Perception of Paddy Farmers on Climate Change in Western Odisha: An ANN Model Integration - Samik Kumar Pradhan; Akkamahadevi Naik; Ashok kumar; Soumik Ray (Indian Journal of Extension Education, 2025)
The study, conducted during 2024-25, to examine Paddy farmers’ perception of climate change in Balangir and Kalahandi districts of Western Odisha, an Artificial Neural Network (ANN) model was integrated to analyse the relationship between socio-economic factors of Paddy farmers and their perception of climate change. A total of 180 farmers were interviewed with a structured interview schedule to evaluate their perceptions of three main components, viz., exposure, sensitivity, and adaptive competence. The majority of farmers strongly agreed that climate variability, including erratic rainfall, rising temperatures, and extreme weather, adversely impacts agricultural production and causes a serious threat to food security, and changes in climatic conditions lead to shifts in cropping patterns. An ANN model identified the best hidden nodes, i.e., (3,3) for both the exposure and sensitivity, and (5,3) for the adaptive competence component, achieving a minimum Mean Square Error of 7.726 for the best neural network architecture.