17 research outputs found
A hybrid elicit teaching learning based optimization with fuzzy c-means (ETLBO-FCM) algorithm for data clustering
No full textSince its inception, Fuzzy c-means (FCM) technique has been widely used in data clustering. The advantages of FCM such as balancing of individual number of cluster points, drifting of small cluster centers to large neighboring cluster centers, and presence of fuzzy factor, make it more popular. However, early trapping at local minima and high sensitivity to the cluster center initialization are the major limitations of FCM. In this paper, a novel Elicit Teaching learning based optimization (ETLBO) approach has been incorporated with the Fuzzy c-means clustering algorithm to obtain the improved fitness values of the cluster centers. The simulation results of the proposed method have been compared with some other existing methods such as GA, PSO and IPSO. Experimental results show that the proposed approach is superior to the other methods in terms of their fitness value calculations. Keywords: FCM, K-means, Elicit TLBO, TLBO, PSO, IPS
Approaches for comparative evaluation of raster GIS-based landslide susceptibility zonation maps
No full textRock slope stability assessment using finite element based modelling – examples from the Indian Himalayas
No full textStructure and its impact in Uthangarai and Thirthamalai region, Tamil Nadu, India using remote sensing technique
No full textInterpretation on water seepage and degree of weathering in a landslide based on pre‐ and post‐monsoon electrical resistivity tomography
No full textA comparative evaluation of supervised machine learning algorithms for township level landslide susceptibility zonation in parts of Indian Himalayas
No full textDesign and Development of an Intelligent Extension for Mapping Landslide Susceptibility Using Artificial Neural Network
No full textAntecedent Value of Professional Commitment and Job Involvement in Determining Job Satisfaction
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