Ant Colony Optimization of Interval Type-2 Fuzzy C-Means with Subtractive Clustering and Multi-Round Sampling for Large Data
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 1
Abstract
Fuzzy C-Means (FCM) is widely accepted as a clustering technique. However, it cannot often manage different uncertainties associated with data. Interval Type-2 Fuzzy C-Means (IT2FCM) is an improvement over FCM since it can model and minimize the effect of uncertainty efficiently. However, IT2FCM for large data often gets trapped in local optima and fails to find optimal cluster centers. To overcome this challenge an Ant Colony-based Optimization (ACO) is proposed. Another challenge encountered is determining the number of clusters to perform clustering. Subtractive clustering (SC) is an efficient technique to estimate appropriate number of clusters. Though for large datasets the convergence rate of ACO and SC becomes high and thus, it becomes challenging to cluster data and evaluate correct number of clusters. To encounter the challenges of large dataset, Multi-Round Sampling (MRS) technique is proposed. IT2FCM-ACO with SC and MRS technique performs clustering on subsets of data and determines suitable cluster centers and cluster number. The obtained clusters are then extended to the entire dataset. This eliminates the need for IT2FCM to work on the complete dataset. Thus, the objective of this paper is to optimize IT2FCM using ACO algorithm and to estimate the optimal number of clusters using SC while employing MRS to handle the challenges of voluminous data. Results obtained from several clustering evaluation measures shows the improved performance of IT2FCM-ACO-MRS compared to ITFCM-ACO and IT2FCM. Speed up for different sample size of dataset is computed and is found that IT2FCM-ACO-MRS is ≈1–5 times faster than IT2FCM and IT2FCM-ACO for medium datasets whereas for large datasets it is reported to be ≈ 30–150 times faster.
Authors and Affiliations
Sana Qaiyum, Izzatdin Aziz, Jafreezal Jaafar, Adam Kai Leung Wong
Keywords
Related Articles
- EP ID EP448671
- DOI 10.14569/IJACSA.2019.0100106
- Views 107
- Downloads 0
Calculation of Pressure Loss Coefficients in Combining Flows of a Solar Collector using Artificial Neural Networks
The paper presents a novel technique for determination of loss coefficients due to pressure by use of artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for pur...
FPGA-Based Design of High-Speed CIC Decimator for Wireless Applications
In this paper an efficient multiplier-less technique is presented to design and implement a high speed CIC decimator for wireless applications like SDR and GSM. The Cascaded Integrator Comb is a commonly used decimation...
Performance Analysis of Open Source Solution "ntop" for Active and Passive Packet Analysis Relating to Application and Transport Layer
A key issue facing operators around the globe is the most appropriate way to deal with spotting black in networks. For this purpose, the technique of passive network monitoring is very appropriate; this can be utilized t...
Phishing Website Detection based on Supervised Machine Learning with Wrapper Features Selection
The problem of Web phishing attacks has grown considerably in recent years and phishing is considered as one of the most dangerous Web crimes, which may cause tremendous and negative effects on online business. In a Web...
A Multi-Threaded Symmetric Block Encryption Scheme Implementing PRNG for DES and AES Systems
Due to the ever-increasing efficiency of computer systems, symmetric cryptosystem are becoming more vulnerable to linear cryptanalysis brute force attacks. For example, DES with its short key (56 bits) is becoming easier...