Search Results - (( using function method algorithm ) OR ( parameter classification clustering algorithm ))

Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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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

“…Although the neural network methods are not very effective in clustering biologically active structures, their performance is remarkable when used as classifiers. …”
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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…To obtain optimal accuracy results, Uniform Design method is used to select parameter. The performance of the method is evaluated using 10-fold cross validation accuracy, confusion matrix, sensitivity and specificity. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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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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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…However, the MGCACO algorithm has three main drawbacks in producing a features subset because of its clustering method, parameter sensitivity, and the final subset determination. …”
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A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment by Tan, Ming Gui, Ho, Jee Hou, Goh, Hui Ting, Ng, Hoon Kiat, Abdul Latif, Lydia, Mazlan, Mazlina

“…Hierarchical cluster analysis was used to classify stroke survivors into different subgroups with (i) conventional multiple category of gait parameters (Approach 1), and (ii) single input by using the proposed K.I. value (Approach 2). …”
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Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

“…Whereas kernel-based clustering algorithm is developed for finding clusters in climate data. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…Hence, the algorithm must overcome the problem of dynamic update in the internal parameters or countering the concept drift. …”
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Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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Detection of sweetness level for fruits (watermelon) with machine learning by Wan Nazulan, Wan Nurul Suraya, Asnawi, Ani Liza, Mohd Ramli, Huda Adibah, Jusoh, Ahmad Zamani, Ibrahim, Siti Noorjannah, Mohamed Azmin, Nor Fadhillah

“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Development and usage of self-organising maps in high energy physics analysis with high performance computing / Mohd Adli Md Ali by Mohd Adli , Md Ali

“…Thus, development of an SOM algorithm for high energy physics datasets was performed. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Analysing method for acoustic emission clustering system on reinforced concrete beam by Saiful Bahari, Nur Amira Afiza

“…The need for effective data analysis in the clustering system can be linked to three main objectives in this research; (1) to determine the type of failure on reinforced concrete beams through the AE system; (2) to identify and discriminate the AE data parameters via crack classification (tensile and shear movement); (3) to verify the crack classification of Rise Amplitude (RA) clustering by using the NI LabVIEW clustering algorithm. …”
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