Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive strength of concrete using rebound hammer field test
Dung Quang VU1, Fazal E. JALAL2, Mudassir IQBAL3, Dam Duc NGUYEN1, Duong Kien TRONG1, Indra PRAKASH4, Binh Thai PHAM1()
1. University of Transport Technology, Hanoi 100000, Vietnam 2. Department of Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China 3. Department of Civil Engineering, University of Engineering and Technology, Peshawar 25120, Pakistan 4. DDG (R) Geological Survey of India, Gandhinagar 382010, India
In this study, we developed novel hybrid models namely Adaptive Neuro Fuzzy Inference System (ANFIS) optimized by Shuffled Complex Evolution (SCE) on the one hand and ANFIS with Artificial Bee Colony (ABC) on the other hand. These were used to predict compressive strength (Cs) of concrete relating to thirteen concrete-strength affecting parameters which are easy to determine in the laboratory. Field and laboratory tests data of 108 structural elements of 18 concrete bridges of the Ha Long-Van Don Expressway, Vietnam were considered. The dataset was randomly divided into a 70:30 ratio, for training (70%) and testing (30%) of the hybrid models. Performance of the developed fuzzy metaheuristic models was evaluated using standard statistical metrics: Correlation Coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that both of the novel models depict close agreement between experimental and predicted results. However, the ANFIS-ABC model reflected better convergence of the results and better performance compared to that of ANFIS-SCE in the prediction of the concrete Cs. Thus, the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of concrete based on easily determined parameters for the design of civil engineering structures including bridges.
. [J]. Frontiers of Structural and Civil Engineering, 2022, 16(8): 1003-1016.
Dung Quang VU, Fazal E. JALAL, Mudassir IQBAL, Dam Duc NGUYEN, Duong Kien TRONG, Indra PRAKASH, Binh Thai PHAM. Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive strength of concrete using rebound hammer field test. Front. Struct. Civ. Eng., 2022, 16(8): 1003-1016.
compressive strength of Portland cement mortar at an age of 28 d
PC
X13
MPa
43.09
43.83
43.418
0.265
compressive strength of concrete
Cs
Y
MPa
35.11
56.78
46.343
6.041
Tab.1
Fig.4
Fig.5
Fig.6
No
hyper-parameters
models
ANFIS
ANFIS-SCE
ANFIS-ABC
1
input membership function type
Gaussian
–
–
2
number of parameters per membership function
3
–
–
3
number of membership function per input
10
–
–
4
output membership function type
linear
–
–
5
number of total parameters
108
–
–
6
population size
–
50
50
7
complex size
–
20
–
8
number of complexes
–
10
–
9
number of parents
–
75
–
10
number of off springs
–
3
–
11
maximum number of iterations
–
5
–
12
acceleration coefficient upper bound
–
–
30
13
acceleration coefficient lower bound
–
–
1
14
stopping iteration
–
1000
1000
Tab.2
STT
models
RMSE
MAE
1
ANFIS-SCE
0.084633
0.061924
2
ANFIS-ABC
0.072634
0.056623
Tab.3
STT
models
RMSE
MAE
1
ANFIS-SCE
0.08348
0.067697
2
ANFIS-ABC
0.072272
0.059358
Tab.4
Fig.7
Fig.8
Fig.9
Fig.10
Fig.11
Fig.12
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