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Predicting Points with Interpolation: Linear, Quadratic, and TIN Approaches

Explore different approaches for predicting data points between known points using linear and quadratic interpolation methods, as well as the Triangular Irregular Network (TIN) technique. Understand how moving a point affects polynomial interpolation.

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Predicting Points with Interpolation: Linear, Quadratic, and TIN Approaches

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Presentation Transcript

  1. What approaches are there for predicting between points?

  2. To my data, right or wrong.

  3. Linear Interpolation 650 600 Known Points 550 Predicted Point Actual curve Numbers 500 450 400 350 0.9 1.1 1.3 1.5 1.7 1.9 2.1 Time

  4. Quadratic Interpolation Known Points Actual curve Numbers Predicted Point Time

  5. What happens if we move a point with polynomial Interpolation?

  6. Triangular Irregular Network (TIN) Latitude Longitude

  7. Triangular Irregular Network (TIN) Latitude Longitude

  8. Triangular Irregular Network (TIN) Latitude Longitude

  9. y = 1000 exp(-zt) y ' = -z exp(-zt) y ' (1) = -0.2 * exp(-0.2) = -0.16 y ' (1) = -1.0 * exp(-1.0) = -0.37

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