Application of Systems Approach for Spatial Planning of Human Settlements Case of India

Abstract

Systems approach is an established set of universal principles and particular newlinetechniques and tools, in preference to a topic or subject area on its own; it may be newlinecarried out in several fields and can be thus defined as a meta-discipline. In the past, newlineseveral kinds of system theories have been proposed including Systems Approach, newlineGeneral Systems Theory, Cybernetics, System Dynamics approach, etc. newlineMathematical Models on Spatial Planning of human settlement systems explain, newlinepredict and help in identifying gaps in the present and future dynamics through logical newlineprocedures. These procedures have been followed by spatial planners for a long time newlineand are being developed to date. newlineThe requirement for integrative explanations in mathematical models on spatial newlineplanning of human settlements is becoming imperative with each passing day due to newlinethe interconnectedness of the economic, social and environmental problems along newlinewith the urban challenges of the 21st century, change agents and evolution of more newlinerecent and novel planning procedures. newlineThis thesis works on and presents forward the data-oriented simulation of impact of newlineimmigration on urbanization in India (1961-2001). For this purpose, Bi-LSTM newline(Bidirectional Long Short-Term Memory) model is used. It is a category of recurrent newlineneural network (RNN) that can model sequential data effectively. The model, newlinecalibrated by introducing the novelty by enhanced attention mechanism, simulates the newlinegeneral dynamics of urban systems to a very precise degree of accuracy. The scales newlineof observations used are demography, trade, immigration, labour force and newlinedevelopment. The simulation helps in bringing to the surface the impact of newlineimmigration on the Gross Domestic Product (GDP) of the country. The proposed newlinemodel has been trained to study the data from 1961 to 2001, test the same from 2002 newlineto 2021 and then predict for the years till 2051 in three different scenarios, namely, newlinethree years prediction, five years prediction and ten years prediction. newlineThe proposed