Search Results - (( basic optimization method algorithm ) OR ( user classification clustering algorithm ))

ChoCD : Usable and secure graphical password authentication scheme by Radhi Rafiee Bin Afandi

Text spam messages classification using Artificial Immune System (AIS) algorithms by Nurul Fadhilah Sulaiman

Clustering network traffic utilization by Mohd Khairudin, Nazli, Muda, Zaiton, Mustapha, Aida, Nagarathinam, Yogeswaran, Salleh, Mohd. Sidek

“…The clustering experiments were conducted using three different clustering algorithms, which are K-Means, DBScan and AutoClass. …”
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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. The optimal number of cluster for FCM is obtained through cluster validity analysis. …”
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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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Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

“…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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A global k-means approach for autonomous cluster initialization of probabilistic neural network by Chang, R.K.Y., Loo, C.K., Rao, M.V.C.

“…This brings about the problem of random initialization, which means, the user has to predefine the number of clusters through trial and error. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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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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Development of a parallel clustering of bilingual corpora based on reduced terms by Leow, Ching Leong

“…There are several studies related to document clustering. However, with the current technology, clustering bilingual text documents provides more benefits to users. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…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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Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

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A hybrid framework based on neural network MLP and means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…Due to the widespread use of Internet and communication networks, in case a reliable and secure network plays a crucial role for information technology (IT) service providers and users. The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is a big issue for majority of researches in this area.To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

“…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”

A knowledge based system for automatic classification of web pages by Fathy, Sherif Kassem

“…The paper describes design and implementation of a new knowledge based system for Automatic Information Retrieval DataBase (AIRDB).AIRDB helps the end-user to cluster and classify web pages on the basis of information filtering combined with an Artificial Neural Network (ANN).The classification depends mainly on keyword indexes.A large sample set consists of 11043 web pages of several formats are collected automatically and randomly from various resources.The AIRDB feature selection algorithm is summarized.The feature selection depends upon stemming words of web page. …”
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KM-NEU: an efficient hybrid approach for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia, Udzir, Nur Izura

“…The K-means clustering algorithm is engaged for grouping analogous nodes into k clusters using the similarity measures such as attack and non-attack, whereas the Neural Network Multi-Layer Perceptron classifies the clustered data into detail categories such as R2L, Probing, DoS, U2R and Normal. …”
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A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

“…To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. …”
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Classification and prediction of obesity levels among subjects in Colombia, Peru, and Mexico using unsupervised and supervised learning by Suhaila, Bahrom, Anuar, Ab Rani, Aisyah Amalina, Mohd Noor

“…Through Python, the study employs classification and clustering analyses, focusing on logistic regression to predict obesity levels and generate actionable recommendations. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
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