Helicopter landing sites in proximity to the forest fire-risk zones are necessary for the delivery of supplies and fire emergency response teams. In this paper, we initially prepared forest fire risk map using Random Forest algorithm by overlaying the effective factors on fire occurring including vegetation types, physiographic, climatic and human factors. Then, three variants of natural candid...

Identifying the association between metabolites and diseases will help us understand pathogenesis of diseases, which has great significance in diagnosing treating diseases. However, traditional biometric methods are time consuming expensive. Accordingly, we propose a new metabolite-disease prediction algorithm based on DeepWalk random forest (DWRF), consists following key steps: First, semantic...

<p>Random forest algorithm is a common classification method. However, if the weights of many attributes in data set are not same or close to each other, direct use this for training will lead neglect interrelationships between these attributes, and it difficult reflect differences brought by different attributes. Worse, number relatively large, be given very little weight when normalizat...

This paper addresses the problem of forecasting daily stock trends. The key consideration is to predict whether a given will close on uptrend tomorrow with reference today’s closing price. We propose model that comprises features selection model, based Genetic Algorithm (GA), and Random Forest (RF) classifier. In our study, we consider four international indices follow concept distributed lag a...