IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

An Intelligent Approach for Virtual Chemistry Laboratory

An Intelligent Approach for Virtual Chemistry Laboratory
View Sample PDF
Author(s): Shikha Mehta (Jaypee Institute of Information Technology, India), Monika Bajaj (University of Delhi, India) and Hema Banati (Dyal Singh College, India)
Copyright: 2019
Pages: 35
Source title: Virtual Reality in Education: Breakthroughs in Research and Practice
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-8179-6.ch023

Purchase

View An Intelligent Approach for Virtual Chemistry Laboratory on the publisher's website for pricing and purchasing information.

Abstract

Formal learning has shifted from the confines of institutional walls to our home computers and even to our mobiles. It is often felt that the concept of e-learning can be successfully applied to theoretical subjects but when it comes to teaching of science subjects like chemistry where hands on practical training is must, it is inadequate. This chapter presents a hybrid approach (amalgamation of concepts of machine learning technique with soft computing paradigm) to develop an intelligent virtual chemistry laboratory (IVCL) tool for simulating chemical experiments online. Tool presents an easy to use web based interface, which takes as input the reactants and presents results in the form of - type of reaction occurred and the list of possible products. Technically, the IVCL tool utilizes naïve bayes algorithm to classify the type of reactions and then applies genetic algorithm inspired approach to generate the products. Subsequently it employs system of equations method to balance the reactions. Experimental evaluations reveal that proposed IVCL tool runs with 95% accuracy.

Related Content

Xiaoxiao Liu, Ka Yin Chau, Hoi Sze Chan, Yan Wan. © 2022. 20 pages.
Jiancong Ye, Junpei Zhong. © 2022. 20 pages.
Yui-yip Lau, Ivy Chan. © 2022. 22 pages.
Haoyu Liu, Bowen Dong, Pi-Ying Yen. © 2022. 22 pages.
Karen Sie, Yuk Ming Tang, Kenneth Nai Kuen Fong. © 2022. 25 pages.
N. Raghavendra Rao. © 2022. 21 pages.
Yuk Ming Tang, Hoi Sze Chan, Wei Ting Kuo. © 2022. 29 pages.
Body Bottom