• Dr. S. Jafarunnisa

In rural communities, employment opportunities and infrastructure development are often interconnected. Efficient planning and development depend on accurate forecasting models that can predict future demands and resource requirements. This paper explores the application of mathematical forecasting techniques in rural employment trends and infrastructure planning. We focus on time series analysis, econometric models, and machine learning approaches that can aid in predicting future employment patterns and the infrastructure required to support sustainable economic growth. The goal is to demonstrate how mathematical forecasting tools can empower policymakers and local governments to make informed decisions that will enhance rural development, improve employment prospects, and optimize infrastructure investments.

Mathematical forecasting, rural employment, infrastructure planning, time series analysis, econometrics, machine learning, sustainable development

"Mathematical Forecasting for Rural Employment and Infrastructure Planning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.24-26, March-2025, Available :http://www.jetir.org/papers/JETIRGU06005.pdf

"Mathematical Forecasting for Rural Employment and Infrastructure Planning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. pp24-26, March-2025, Available at : http://www.jetir.org/papers/JETIRGU06005.pdf