An Intelligent Approach for Virtual Chemistry Laboratory

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.