Timber density determination method based on iteration weight least square estimate method
A least squares, iterative weighting technique, applied in the estimation field of wood density determination, can solve the problem of large batch wood error, and achieve the effect of accurate estimation
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specific Embodiment approach 1
[0042] A wood density determination method based on iterative weighted least squares estimation method, comprising the following steps:
[0043] Step 1. Randomly select samples for a batch of wood, and calculate the density ρ of each sample i ;
[0044] Step 2. Expected average estimate of sample density:
[0045] Step 2.1, frequency statistics of sample density:
[0046] from ρ i The maximum value ρ was determined in max and the minimum value ρ min ;
[0047] Take a=[ρ min *10 l-1 -0.5] / 10 l-1 , b=[ρ max *10 l-1 +0.5] / 10 l-1 ; l is ρ i , ρ max or ρ min The effective number of digits after the decimal point, the [ ] operation means to take an integer;
[0048] Divide the interval [a,b] into m small intervals, and calculate the number of sample densities p falling into each small interval j , this p j is the frequency, the total number of samples
[0049] Step 2.2, expected average estimate:
[0050] The expected average estimate of the sample density can b...
specific Embodiment approach 2
[0080] The specific process of step 1 of this embodiment is as follows:
[0081] Randomly select samples from a batch of wood (need to be representative, the number of samples should account for more than a quarter of the total samples, and not less than 20), and measure according to "GB / T 1933-2009 Wood Density Determination Method" Get the volume v of each sample i , mass g i , i is the serial number of the sample, i=1,2...n;
[0082] Calculate the density of each sample by formula (1)
[0083] ρ i = g i v i - - - ( 1 ) .
[0084] Other steps and parameters are the same as those in Embodiment 1.
specific Embodiment approach 3
[0085] The method for determining m described in step 2.1 of the present embodiment is as follows:
[0086] From the empirical formula m≈[Δ·(n-1) 0.4 ] Determine the interval m to be divided; Δ takes a value of 1.80 to 1.90;
[0087] In the formula, the [·] operation means to take an integer.
[0088] Other steps and parameters are the same as in the second embodiment.
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