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Prediction
• Purpose: To estimate future outcomes based on historical data or current trends.
• Method: Uses statistical models, machine learning, or regression techniques.
• Example: Forecasting crop yield based on rainfall patterns and soil data.
• Key Feature: Focuses on what is likely to happen.
Simulation
• Purpose: To mimic the behavior of a system under various scenarios.
• Method: Builds a virtual model to test how changes in inputs affect outputs.
• Example: Simulating water flow in a river basin under different climate conditions.
• Key Feature: Explores what could happen under different conditions.
Optimization
• Purpose: To find the best possible solution from a set of alternatives.
• Method: Applies mathematical or heuristic algorithms to maximize or minimize objectives.
• Example: Determining the most efficient allocation of water resources to maximize food production while minimizing energy use.
• Key Feature: Focuses on what should be done to achieve the best outcome.
The video above will explain these differences in detail.
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