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The Value Of An Intermediate Data

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The value to be used for updating the estimated value has been chosen as 181 (the value of range of each subgroup) for the first iteration of the algorithm. The value of an intermediate data has been taken as the range of each subgroup/ number of subgroup (181/6 = 30.16). That intermediate value 30.16 has been chosen as a change in temperature for the second iteration of algorithm. For third iteration, the value (30.16/6) 5.02 has been considered as a change in temperature. Similarly for the next iteration the value has been chosen as (5.02/6) 0.83 and so on. The value encoding is considered as the data encoding and the (1/estimated error) of the data with the actual data is considered as a fitness function
Step 2
The least square technique based on linear, exponential, asymptotic, curvilinear and logarithmic equations has been applied on the available data to produce the estimated data. The error analysis has been made to produce estimated error. It has been observed that average error based on least square technique based on linear equation has shown the minimum error (2.25%) as compared to the other models according to table 2. Therefore least square technique based linear equation has been chosen as the best known solution.
Step 3
The updating of estimated data has been made based on the process of simulating annealing algorithm. Initially, in the simulating annealing algorithm, high temperature values have to be considered for the material and decrease in the

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