Spatial and temporal characteristics of rural livability and its influencing factors: implications for the development of rural revitalization strategy.

Building livable rural regions is a key objective of China's rural revitalization, and fostering coordinated and sustainable regional development in China necessitates investigating the geographical and temporal distribution and influencing variables of livability in China's rural areas. This paper compares the concept and connotation of rural livability based on regional economic development theory and sustainable development theory, integrates China's rural revitalization strategy, proposes an index system for evaluating rural livability in China, and conducts an empirical analysis of livable rural areas. Firstly, the level of rural livability development is measured by the entropy method; secondly, the aggregation effect of provinces is demonstrated by using the Moran I index, and finally, the spatial Durbin model is used to explore the influencing factors of rural livability and its spatial spillover effects.

Implementing a novel deep learning technique for rainfall forecasting via climatic variables: An approach via hierarchical clustering analysis.

Variations in rainfall negatively affect crop productivity and impose severe climatic conditions in developing regions. Studies that focus on climatic variations such as variability in rainfall and temperature are vital, particularly in predominant rainfed areas. Forecasting rainfall is very essential in the agriculture sector due to the dependence of many people, while it is very complex to accurately predict rainfall due to its dynamic nature.