Applying Case Based Reasoning in Cuckoo Search for the Expedition of Groundwater Exploration

Abstract

A new metaheuristic algorithm named Cuckoo search came up in the recent years. Though lots of metaheuristic algorithms exist but the main advantage of this algorithm is that its search space is extensive in nature. Due to its new arrival it hardly has any footprint in any application. Thus we have adapted this new nature inspired algorithm in our application. The main objective of our application is to find out the potentiality of groundwater in any area as queried by the user. To detect the presence of groundwater, we not only applied Cuckoo search but also case based reasoning. Thus our paper tries to integrate the above mentioned techniques. Our expert provided us with different geographical attributes such as landform, soil, lineament, geology, landuse, and slope. Depending on these attribute values, our proposed algorithm finds out the intensity of groundwater in such areas. Basically the intensity values are narrowed down to high, moderate and low. Thus, once a problem case is given by the user, the case based reasoning uses the K nearest neighbor algorithm to find out the best possible match. After the best possible match is obtained, we apply some propositional logic conditions. The need of propositional logic arises because we have observed a lot of varieties in our case base. Thus to maintain consistency in our output propositional logic is required. Our algorithm achieved 99 % efficiency. Thus we can use our proposed work in any real life problem where groundwater detection is necessary. In our application, cases are basically nests.