In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news’ sentiments and Google search engine query data, we construct a web news content and online search behavior-based integrated model for real estate prediction. Besides these factors, real estate price time se...

The futures market offers a secure, precise and quick exchange platform for traders, offering efficient transactions no triangle bonds, which is beneficial establishing improving the economy. However, trading prices, it generally difficult to predict. Therefore, this article uses big data analysis methods predict prices. research results show that after using prediction analysis, highest accura...

Abstract Our target is focused largely on agriculture. In agriculture, farmers play the most important role. When price falls after harvest, face immense losses. A country’s GDP affected by fluctuations of agricultural products. Crop estimation and evaluation are done to take an intelligent decision before farming a specific type crop. Predicting crop will help in taking better decisions which ...

Bidirectional Long Short Term Memory (Bidirectional LSTM) is a machine learning technique with the ability to capture data context by traversing backward forward and vice versa. However, characteristics of stock large fluctuations, high dimensions non-linearity become challenge in obtaining price prediction accuracy values. The purpose this study provide solution problem combining Complete Ense...