Prediction of Chikungunya disease using PSO-based adaptive neuro-fuzzy inference system model

ABSTRACT

Chikungunya is one of the rapidly spreading viruses which is transmitted by infected mosquitoes and is one of the global health issues. As population is growing at fast pace, so as the data related to patients, health staff ,and doctors. Many machine learning models for the classification of Chikungunya infection were proposed earlier, however, majority of these models suffer from hyper-parameter tuning. In this paper, we propose a novel machine learning model in which hyper-parameters of adaptive neuro-fuzzy inference system (ANFIS) model are optimized using crossover-based Particle Swarm Optimization (PSO). To improve the accuracy and performance of classification, the ANFIS model is optimized using crossover-based PSO. Then, this ANFIS model is trained and tested on the given dataset. The performance of the designed is compared with the existing Chikungunya disease predicting models. General experimental study shows that the proposed ANFIS outperforms competitive models in all aspects, and F-score, accuracy, sensitivity, and specificity are found to be 97.5%, 97.3%, 97.1%, 97.14% respectively. Thus forecasting in terms of predicting Chikungunya disease using optimized machine learning model provides better results and good decision making.

KEYWORDS:

• Adaptive neuro-fuzzy inference system (ANFIS)
• Chikungunya
• machine learning model
• particle swarm optimization (PSO)

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Sandeep Kaur

Sandeep Kaur is working as Assistant Professor, Department of Computer Science & Engineering , Guru Nanak Dev University, Regional Campus, Gurdaspur, since 2012. Pursuing Ph.D. from Guru Nanak Dev University, Amritsar. Area of interest is Artificial Intelligence and Machine Learning. Guided more than 15 M.Tech (CSE) students and have more than 12 papers published and presented in various journals and international conferences.

Kuljit Kaur Chahal

Dr. Kuljit Kaur Chahal is working as Associate Professor, Department of Computer Science , Guru Nanak Dev University, Amritsar. Teaching experience of more than 18 years. Area of interest is software engineering, artificial intelligence, open source software. Guided 5 Ph.D. students and have papers published more than 40 in various reputed journals. Also she has more than 24 papers presented and published in various conferences.