Anurag Sharma scite author profile

In this paper, we presented the architecture and basic learning process underlying ANFIS (adaptive-network-based fuzzy inference system) which is a fuzzy inference system implemented in the framework of adaptive networks. Soft computing approaches including artificial neural networks and fuzzy inference have been used widely to model expert behavior. Using given input/output data values, the proposed ANFIS can construct mapping based on both human knowledge (in the form of fuzzy if-then rules) and hybrid learning algorithm. In modeling and simulation, the ANFIS strategy is employed to model nonlinear functions, to control one of the most important parameters of the induction machine and predict a chaotic time series, all yielding more effective, faster response or settling times.

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A Comparative Review on Routing Protocols in Wireless Sensor Networks

Sharma¹,

Singh²,

Sharma³

2015

IJCA

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Wireless Networking is a technology in which number of mobile nodes can communicate with each other directly or indirectly through wireless links. A sensor network is composed of a large number of sensor nodes and a sink. In the wireless sensor networks the main problem is limited battery life used by sensor nodes because the size of sensor nodes is small so constraints are there like battery size, processor, storage for data, these all are small as sensor nodes Routing protocols of sensor networks are dependable for handles the routes in the networks. This paper surveys current routing protocols for sensor networks and present a categorization for the various approaches pursued and contrast their strength and constraint.

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Geographic Routing Protocol: A Review

Kaur¹,

Singh²,

Sharma³

2016

IJGDC

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Effective Analysis of Lung Infection using Fuzzy Rules

Walia

Singh

Sharma

2016

IJ-AI

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<span style="font-size: 9.0pt; font-family: 'Times New Roman','serif'; mso-fareast-font-family: 'Times New Roman'; color: black; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA; mso-bidi-font-style: italic;">Soft Computing is conglomerate of methodologies which works together and provides an ability to make a decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, an algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses an output of Rulebase entered by the user to determine a level of infection.</span><div id="_mcePaste" class="mcePaste" style="position: absolute; left: -10000px; top: 0px; width: 1px; height: 1px; overflow: hidden;"><span style="font-size: 10pt; font-family: 'Times New Roman', serif;" lang="EN-IN">Soft Computing is conglomerate of methodologies which works together and provides an ability to make decision from reliable data or expert’s experience. Nowadays different types of soft computing techniques such as neural network, fuzzy logic, genetic algorithm and hybrid system are largely used in medical areas. In this paper, algorithm for analysis of lung infection is presented. The main focus is to develop system architecture to find probable disease stage patient may have. Severity level of disease is determined by using rule base method. The algorithm uses output of Rulebase entered by user to determine level of infection.</span></div>

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A comparative analysis of LEACH and SEP using NS2

Thapa¹,

Singh²,

Sharma³

2017

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Performance Enhancement of 16 Channels Back Haul DWDM OADM Ring Network Using Electronic Dispersion Compensation

Sharma¹,

Sharma²,

Kaur³

et al. 2014

AMM

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An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis

Sharma¹,

Sharma²,

Malhotra³

et al. 2021

Tuberculosis

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Fuzzy expert system for diagnosis of Breast Cancer

Ohri¹,

Singh²,

Sharma³

2016

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Anurag Sharma

ANFIS: Adaptive Neuro-Fuzzy Inference System- A Survey

A Comparative Review on Routing Protocols in Wireless Sensor Networks

Geographic Routing Protocol: A Review

Effective Analysis of Lung Infection using Fuzzy Rules

A comparative analysis of LEACH and SEP using NS2

Performance Enhancement of 16 Channels Back Haul DWDM OADM Ring Network Using Electronic Dispersion Compensation

An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis

Fuzzy expert system for diagnosis of Breast Cancer

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