Computer-Aided Analysis of Landsat-1 MSS Data: A Comparison of Three Approaches, Including a "Modified Clustering" Approach-1 MSS Data: A Comparison of Three Approaches, Including a "Modified Clustering" Approach

Computer-Aided Analysis of LANDSAT-1 MSS Data: A Comparison of Three Approaches, Including a "Modified Clustering" Approach

A Hybrid Data Clustering Algorithm Using Modified Krill Herd Algorithm and K-MEANS

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

A Hybrid Time Series Clustering Method Based on Fuzzy C-Means Algorithm: An Agreement Based Clustering Approach

In recent years, the advancement of information gathering technologies such as GPS and GSM networks have led to huge complex datasets such as time series and trajectories. As a result it is essential to use appropriate methods to analyze the produced large raw datasets. Extracting useful information from large data sets has always been one of the most important challenges in different sciences,...

Modified Convex Data Clustering Algorithm Based on Alternating Direction Method of Multipliers

Knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. Due to properly converting the task of optimization to an equivalent...

Evaluation of Updating Methods in Building Blocks Dataset

With the increasing use of spatial data in daily life, the production of this data from diverse information sources with different precision and scales has grown widely. Generating new data requires a great deal of time and money. Therefore, one solution is to reduce costs is to update the old data at different scales using new data (produced on a similar scale). One approach to updating data i...