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Kannan, K.
- Newton's Law of Gravity-based Search Algorithms
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Authors
Affiliations
1 Department of Mathematics, SASTRA University, Thanjavur, 613001, IN
1 Department of Mathematics, SASTRA University, Thanjavur, 613001, IN
Source
Indian Journal of Science and Technology, Vol 6, No 2 (2013), Pagination: 4141-4150Abstract
Many heuristic optimization methods have been developed in recent years that are derived from Nature. These methods take inspiration from physics, biology, social sciences, and use of repeated trials, randomization, and specific operators to solve NP-hard combinatorial optimization problems. In this paper we try to describe the main characteristics of heuristics derived from "Newton's law of gravitation", namely a gravitational emulation local search algorithm and a gravitational search algorithm. We also present the detailed survey of distinguishing properties, parameters and applications of these two algorithms.Keywords
Meta-Heuristic Algorithms, Gravitation, Newton's Law of Gravity, Combinatorial Optimization Problems, NP-HardFull Text
References
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- Wavelet Solution for Class of Nonlinear Integro-differential Equations
Abstract Views :331 |
PDF Views:0
Authors
Affiliations
1 Department of Mathematics, School of Humanities and Sciences, SASTRA University, Thanjavur-613401, Tamilnadu, IN
1 Department of Mathematics, School of Humanities and Sciences, SASTRA University, Thanjavur-613401, Tamilnadu, IN
Source
Indian Journal of Science and Technology, Vol 6, No 6 (2013), Pagination: 4670-4677Abstract
The aim of this work is to study the Legendre wavelets for the solution of a class of nonlinear Volterra integro-differential equation. The properties of Legendre wavelets together with the Gaussian integration method are used to reduce the problem to the solution of nonlinear algebraic equations. Also a reliable approach for convergence of the Legendre wavelet method when applied to nonlinear Volterra equations is discussed. Illustrative examples have been discussed to demonstrate the validity and applicability of the technique and the results obtained by Legendre wavelet method is very nearest to the exact solution. The results demonstrate reliability and efficiency of the proposed method.Keywords
Legendre Wavelets, Integro-differential Equations, Gaussian Integration, Legendre Wavelet Method, Convergence AnalysisFull Text
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- Soft Strongly g-Closed Sets
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Authors
Affiliations
1 Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA University, Kumbakonam - 612 001, Tamil Nadu, IN
2 Department of Mathematics, SASTRA University, Thanjavur - 613 401, Tamil Nadu, IN
1 Department of Mathematics, Srinivasa Ramanujan Centre, SASTRA University, Kumbakonam - 612 001, Tamil Nadu, IN
2 Department of Mathematics, SASTRA University, Thanjavur - 613 401, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 18 (2015), Pagination:Abstract
Background/Objectives: The objective of the present paper is to define soft strongly g-closed sets and soft strongly g-open sets in soft topological spaces and study their basic properties. Methods: Here we used the concept of soft closure of soft interior and soft open sets to define soft strongly g-closed sets. Findings: The relationship between soft strongly g-closed sets and other existing sets has been investigated. Further the union, intersection of two soft strongly g-closed sets have been obtained. The authors discussed the complements of soft strongly g-closed sets in the last section. Conclusion/Improvements: In future, the varieties of new continuous mappings and separation axioms based on these sets may be introduced and the future research may be undertaken in this direction.Keywords
Soft Strongly g-closed Sets, Soft Strongly g-open Sets, Soft g-closed Sets, Soft g-open Sets, Soft rg-closed Sets, Soft rg-open SetsFull Text
- Hypergraph-based Algorithm for Segmentation of Weather Satellite Imagery
Abstract Views :139 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
2 Department of Mathematics, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
1 Department of Computer Science, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
2 Department of Mathematics, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 36 (2016), Pagination:Abstract
Objective: Classification of cloud images through segmentation of automated satellite images to improvise the level of accuracy. Method Analysis: To classify cloud images the hyper graph model uses the idea of maximally bonded subsets that is endowed with integer valued metric are applied to receive the classifications. The widely used hyper graph model is Intensity Neighborhood Hyper graph (INHG) and representation model in this article is Intensity Interval Hyper graph (IIHG). Findings: The results obtained through this process is proved to be more accurate and the time complexity is O(n) in weather prediction. Similarly, the results received through IIHG, which also provides the same computational complexity where all the pixels to be processed with less time. Enhancement: The proposed methodology increases the accuracy level of prediction with less computation time and this work can be enhanced by including pattern recognition in automated processing.Keywords
Hyper Graph, INHG, IIHG, Satellite Imagery, Segmentation.Full Text
- Decision Making Process for B2C Model Using Behavior Analysis with Big Data Technologies
Abstract Views :196 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Engineering, Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Alpha College of Engineering, Chennai - 600035, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Alpha College of Engineering, Chennai - 600035, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 24 (2016), Pagination:Abstract
Objectives: Business to Consumer (B2C) E-Commerce activities are developed with a large number through agent-based systems. Case Based Reasoning (CBR) has been applied in these systems by analyzing the consumer buying behavior to provide consumers, a support to the decision making process. Analysis: Current applications of CBR to E-Commerce are limited to fixed, unchangeable products. To make the environment support for configurable products, an interactive operator based customization approach from CBR can be applied. Findings: In this work, to make the process more reliable and efficient, real time data from provisional stores has been taken and the system is trained to predict the consumer buying behavior along with CBR to pave way for a consumer to make a better decision making process. Applications/ Improvements: This work also applies big data concepts in predicting the behavior of the consumers. It thereby also led the customers to mine about their preferences in purchasing necessary products.Keywords
Big Data, Business to Consumer E-Commerce Activities, Case based Reasoning, Multi Agent Systems, Semantic Web.Full Text