An Exploration for the Analysis of Ground Water Possibility in Case Based Recommendation System using Hybrid Cuckoo Search and Artificial Honey Bee Algorithm

• Published in: International journal of advanced research in computer science Vol. 8; no. 5; p. 64
• Main Authors: Jethi, Sheetal, Sadawarti, Harsh
• Format: Journal Article
• Language: English
• Published: Udaipur International Journal of Advanced Research in Computer Science 01.05.2017
• Subjects: Algorithms; Eggs; Groundwater; Hybrid systems; Parameter sensitivity; Recommender systems; Search algorithms; Sensitivity analysis; Water resources
• ISSN: 0976-5697
• DOI: 10.26483/ijarcs.v8i5.3201

Groundwater Possibility Exploration is one of the prime problems in human life. Human and other social species are directly or indirectly dependent on water resources. But with increasing population and instant changing environmental conditions, groundwater resources are also becoming less day by day. One approach of manual exploration can be used but that is most laborious and time consuming task. So, there is need of some autonomous approach with which we can find the more groundwater resources without digging the bore well. This paper presents an autonomous approach in case based recommendation system using hybrid cuckoo search and artificial honey bee algorithm for groundwater possibility detection. The proposed concept is structured in the manner to have the input in the form six attributes of slope, geology, landuse, lineament, soil & landform and give output in the form of low, intermediate and high possibility. In this method, case based reasoning used in the manner to retrieve the previous knowledge of use cases. The cases are actually the host bird’s nest and input is cuckoo’s egg. CS originates from the behaviour of certain species of cuckoo which lay eggs in other birds nest in parasitic manner. If cuckoo’s egg adapts the behaviour of host nests it will exist otherwise the host bird will discard cuckoo’s egg. The minimum similarity value is calculated using ABC algorithm. CBR life cycle further uses the information from this metaphor. The overall method is evaluated using the parameters of sensitivity, specificity and accuracy.