Advanced AI Methods for Intelligent Data Analytics and Predictive Decision Making

In the current era, artificial intelligence plays a central role in driving technological advancements, a new age computing mechanism based on nature or bio inspired methodology came into existence. Bioinspired algorithms are algorithms which mimic the behaviour of organisms and are often linked with AI systems to guide goal-oriented organization. However, this methodology was implemented in early 90s, there is less research work done in this field. The past research shows the potential of such algorithms in various field like routing in ad-hoc networks, data analytics, and image processing. There is a growing need to apply nature-inspired algorithms in energy-sensitive environments, where solving complex problems must be balanced with computational efficiency and sustainability. The previous research results show that these algorithms have better capability than the traditional algorithms. The paper classifies all such algorithms which are efficient and open to use for more complex and NP hard problems. The focus is on their relevance to green computing and advantages such as design and lower computational complexity. The comparison of such algorithms is also done on different parameters so as to find out the optimality of these algorithms.