Pattern Mining Method for Hospital Facility Review using Optimized Nonlinear Mathematical Model

The development of discovering appealing, valuable and important patterns from large spatial datasets is stated as spatial data mining. From the preceding hospital location analyses technique, the locations are predicted from the hospital dataset using pattern mining technique. In terms of road weightage computation the location analyses technique is not enough in its performance. In order to improve the performance, a new hospital location analyses method is proposed in this paper with non linear mathematical model. The proposed method comprises of four major stages, namely, feature compilation, developed non linear mathematical model, selection of patterns (locations) by utilizing pattern mining and location analyses. Initially the features are collected from the historical dataset that are related to information on roads and the nearest hospital locations. Based on the assembled information a non linear mathematical model is developed for the roads. The non linear mathematical model is a developed model and this is optimized by the Genetic Algorithm (GA). This optimized non linear mathematical model is utilized in the hospital location analyses process. Thus our proposed technique successfully selects the hospital locality via optimized non linear mathematical model and pattern mining. The implementation results showed the effectiveness of the proposed hospital location analyses method in predicting the hospitals and the achieved improvement in the analyses result. Furthermore, the performance of the proposed technique is evaluated by comparing it with the previous hospital location analyses method.