Proposing novel ensemble approach of particle swarm optimized and machine learning algorithms for drought vulnerability mapping in Jharkhand, India

Abstract

Drought, a natural and very complex climatic hazard, causes impacts on natural and socio-economic environments. This study aims to produce the drought vulnerability map (DVM) considering novel ensemble machine learning algorithms (MLAs) in Jharkhand, India. Forty, drought vulnerability determining factors under the categories of exposure, sensitivity, and adaptive capacity were used. Then, four machine learning and four novel ensemble approaches of particle swarm optimized (PSO) algorithms, named random forest (RF), PSO-RF, multi-layer perceptron (MLP), PSO-MLP, support vector regression (SVM), PSO-MLP, Bagging, and PSO-Bagging, were established for DVMs. The receiver operating characteristic curve (ROC), mean-absolute-error (MAE), root-mean-square-error (RMSE), precision, and K-index were utilized for judging the performance of novel ensemble MLAs. The obtained results show that the PSO-RF had the highest performance with an AUC of 0.874, followed by RF, PSO-MLP, PSO-Bagging, Bagging, MLP, PSO-SVM and SVM, respectively. Produced DVMs would be helpful for policy intervention to minimize drought vulnerability.

Keywords:

• Drought vulnerability
• particle swarm optimized
• ensemble approaches
• exposure index
• GIS
• adaptive capacity index

Disclosure statement

No potential conflict of interest was reported by the author(s).

Credit author statement

Sunil Saha: Methodology, Format analysis, Supervision, Writing original draft preparation; Writing review and editing; Amiya Gayen: Methodology, Format analysis, writing original draft preparation, Writing review and editing; Priyanka Gogoi: Methodology, Format analysis, investigation, software, writing original draft preparation, Barnali Kundu: Format analysis, investigation, software, writing original draft preparation; Gopal Chandra Paul: Methodology, Format analysis, investigation, software, writing original draft preparation; Biswajeet Pradhan: Writing review and editing,

Data availability statement

All the relevant data have been provided in the tables. Sources of all the data have been describe properly. Derived data supporting the findings of this study are available from the corresponding author on request.

Additional information

Funding

No fund was received for this work.