Loading...
Search for:
hybrid-approach
0.006 seconds
A novel clustering algorithm based on circlusters to find arbitrary shaped clusters
, Article 2008 International Conference on Computer and Electrical Engineering, ICCEE 2008, Phuket, 20 December 2008 through 22 December 2008 ; January , 2008 , Pages 619-624 ; 9780769535043 (ISBN) ; Habibi, J ; Abolhassani, H ; Shirali Shahreza, S ; Sharif University of Technology
2008
Abstract
Clustering is the problem of partitioning a (large) set of data using unsupervised techniques. Today, there exist many clustering techniques. The most important characteristic of a clustering technique is the shape of the cluster it can find. In this paper, we propose a method that is capable to find arbitrary shaped clusters and uses simple geometric constructs, Circlusters. Circlusters are different radius sectored circles. Circlusters can be used to create many hybrid approaches in mixture with density based or partitioning based methods. We also proposed two new clustering methods that are capable to find complex clusters in O(n), where n is the size of the data set. Both of the methods...
Circluster: storing cluster shapes for clustering
, Article 2008 4th International IEEE Conference Intelligent Systems, IS 2008, Varna, 6 September 2008 through 8 September 2008 ; Volume 3 , 2008 , Pages 1114-1119 ; 9781424417391 (ISBN) ; Hassas Yeganeh, S ; Abolhassani, H ; Habibi, J ; Sharif University of Technology
2008
Abstract
One of the important problems in knowledge discovery from data is clustering. Clustering is the problem of partitioning a set of data using unsupervised techniques. An important characteristic of a clustering technique is the shape of the cluster it can find. Clustering methods which are capable to find simple cluster shapes are usually fast but inaccurate for complex data sets. Ones capable to find complex cluster shapes are usually not fast but accurate. In this paper, we propose a simple clustering technique named circlusters. Circlusters are circles partitioned into different radius sectors. Circlusters can be used to create hybrid approaches with density based or partitioning based...
Combination of wavelet and PCA for face recognition
, Article 2006 IEEE GCC Conference, GCC 2006, Manama, 20 March 2006 through 22 March 2006 ; 2006 ; 9780780395909 (ISBN) ; Kasaei, S ; Sharif University of Technology
2006
Abstract
This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, and Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform and PCA. During the classification stage, the Neural Network (MLP) is explored to achieve a robust decision in presence of wide facial variations. The computational load of the proposed method is greatly reduced as comparing with the original PCA based method on the Yale and ORL face databases. Moreover, the...
A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran
, Article Energy ; Volume 49, Issue 1 , 2013 , Pages 204-210 ; 03605442 (ISSN) ; Ramiyani, S. S ; Sarvar, R ; Moud, H. I ; Mousavi, S. M ; Sharif University of Technology
2013
Abstract
This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the...
A new hybrid approach for dynamic continuous optimization problems
, Article Applied Soft Computing Journal ; Volume 12, Issue 3 , 2012 , Pages 1158-1167 ; 15684946 (ISSN) ; Nobahari, H ; Pourtakdoust, S. H ; Sharif University of Technology
2012
Abstract
A new hybrid approach for dynamic optimization problems with continuous search spaces is presented. The proposed approach hybridizes efficient features of the particle swarm optimization in tracking dynamic changes with a new evolutionary procedure. In the proposed dynamic hybrid PSO (DHPSO) algorithm, the swarm size is varied in a self-regulatory manner. Inspired from the microbial life, the particles can reproduce infants and the old ones die. The infants are especially reproduced by high potential particles and located near the local optimum points, using the quadratic interpolation method. The algorithm is adapted to perform in continuous search spaces, utilizing continuous movement of...
Wavelet transform and fusion of linear and non linear method for face recognition
, Article DICTA 2009 - Digital Image Computing: Techniques and Applications, 1 December 2009 through 3 December 2009, Melbourne ; 2009 , Pages 296-302 ; 9780769538662 (ISBN) ; Kasaei, S ; Neissi, N. A ; Sharif University of Technology
Abstract
This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, KPCA, and RBF Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform, PCA and KPCA. During the classification stage, the Neural Network (RBF) is explored to achieve a robust decision in presence of wide facial variations. At first derives a feature vector from a set of downsampled wavelet representation of face images, then the resulting PCA-based linear features and...
Construction and application of SVM model and wavelet-PCA for face recognition
, Article 2009 International Conference on Computer and Electrical Engineering, , 28 December 2009 through 30 December 2009, Dubai ; Volume 1 , 2009 , Pages 391-398 ; 9780769539256 (ISBN) ; Kasaei, S ; Alemi, H ; Sharif University of Technology
Abstract
This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, and SVM. Pre-processing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For pre-processing and feature extraction steps, we apply a combination of wavelet transform and PCA. During the classification stage, SVMs incorporated with a binary tree recognition strategy are applied to tackle the multi-class face recognition problem to achieve a robust decision in presence of wide facial variations. The binary trees extend naturally, the pairwise discrimination capability of the SVMs to...
A hybrid simulation-adaptive network based fuzzy inference system for improvement of electricity consumption estimation
, Article Expert Systems with Applications ; Volume 36, Issue 8 , 2009 , Pages 11108-11117 ; 09574174 (ISSN) ; Saberi, M ; Gitiforouz, A ; Saberi, Z ; Sharif University of Technology
2009
Abstract
This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and complex estimation and forecasting. Computer simulation is developed to generate random variables for monthly electricity consumption. Various structures of ANFIS are examined and the preferred model is selected for estimation by the proposed algorithm. Finally, the preferred ANFIS and time series...
Estimating the four parameters of the Burr III distribution using a hybrid method of variable neighborhood search and iterated local search algorithms
, Article Applied Mathematics and Computation ; Volume 218, Issue 19 , 2012 , Pages 9664-9675 ; 00963003 (ISSN) ; Abbasi, B ; Niaki, S. T. A ; Abdi, M ; Sharif University of Technology
2012
Abstract
The Burr III distribution properly approximates many familiar distributions such as Normal, Lognormal, Gamma, Weibull, and Exponential distributions. It plays an important role in reliability engineering, statistical quality control, and risk analysis models. The Burr III distribution has four parameters known as location, scale, and two shape parameters. The estimation process of these parameters is controversial. Although the maximum likelihood estimation (MLE) is understood as a straightforward method in parameters estimation, using MLE to estimate the Burr III parameters leads to maximize a complicated function with four unknown variables, where using a conventional optimization such as...