Algorithm 3 The gas recognition algorithm based on CNN

1   Input: E represents the error; e represents the set error value; k represents the number of iterations and K represents the maximum batch; $D_{total}$ represents all data sets.

2   Process:

//training the LeNet-5

3   for $D_{total}$ do

4    One-Hot encoding and data set partition

5    training dataset and testing dataset are obtained

6   Begin of training time

7   for all training dataset do

8    for $(k=0;k=k+1;k<K)$ do

9     Algorithm 1

10    if $E>e$ then do

11     Algorithm 2 and return to step 8

12    else

13     break;

14    end

15   end

16  end

17  End of training time

18  store all $w$ and all $b$

// test the LeNet-5

19  Load all $w$ and all $b$ to the LeNet-5 then do

20  Begin of test time

21  for all testing dataset do

22   Algorithm 1 which is forward propagation

23  end

24  End of test time

25  Calculate the accuracy

26  Output: training time, test time and accuracy.