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Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.


Papers
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Proceedings ArticleDOI
03 Mar 2015
TL;DR: IASFLA is an integer-coded algorithm which unites the benefits of both the social behavior based PSO and the genetic-based memetic algorithm and is applied to find the optimum generation schedule considering losses and with valve point effect for thermal units.
Abstract: Economic dispatch is one of the optimization problems in the power system operation and planning in which the total cost of generation is minimized while supplying the demand and losses The ED problem have cost functions which are non-smooth curves with equality and inequality constraints Conventional methods have drawbacks of high convergence time and inherent sub optimality So the researchers are looking for the alternate methods which will overcome the drawbacks of the conventional methods In recent years optimization based on evolutionary approach is an upcoming one in which the social behavior of living organism is applied to get the solution The objective of the paper is to present the solution to Economic dispatch problem using An Improved Adaptive Shuffled Frog Leaping Algorithm(IASFLA) IASFLA is an integer-coded algorithm which unites the benefits of both the social behavior based PSO and the genetic-based memetic algorithm (MA) In this paper, IASFLA is applied to find the optimum generation schedule considering losses and with valve point effect for thermal units The validity of the proposed method is compared with the conventional Lagrange method, PSO, GA, Secant method and Shuffled Frog Leaping Algorithm Four different cases have been considered for simulation study and the results obtained prove the superiority of the proposed work It is observed from the result that the proposed method has produced best solution in terms of cost and convergence time

6 citations

Proceedings ArticleDOI
01 Jan 2015
TL;DR: The proposed model has a dynamic linear part between two static nonlinear parts and Piecewise linear, sigmoidal, saturation, dead zone and one dimensional polynomial nonlinearities are used as nonlinear part and transfer function is used as linear part.
Abstract: Potential of Hydrogen (pH) neutralization process plays a significant role in process industries. In pH neutralization process, identification can be done in many ways. Modeling of pH neutralization process is necessary for proper control. Neural networks used for modeling the process had a larger training error and learning rate selection was complex. Wiener model used for pH neutralization process identification had less model fit and larger training error. This paper presents the use of Hammerstein-Wiener model for identification of pH neutralization process. The proposed model has a dynamic linear part between two static nonlinear parts. Piecewise linear, sigmoidal, saturation, dead zone and one dimensional polynomial nonlinearities are used as nonlinear part and transfer function is used as linear part. Model is found for different nonlinearities and their model fits are compared. A model fit of 65.46% is obtained using Hammerstein-Wiener model. This paper also compares the results of Wiener model and Hammerstein-Wiener model.

6 citations

Proceedings ArticleDOI
26 Apr 2004
TL;DR: A fuzzy logic based system is presented to deal with the congestion control problem in asynchronous transfer mode (ATM) networks and the investigation is based on the simulation of peak cell rate, sustained cell rate and number of calls accepted.
Abstract: Summary form only given. Congestion in an ATM network is a condition in which performance degrades due to saturation of the network resources such as available communication links, processor speed and buffer capacity. The connection/call admission control (CAC) procedures determine if sufficient resources are available in the network to support the requested call. In this paper, a fuzzy logic based system is presented to deal with the congestion control problem in asynchronous transfer mode (ATM) networks. We examine the conventional CAC and fuzzy based CAC systems. The conventional CAC systems that utilize either capacity estimation or buffer thresholds are incapable of obtaining complete statistics on input traffic. This paper exploits the fuzzy concepts in order to provide effective congestion control in ATM networks. The investigation is based on the simulation of peak cell rate (PCR), sustained cell rate (SCR) and number of calls accepted.

5 citations

Journal ArticleDOI
TL;DR: An enhanced session key agreement protocol which uses the data derived from iris signature is suggested to improve the security of biometric based applications like e-Passport, e-Driving license, etc.
Abstract: Cryptographic protocols are the backbone of information security. Unfortunately the security of several important components of these protocols can be neglected. This causes violation of p...

5 citations

Journal ArticleDOI
TL;DR: In this article, the value stream mapping (VSM) tool is used to identify the wastes at each stage of the production process and a future state value stream map is developed to illustrate the improvements achieved due to the implementation of selected lean tools.
Abstract: Manufacturing industries strive hard to improve their productivity to meet the highly demanding business market. Productivity can be improved by effective use of resources, elimination of wastes, process flow enhancement, and continuous improvement. There are strategies and tools to improve productivity but industries face the problem of selecting appropriate strategies. Lean manufacturing philosophy helps the manufacturing industries to enhance their productivity aspects by identifying and eliminating the wastes using specific tools/techniques. This article presents an integrated framework for the lean implementation process in the steel processing industry. The value stream mapping (VSM) tool is used to identify the wastes at each stage of the production process. Lean tools are identified from literature based on the wastes identified from the current state. For prioritizing the lean tools based on the positive correlation on one another, fuzzy integrated analytic hierarchy process and complex proportional assessment of alternatives are used. A future state value stream map is developed to illustrate the improvements achieved due to the implementation of selected lean tools. Comparison of present and future state VSM shows a great reduction of wastes, such as scale waste (50%), miss roll defects (72.7%), size variation defect (62%), corrosion defect, and improvements in talk time and cleanliness.

5 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202221
2021572
2020234
2019121
2018143
2017136