Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2463
Title: Weight based-artificial neural network (W-ann) for predicting dengue using machine learning approach with Indian perspective
Authors: Kapoor R
Kadyan V
Ahuja S.
Keywords: Artificial Neural Network
Dataset
Decision Tree
Dengue
Machine Learning
Random Forest
Support Vector Machine
Vector Borne Diseases.
Issue Date: 2020
Publisher: International Journal of Scientific and Technology Research
Abstract: Dengue is a rising vector borne disease in India. It becomes a burden for whole community residing in India. Unfortunately, still there is no vaccine discovered. Prevention and control of Dengue is still challenge for developing countries like India. The goal of this study is to investigate the influence, symptoms and clinical test parameters that belong to Dengue disease with an Indian perspective. This main aim is to develop a prediction model for early detection of Dengue. The propose prediction model is divided in to the following phases i.e. data preprocessing, training of ANN network with weights of symptoms & signs as well as evaluation function. Machine learning models namely decision tree, random forest and support vector machine is used to detect high priority symptoms. The experimental results show that support vector machine approach is more suitable for propose prediction model with in Indian environment. The future scope of this paper can be extended in to with other diseases like malaria, Chikungunya and Zika etc.
URI: http://hdl.handle.net/123456789/2463
Appears in Collections:Journals

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