Predicting the Future: Optimized Grey N_Verhulst Model Reveals Trends in Chongqing’s Rural Migrant Workforce

Forecasting the number of rural migrant workers in Chongqing using the optimized grey N_Verhulst model – Nature

Rural Migration in Chongqing: New Insights Through Advanced Predictive Modeling

Unraveling the Shifts in Rural-to-Urban Migration Patterns in Chongqing

Chongqing, a city famed for its striking topography and swift urban growth, is experiencing a profound demographic shift fueled by the migration of rural laborers to urban centers. This movement is largely motivated by the pursuit of improved livelihoods and economic prospects. Grasping the underlying factors driving this migration has become increasingly vital as Chongqing’s population landscape evolves.

Recent research employing an enhanced predictive tool—the optimized grey N-Verhulst model—has provided fresh perspectives on forecasting migrant worker populations. Published in Nature, this study offers valuable projections that illuminate how labor dynamics may unfold amid ongoing rural-to-urban transitions. These insights are critical for policymakers aiming to balance economic development with social infrastructure demands within one of China’s most populous municipalities.

Key Drivers Behind Rural Labor Migration to Chongqing

The flow of rural workers into Chongqing is shaped by a multifaceted set of influences, where both “push” factors from countryside areas and “pull” factors from cities interact dynamically:

  • Evolving Economic Landscape: Expanding sectors such as manufacturing, technology, and services offer increasing employment opportunities that attract migrants seeking stable incomes.
  • Environmental Pressures: Declining agricultural yields due to climate variability and land degradation compel many rural residents to seek alternative livelihoods elsewhere.
  • Improved Social Amenities: Access to better education facilities, healthcare services, and social welfare programs draws younger generations toward urban environments.

The latest data forecasts a steady rise in migrant worker numbers over the next few years—a trend that poses significant challenges for local authorities tasked with managing housing availability, job creation, and community integration efforts. The table below summarizes projected figures based on current modeling outcomes:


Year Migrant Worker Estimate % Annual Growth
2023 1,200,000
2024 1,370,000 14.2%
2025 1,540,000 12.4%

This upward trajectory underscores an urgent need for comprehensive urban planning strategies encompassing affordable housing projects, targeted social support systems ,and employment facilitation programs designed specifically for migrant populations.

The Optimized Grey N-Verhulst Model: Enhancing Population Forecast Accuracy for Migrant Workers  in Urban Settings  of Chongqing

The optimized grey N-Verhulst model represents a cutting-edge evolution in demographic forecasting methodologies tailored explicitly toward predicting migratory labor flows within complex socio-economic contexts like those found in Chongqing’s rapidly changing environment.

This approach integrates principles from grey system theory—which excels at handling uncertain or incomplete information—with logistic growth models (N-Verhulst), enabling it to adapt dynamically as new data emerges or conditions shift.