Travel/activity behavior selection model parameter calibration method based on least square method
A technique of least squares and model selection, which is applied in the field of travel behavior modeling, and can solve problems such as not supporting the maximum likelihood estimation method, small data samples, and inability to calculate the convergence value of the maximum likelihood estimation.
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[0089] The accompanying drawings are for illustrative purposes only and should not be construed as limiting the patent.
[0090] For those skilled in the art, it is understandable that some well-known structures and descriptions thereof may be omitted in the drawings.
[0091] Below in conjunction with example and accompanying drawing, the present invention will be further described.
[0092] The invention provides a method for calibrating parameters of a travel / activity behavior selection model based on the least squares method, the method comprising the following steps:
[0093] (1) Define the data type and perform preprocessing;
[0094] (2) With the least squares method as the core, design the upper-level optimization model, and solve the optimal estimation of the parameters of the travel / activity behavior selection model;
[0095] (3) With the traffic distribution as the core, design the lower layer optimization model to solve the traffic distribution in the traffic net...
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