『Abstract
This paper proposes a hybrid model based on genetic algorithm
(GA) and system dynamics (SD) for coal production-environmental
pollution load in China. GA has been utilized in the optimization
of the parameters of the SD model to reduce implementation subjectivity.
The chain of “Economic development-coal demand^-coal production-environmental
pollution load” of China in 2030 was predicted, and scenarios
were analyzed. Results show that: (1) GA performs well in optimizing
the parameters of the SD model objectively and in simulating the
historical data; (2) The demand for coal energy continuously increases,
although the coal intensity has actually decreased because of
China's persistent economic development. Furthermore, instead
of reaching a turning point by 2030, the environmental pollution
load continuously increases each year even under the scenario
where coal intensity decreased by 20% and investment in pollution
abatement increased by 20%; (3) For abating the amount of “three
types of wastes”, reducing the coal intensity is more effective
than reducing the polluted production per tonne of coal and increasing
investment in pollution control.
Keywords: Coal production; Environmental pollution; GA-SD prediction
model』
1. Introduction
2. GA-SD modeling
2.1. System boundary
2.2. Causal loop and flow diagrams
2.3. Initial value of the variables
2.4. Design the SD model equations
2.5. Parameter optimization by GA
3. GA optimization results
4. Scenario analysis
4.1. Scenario design
4.2. The results of scenarios
4.3. Results analysis
5. Conclusions
Acknowledgments
Appendix A
Appendix B
References