k-mean clustering and multi-class SVM algorithms. The methods have been applied for detecting, clustering and classification polycrystalline solar wafer images, corresponding to defects such as micro cracks, stain, and fingerprints. …”
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