scholarly journals Advanced Early Dengue Prediction and Exploration Service (AEDES)

2021 ◽  
Author(s):  
Dominic Vincent Ligot ◽  
Mark Toledo
Keyword(s):  
Dengue Prediction

scholarly journals Ensemble method for dengue prediction

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0189988 ◽  
Author(s):  
Anna L. Buczak ◽  
Benjamin Baugher ◽  
Linda J. Moniz ◽  
Thomas Bagley ◽  
Steven M. Babin ◽  
...  
Keyword(s):  
Ensemble Method ◽  
Dengue Prediction

Specific K-mean clustering-based perceptron for dengue prediction

2017 ◽  
Vol 10 (3/4) ◽  
pp. 269
Author(s):  
Hoang Long Nguyen ◽  
Trong Hai Duong ◽  
Cuong Phan Nguyen ◽  
Duc Cuong Nguyen ◽  
Thach Phat Chiem ◽  
...  
Keyword(s):  
Dengue Prediction

scholarly journals Hybrid Classification Method for Dengue Prediction

2019 ◽  
Vol 8 (6) ◽  
pp. 1858-1861 ◽  
Keyword(s):  
Data Mining ◽  
Execution Time ◽  
Classification Method ◽  
Svm Classifier ◽  
Raw Data ◽  
Classification Approach ◽  
Hybrid Classification ◽  
Essential Knowledge ◽  
Accuracy Of Prediction ◽  
Dengue Prediction

Data mining is defined as the process in which useful information is extracted from the raw data. In order to acquire essential knowledge it is essential to extract large amount of data.. In this existing work, the technique of SVM is applied for the prediction of dengue. The SVM classifier has less accuracy and high execution time for the prediction. To improve the accuracy of prediction the voting based classification approach will be applied for the dengue prediction. The proposed method will be implemented in python and results will be analyzed in terms of accuracy, precision, recall and execution time.

scholarly journals Advanced Early Dengue Prediction and Exploration Service (AEDES)

2021 ◽  
Author(s):  
Dominic Vincent Ligot ◽  
Mark Toledo
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Public Interest ◽  
Surveillance System ◽  
Climate Data ◽  
Current State ◽  
Recent Developments ◽  
Dengue Prediction ◽  
Google Search ◽  
Precipitation And Temperature

This paper presents Project AEDES, a big data early warning, and surveillance system for dengue. The project utilizes Google Search Trends to detect public interest and panics related to dengue. Using Google Search Trends, precipitation, and temperature readings from climate data, the system nowcasts probable dengue cases and dengue-related deaths. The system utilizes FAPAR, NDVI, and NDWI readings from remote sensing to detect likely mosquito hotspots to prioritize interventions. We discuss the origin and development of the project and recent developments. We also discuss the current state of development and directions for further work.

Dengue Prediction Using Tweets in India

2019 ◽  
Vol 7 (10) ◽  
pp. 57-63
Author(s):  
Sarita Kumari ◽  
K. Jeberson ◽  
W. Jeberson
Keyword(s):  
Dengue Prediction

Developing a dengue prediction model based on climate in Tawau, Malaysia

Acta Tropica ◽  
2019 ◽  
Vol 197 ◽  
pp. 105055 ◽  
Author(s):  
Vivek Jason Jayaraj ◽  
Richard Avoi ◽  
Navindran Gopalakrishnan ◽  
Dhesi Baha Raja ◽  
Yusri Umasa
Keyword(s):  
Prediction Model ◽  
Model Based ◽  
Dengue Prediction

Microscopic Image Segmentation Using Hybrid Technique for Dengue Prediction

2016 ◽  
pp. 109-136
Author(s):  
Pramit Ghosh ◽  
Ratnadeep Dey ◽  
Kaushiki Roy ◽  
Debotosh Bhattacharjee ◽  
Mita Nashipuri
Keyword(s):  
Image Segmentation ◽  
Hybrid Technique ◽  
Microscopic Image ◽  
Dengue Prediction
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