Hadoop + Spark Platform Based on Big Data System Design of Agricultural Product Price Analysis and Prediction by HoltWinters

2019 ◽  
pp. 103-123
Author(s):  
Yun Deng ◽  
Yan Zhu ◽  
Qingjun Zhang ◽  
Xiaohui Cheng
Keyword(s):  
Big Data ◽  
System Design ◽  
Data System ◽  
Agricultural Product ◽  
Product Price ◽  
Price Analysis

scholarly journals Developing an Agricultural Product Price Prediction Model using HADT Algorithm

2019 ◽  
Vol 9 (1S4) ◽  
pp. 569-575
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Decision Tree ◽  
Prediction Model ◽  
Predictive Analytics ◽  
Agricultural Product ◽  
Agricultural Crop ◽  
Product Price ◽  
Price Prediction ◽  
Model Based

Big Data Predictive Analytics and Data mining are emerging recent research field to analyse the agricultural crop price. The applications and techniques of data mining as well as Big Data using agriculture data is considered in this paper. In particular, the farmers are more concern about estimating that how much profit they are about to expect for the chosen crop. As with many other sectors the amount of agriculture data are increasing on a daily source. In this work, agriculture crop price dataset of Virudhunagar District, Tamilnadu, India is considered and for the price prediction model based on data mining decision tree techniques. The main goal is to establish the new predictive model based on Hybrid Association rule-based Decision Tree algorithm (HADT). The outcome for the suggested HADT forecast model is heartening and precise to predict agricultural product prices than other current decision tree models.

FPGA medical big data system and ischemic stroke rehabilitation nursing

2021 ◽  
Vol 83 ◽  
pp. 104014
Author(s):  
Shanshan Liu ◽  
Dongchuan Zhai ◽  
Baoxue Han
Keyword(s):  
Big Data ◽  
Ischemic Stroke ◽  
Stroke Rehabilitation ◽  
Data System ◽  
Medical Big Data

scholarly journals IDENTIFICATION OF SOCIAL SYMPTOMS USING THE DRONE EMPRIT ACADEMIC AS A SUPPORT FOR STATISTICAL LITERACY

Abjadia ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 97
Author(s):  
Waluyo Satrio Adji ◽  
Abdul Bashith ◽  
Ali Nasith ◽  
Saiful Amin
Keyword(s):  
Social Media ◽  
Big Data ◽  
Critical Literacy ◽  
Statistical Data ◽  
Qualitative Approach ◽  
Data System ◽  
Literature Study ◽  
Statistical Literacy ◽  
Social Phenomena ◽  
Three Stages

<p>Social problems in Indonesia in particular are caused by social phenomena transmitted to users of social media, especially Twitter. Big data system provided by Drone Emprit Academic is able to find social phenomena. The ability of critical literacy to read and write supported by statistical data is very important in the 4.0 era. The aim of the research is to find out which Drone Emprit Academic works, analyzes, and displays data on social phenomena whose results can be used to support critical Literacy. This research uses a qualitative approach, literature study method. The analysis includes three stages, namely organize, synthesize, identify. The results of this study that Drone Emprit Academic is a big data system that carries out social network analysis of specific conversations on Twitter in semi-realtime and detail. The form displayed is in the form of a percentage of trends, retweet relationships, mentioning trend graphs, most retweet statuses, conversation trends. The data generated can help read information about social phenomena so that it can support critical literacy which has been partially published in online and offline media.</p>

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