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Application of machine learning models to investigate the performance of concrete reinforced with oil palm empty fruit brunch (OPEFB) fibers

Application of machine learning models to investigate the performance of concrete reinforced with... The use of agricultural waste as a sustainable fibre material for structural concrete manufacturing has been gaining traction owing to its eco-friendliness, availability, and cost effectiveness. The oil palm empty fruit brunch (OPEFB) fibre is cheap and readily available in most tropical countries. In this study, the performance of using OPEFB-fibre for structural concrete production was investigated experimentally and using a machine-learning approach. An architectural study of the artificial neural network (ANN) with different training algorithms and activation functions in a range of 1–10 neurons in a single hidden layer was carried out to select the optimal network for prediction. Also, hyper-parametric tuning of the adaptive neuro-fuzzy inference system (ANFIS) model clustered with fuzzy c-means (FCM) was studied for optimal model selection. The best models for each output were selected after evaluating the model’s performance using relevant statistical metrics like root mean square error (RMSE), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and correlation coefficient (R2). FCM-clustered ANFIS models with five, five, six, and four clusters for co-efficient of water absorption, density, compressive strength, and tensile strength, respectively, outperformed other models with RMSE values of 0.0016, 3.183, 0.6357 and 0.0234 and R2 values of 0.9994, 0.9985, 0.9966 and 0.9919, respectively. The experimental result revealed that the maximum compressive strength was obtained with 0.2% OPEFB-fibre at 60 days curing, maximum tensile strength with 0.2% OPEFB-fibre at 7 days curing and maximum density with 0.4% OPEFB-fibre at 7 days.Graphical abstract[graphic not available: see fulltext] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asian Journal of Civil Engineering Springer Journals

Application of machine learning models to investigate the performance of concrete reinforced with oil palm empty fruit brunch (OPEFB) fibers

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Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022
ISSN
1563-0854
eISSN
2522-011X
DOI
10.1007/s42107-022-00424-0
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Abstract

The use of agricultural waste as a sustainable fibre material for structural concrete manufacturing has been gaining traction owing to its eco-friendliness, availability, and cost effectiveness. The oil palm empty fruit brunch (OPEFB) fibre is cheap and readily available in most tropical countries. In this study, the performance of using OPEFB-fibre for structural concrete production was investigated experimentally and using a machine-learning approach. An architectural study of the artificial neural network (ANN) with different training algorithms and activation functions in a range of 1–10 neurons in a single hidden layer was carried out to select the optimal network for prediction. Also, hyper-parametric tuning of the adaptive neuro-fuzzy inference system (ANFIS) model clustered with fuzzy c-means (FCM) was studied for optimal model selection. The best models for each output were selected after evaluating the model’s performance using relevant statistical metrics like root mean square error (RMSE), mean absolute deviation (MAD), mean absolute percentage error (MAPE), and correlation coefficient (R2). FCM-clustered ANFIS models with five, five, six, and four clusters for co-efficient of water absorption, density, compressive strength, and tensile strength, respectively, outperformed other models with RMSE values of 0.0016, 3.183, 0.6357 and 0.0234 and R2 values of 0.9994, 0.9985, 0.9966 and 0.9919, respectively. The experimental result revealed that the maximum compressive strength was obtained with 0.2% OPEFB-fibre at 60 days curing, maximum tensile strength with 0.2% OPEFB-fibre at 7 days curing and maximum density with 0.4% OPEFB-fibre at 7 days.Graphical abstract[graphic not available: see fulltext]

Journal

Asian Journal of Civil Engineering – Springer Journals

Published: Feb 1, 2022

Keywords: Machine learning; Agricultural waste; Concrete; Empty palm oil fruit brunch fibres; Neural network

References

  • The application of ANFIS prediction models for thermal error compensation on CNC machine tools
    Abdulshahed, AM; Longstaff, AP; Fletcher, S
  • Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model
    Adedeji, PA; Akinlabi, S; Madushele, N; Olatunji, OO
  • “Prediction of the heating value of municipal solid waste: a case study of the city of Johannesburg
    Adeleke, O; Akinlabi, S; Jen, T-C; Dunmade, I
  • Application of artificial neural networks for predicting the physical composition of municipal solid waste: An assessment of the impact of seasonal variation
    Adeleke, O; Akinlabi, SA; Jen, T; Dunmade, I
  • Dunmade I (2020) Prediction of municipal solid waste generation: an investigation of the effect of clustering techniques and parameters on ANFIS model Performance
    Adeleke, O; Akinlabi, S; Jen, T-C
  • Experimental investigation on chemically treated bamboo reinforced concrete beams and columns
    Agarwal, A; Nanda, B; Maity, D
  • Application of advanced machine learning approaches to predict the compressive strength of concrete containing supplementary cementitious materials
    Ahmad, W; Ahmad, A; Ostrowski, KA; Aslam, F; Joyklad, P; Zajdel, P
  • Tensile, flexural and interlaminar shear properties of woven jute and jute-glass fabric reinforced polyester composites
    Ahmed, KS; Vijayarangan, S
  • Flexural behaviour of pultruded jute/glass and kenaf/glass hybrid composites monitored using acoustic emission
    Akil, HM; De Rosa, IM; Santulli, C; Sarasini, F
  • Evaluating oil palm fresh fruit bunch processing in Nigeria
    Anyaoha, KE; Sakrabani, R; Patchigolla, K; Mouazen, AM
  • High strength lightweight aggregate concrete using blended coarse lightweight aggregate origin from palm oil industry
    Aslam, M; Jumaat, MZ; Shafigh, P
  • Manufacturing of high-strength lightweight aggregate concrete using blended coarse lightweight aggregates
    Aslam, M; Shafigh, P; Alizadeh Nomeli, M; Zamin Jumaat, M
  • Artificial Intelligence to Model the Performance of Concrete Mixtures and Elements: A Review
    Behnood, A; Golafshani, EM
  • Thermal and mechanical performance of natural mortar reinforced with date palm fibers for use as insulating materials in building
    Benmansour, N; Agoudjil, B; Gherabli, A; Kareche, A; Boudenne, A
  • Clustered ANFIS network using fuzzy c-means, subtractive clustering, and grid partitioning for hourly solar radiation forecasting
    Benmouiza, K; Cheknane, A
  • Shear resistance prediction of post-fire reinforced concrete beams using artificial neural network
    Cai, B; Xu, L-F; Fu, F
  • Evaluation and monitoring of impact resistance of fiber reinforced concrete by adaptive neuro fuzzy algorithm
    Cao, Y
  • Modelling energy content of municipal solid waste using artificial neural network
    Ch Ogwueleka, T; Ogwueleka, FN
  • Natural fiber nonwoven reinforced cement composites as sustainable materials for building envelopes
    Claramunt, J; Fernández-Carrasco, LJ; Ventura, H; Ardanuy, M
  • Portland Cement Paste Blended with Pulverized Coconut Fibers
    Colorado, HA; Loaiza, A
  • A review on quality enhancement of oil palm trunk waste by resin impregnation: Future materials
    Dungani, R
  • Engineering properties of lightweight aggregate concrete containing binary and ternary blended cement
    Farahani, JN; Shafigh, P; Alsubari, B; Shahnazar, S; Bin Mahmud, H
  • Adaptive neuro fuzzy inference system based on fuzzy c – means clustering algorithm, a technique for estimation of tbm penetration rate
    Fattahi, H
  • Demountable connections of reinforced concrete structures: Review and future developments
    Figueira, D; Ashour, A; Yıldırım, G; Aldemir, A; Şahmaran, M
  • Enhancement of the mechanical properties of lightweight oil palm shell concrete using rice husk ash and manufactured sand
    Foong, KY; Alengaram, UJ; Jumaat, MZ; Mo, KH
  • Introduction to artificial neural networks
    Grossi, E; Buscema, M
  • Comparison of recurrent neural network, adaptive neuro-fuzzy inference system and stochastic models in eg̈irdir lake level forecasting
    Güldal, V; Tongal, H
  • Use of oil palm shell as an aggregate in cement concrete: A review
    Hamada, HM; Skariah Thomas, B; Tayeh, B; Yahaya, FM; Muthusamy, K; Yang, J
  • Lignocellulose-based hybrid bilayer laminate composite: part i - studies on tensile and impact behavior of oil palm fiber-glass fiber-reinforced epoxy resin
    Hariharan, ABA; Khalil, HPSA
  • Life cycle assessment of nanocellulose-reinforced advanced fibre composites
    Hervy, M; Evangelisti, S; Lettieri, P; Lee, KY
  • Modeling shear strength of medium- to ultra-high-strength steel fiber-reinforced concrete beams using artificial neural network
    Hossain, KMA; Gladson, LR; Anwar, MS
  • Mechanical and fresh properties of sustainable oil palm shell lightweight concrete incorporating palm oil fuel ash
    Islam, MMU; Mo, KH; Alengaram, UJ; Jumaat, MZ
  • Mechanical properties of sisal/oil palm hybrid fiber reinforced natural rubber composites
    Jacob, M; Thomas, S; Varughese, KT
  • Water sorption studies of hybrid biofiber-reinforced natural rubber biocomposites
    Jacob, M; Varughese, KT; Thomas, S
  • Cellulosic/synthetic fibre reinforced polymer hybrid composites: A review”
    Jawaid, M; Abdul Khalil, HPS
  • Woven hybrid composites: Tensile and flexural properties of oil palm-woven jute fibres based epoxy composites”
    Jawaid, M; Abdul Khalil, HPS; Abu Bakar, A
  • Prediction of long-term temperature effect in structural health monitoring of concrete dams using support vector machines with Jaya optimizer and salp swarm algorithms
    Kang, F; Li, J; Dai, J
  • A robust methodology for optimizing the topology and the learning parameters of an ANN for accurate predictions of laser-cut edges surface roughness
    Kechagias, JD; Tsiolikas, A; Petousis, M; Ninikas, K; Vidakis, N; Tzounis, L
  • Investigation of through beam connection to concrete filled circular steel tube (CFCST) column
    Khanouki, MMA; Ramli Sulong, NH; Shariati, M; Tahir, MM
  • Woven hybrid Biocomposite: Mechanical properties of woven kenaf bast fibre/oil palm empty fruit bunches hybrid reinforced poly hydroxybutyrate biocomposite as non-structural building materials
    Khoshnava, SM; Rostami, R; Ismail, M; Rahmat, AR; Ogunbode, BE
  • The use of oil palm fiber as additive material in concrete
    Lee, SW; Oh, CL; Zain, MRM; Yahya, NA
  • Properties of natural fiber cement materials containing coconut coir and oil palm fibers for residential building applications
    Lertwattanaruk, P; Suntijitto, A
  • Effect of pumice powder and nano-clay on the strength and permeability of fiber-reinforced pervious concrete incorporating recycled concrete aggregate
    Mehrabi, P
  • Feasibility study of high volume slag as cement replacement for sustainable structural lightweight oil palm shell concrete
    Mo, KH; Johnson Alengaram, U; Jumaat, MZ; Yap, SP
  • Durability performance of concrete incorporating waste metalized plastic fibres and palm oil fuel ash
    Mohammadhosseini, H; Tahir, MM
  • Suitability of oil-palm-broom-fibres as reinforcement for laterite-based roof tiles
    Momoh, EO; Dahunsi, BIO
  • Recent developments in the application of oil palm fibers in cement composites
    Momoh, EO; Osofero, AI
  • Some applications of ANN to solar radiation estimation and forecasting for energy applications
    Notton, G; Voyant, C; Fouilloy, A; Duchaud, JL; Nivet, ML
  • Potential of oil palm (elaeisguineensis) empty fruit bunch fibres cement composites for building applications
    Omoniyi, TE
  • Oil palm empty fruit bunch fibres as sustainable acoustic absorber
    Or, KH; Putra, A; Selamat, MZ
  • Tensile, physical and morphological properties of oil palm empty fruit bunch/sugarcane bagasse fibre reinforced phenolic hybrid composites
    Ramlee, NA; Jawaid, M; Zainudin, ES; Yamani, SAK
  • Estimating the vulnerability of the concrete moment resisting frame structures using artificial neural networks
    Rofooei, FR; Kaveh, A; Farahani, FM
  • Prediction of fresh and hardened properties of self-compacting concrete using support vector regression approach
    Saha, P; Debnath, P; Thomas, P
  • A comparative study of neural networks and ANFIS for forecasting attendance rate of soccer games
    Şahin, M; Erol, R
  • Engineering properties of lightweight aggregate concrete containing limestone powder and high volume fly ash
    Shafigh, P; Nomeli, MA; Alengaram, UJ; Bin Mahmud, H; Jumaat, MZ
  • Comparative performance of channel and angle shear connectors in high strength concrete composites: An experimental study
    Shariati, M; Sulong, NR; Shariati, A; Kueh, ABH
  • Forecasting municipal solid waste generation using artificial intelligence models—a case study in India
    Soni, U; Roy, A; Verma, A; Jain, V
  • The mechanical performance of hybrid phenol-formaldehyde-based composites reinforced with glass and oil palm fibres
    Sreekala, MS; George, J; Kumaran, MG; Thomas, S
  • Soft computing approaches for comparative prediction of the mechanical properties of jute fiber reinforced concrete
    Sultana, N; Hossain, SZ; Alam, MS; Islam, MS; Al Abtah, MA
  • Prediction of permeability and unconfined compressive strength of pervious concrete using evolved support vector regression
    Sun, J; Zhang, J; Gu, Y; Huang, Y; Sun, Y; Ma, G
  • Sustainable concrete containing palm oil fuel ash as a supplementary cementitious material – A review
    Thomas, BS; Kumar, S; Arel, HS
  • Design for deconstruction and material reuse
    Tingley, DD; Davison, B
  • Experimental study of flax FRP tube encased coir fibre reinforced concrete composite column
    Yan, L; Chouw, N
  • Effect of column parameters on flax FRP confined coir fibre reinforced concrete
    Yan, L; Chouw, N; Jayaraman, K
  • Microstructure, flexural properties and durability of coir fibre reinforced concrete beams externally strengthened with flax FRP composites
    Yan, L; Su, S; Chouw, N
  • Enhancement of mechanical properties in polypropylene– and nylon–fibre reinforced oil palm shell concrete
    Yap, SP; Alengaram, UJ; Jumaat, MZ
  • Flexural toughness characteristics of steel–polypropylene hybrid fibre-reinforced oil palm shell concrete
    Yap, SP; Bu, CH; Alengaram, UJ; Mo, KH; Jumaat, MZ
  • Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
    Yaseen, ZM
  • Performance comparison of ANFIS models by input space partitioning methods
    Yeom, CU; Kwak, KC
  • Effects of polypropylene twisted bundle fibers on the mechanical properties of high-strength oil palm shell lightweight concrete
    Yew, MK; Mahmud, HB; Shafigh, P; Ang, BC; Yew, MC
  • Comparison of ANN (MLP), ANFIS, SVM, and RF models for the online classification of heating value of burning municipal solid waste in circulating fluidized bed incinerators
    You, H
  • Effect of coir fiber loading on mechanical and morphological properties of oil palm fibers reinforced polypropylene composites
    Zainudin, ES; Yan, LH; Haniffah, WH; Jawaid, M; Alothman, OY