Soft computing, encompassing several intelligence tools and techniques in the form of neural networks, fuzzy logic, and evolutionary computation, is efficient in handling uncertainties and imprecision prevalent in real-world settings. One of the more recent applications of soft computing falls within the realm of environmental science as a way to model and predict hazards to the environment in an age of increasing pollution.
Quantum-Inspired Soft Computing in Environmental Science explores the use of a hybrid soft-computing paradigm for the prediction of the adsorption capacity of an environmentally-friendly and low-cost adsorbent. Presenting a viable alternative to conventional time-consuming batch study experiments within environmental analysis, this video is beneficial to environmental scientists, researchers, and graduate students specializing in environmental prediction, modeling, and analysis.