Data mining in the construction industry: Present status, opportunities, and future trends

Lysine acetylation targets protein complexes and co-regulates major cellular functions

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A review of data-driven approaches for prediction and classification of building energy consumption

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Big Data in the construction industry: A review of present status, opportunities, and future trends

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Data Mining techniques for the detection of fraudulent financial statements

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Deep learning for estimating building energy consumption

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Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy

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Accurate occupancy detection of an office room from light, temperature, humidity and CO 2 measurements using statistical learning models

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Development of prediction models for next-day building energy consumption and peak power demand using data mining techniques

Fan, C., Xiao, F., & Wang, S. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.04.016 · Cited by 569 · see citing works

Data Mining for the Internet of Things: Literature Review and Challenges

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Data mining in manufacturing: a review based on the kind of knowledge

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A review of data mining applications for quality improvement in manufacturing industry

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Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques

Chou, J., Chiu, C., Farfoura, M. E., & AL-Taharwa, I. A. (2010) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000088 · Cited by 385 · see citing works

Construction site accident analysis using text mining and natural language processing techniques

Zhang, F., Fleyeh, H. A., Wang, X., & Lu, M. (2018) · Automation in Construction · doi:10.1016/j.autcon.2018.12.016 · Cited by 385 · see citing works

Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network

Atici, Ü. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.01.156 · Cited by 381 · see citing works

Application of machine learning to construction injury prediction

Tixier, A. J. ‐., Hallowell, M. R., Rajagopalan, B., & Bowman, D. (2016) · Automation in Construction · doi:10.1016/j.autcon.2016.05.016 · Cited by 361 · see citing works

Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning

Zhang, Z., Chong, A., Pan, Y., Zhang, C., & Lam, K. P. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.07.029 · Cited by 343 · see citing works

Times-series data augmentation and deep learning for construction equipment activity recognition

Rashid, K. M., & Louis, J. (2019) · Advanced Engineering Informatics · doi:10.1016/j.aei.2019.100944 · Cited by 341 · see citing works

Machine learning algorithms for construction projects delay risk prediction

Gondia, A., Siam, A., El-Dakhakhni, W., & Nassar, A. H. (2020) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001736 · Cited by 327 · see citing works

Automatic detection of hardhats worn by construction personnel: A deep learning approach and benchmark dataset

Wu, J., Cai, N., Chen, W., Wang, H., & Wang, G. (2019) · Automation in Construction · doi:10.1016/j.autcon.2019.102894 · Cited by 311 · see citing works

Deep learning-based feature engineering methods for improved building energy prediction

Fan, C., Sun, Y., Zhao, Y., Song, M., & Wang, J. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.02.052 · Cited by 305 · see citing works

Building Energy Consumption Prediction: An Extreme Deep Learning Approach

Li, C., Ding, Z., Zhao, D., Yi, J., & Zhang, G. (2017) · Energies · doi:10.3390/en10101525 · Cited by 300 · see citing works

Occupancy schedules learning process through a data mining framework

D’Oca, S., & Hong, T. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2014.11.065 · Cited by 294 · see citing works

Prediction of compressive strength of self-compacting concrete containing bottom ash using artificial neural networks

Siddique, R., Aggarwal, P., & Aggarwal, Y. (2011) · Advances in Engineering Software · doi:10.1016/j.advengsoft.2011.05.016 · Cited by 293 · see citing works

Safety leading indicators for construction sites: A machine learning approach

Poh, C. Q. X., Ubeynarayana, C. U., & Goh, Y. M. (2018) · Automation in Construction · doi:10.1016/j.autcon.2018.03.022 · Cited by 289 · see citing works

From occupancy to occupant behavior: An analytical survey of data acquisition technologies, modeling methodologies and simulation coupling mechanisms for building energy efficiency

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A data-mining approach to discover patterns of window opening and closing behavior in offices

D’Oca, S., & Hong, T. (2014) · Building and Environment · doi:10.1016/j.buildenv.2014.10.021 · Cited by 274 · see citing works

Novel Machine-Learning Model for Estimating Construction Costs Considering Economic Variables and Indexes

Rafiei, M. H., & Adeli, H. (2018) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0001570 · Cited by 272 · see citing works

Data mining in building automation system for improving building operational performance

Xiao, F., & Fan, C. (2014) · Energy and Buildings · doi:10.1016/j.enbuild.2014.02.005 · Cited by 258 · see citing works

Predictive modeling for US commercial building energy use: A comparison of existing statistical and machine learning algorithms using CBECS microdata

Deng, H., Fannon, D., & Eckelman, M. J. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.12.031 · Cited by 235 · see citing works

A framework for knowledge discovery in massive building automation data and its application in building diagnostics

Fan, C., Xiao, F., & Yan, C. (2014) · Automation in Construction · doi:10.1016/j.autcon.2014.12.006 · Cited by 218 · see citing works

Use of association rules to explore cause–effect relationships in occupational accidents in the Taiwan construction industry

Cheng, C.-W., Lin, C.-C., & Leu, S.-S. (2010) · Safety Science · doi:10.1016/j.ssci.2009.12.005 · Cited by 209 · see citing works

Estimation of the building energy use intensity in the urban scale by integrating GIS and big data technology

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Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review

Fan, C., Xiao, F., Li, C. Z., & Wang, J. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.11.008 · Cited by 203 · see citing works

Fault detection analysis using data mining techniques for a cluster of smart office buildings

Capozzoli, A., Lauro, F., & Khan, I. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.01.010 · Cited by 197 · see citing works

Data mining for customer service support

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Applied Data Mining for Business and Industry

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Data mining for occupational injuries in the Taiwan construction industry

Liao, C.-W., & Perng, Y. (2007) · Safety Science · doi:10.1016/j.ssci.2007.04.007 · Cited by 183 · see citing works

Overview of the Application of “Fuzzy Techniques” in Construction Management Research

Chan, A. P. C., Chan, D. W. M., & Yeung, J. F. Y. (2009) · Journal of Construction Engineering and Management · doi:10.1061/(asce)co.1943-7862.0000099 · Cited by 179 · see citing works

Improving prediction performance for indoor temperature in public buildings based on a novel deep learning method

Xu, C., Chen, H., Wang, J., Guo, Y., & Yuan, Y. (2018) · Building and Environment · doi:10.1016/j.buildenv.2018.10.062 · Cited by 178 · see citing works

A systematic approach to occupancy modeling in ambient sensor-rich buildings

Zheng, Y., Li, N., Becerik-Gerber, B., et al. (2013) · SIMULATION · doi:10.1177/0037549713489918 · Cited by 176 · see citing works

Data Preparation Process for Construction Knowledge Generation through Knowledge Discovery in Databases

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Automated daily pattern filtering of measured building performance data

Miller, C. C., Nagy, Z., & Schlueter, A. (2014) · Automation in Construction · doi:10.1016/j.autcon.2014.09.004 · Cited by 172 · see citing works

Comparison of Data Mining Techniques for Predicting Compressive Strength of Environmentally Friendly Concrete

Omran, B. A., Chen, Q., & Jin, R. (2016) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000596 · Cited by 169 · see citing works

Predicting construction cost overruns using text mining, numerical data and ensemble classifiers

Williams, T. P., & Gong, J. (2014) · Automation in Construction · doi:10.1016/j.autcon.2014.02.014 · Cited by 164 · see citing works

Integrated production planning and control system for a panelized home prefabrication facility using simulation and RFID

Altaf, M. S., Bouferguène, A., Liu, H., et al. (2017) · Automation in Construction · doi:10.1016/j.autcon.2017.09.009 · Cited by 159 · see citing works

Prediction of properties of waste AAC aggregate concrete using artificial neural network

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A deep learning-based method for detecting non-certified work on construction sites

Qi, F., Li, H., Luo, X., Ding, L., Rose, T. M., An, W., & Yu, Y. (2018) · Advanced Engineering Informatics · doi:10.1016/j.aei.2018.01.001 · Cited by 158 · see citing works

Textual data mining for industrial knowledge management and text classification: A business oriented approach

Ur-Rahman, N., & Harding, J. A. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.09.124 · Cited by 151 · see citing works

Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic

Sarıdemir, M., Topçu, İ. B., Özcan, F., & Severcan, M. H. (2008) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2008.07.021 · Cited by 150 · see citing works

Clustering-based analysis for residential district heating data

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Convolutional neural network: Deep learning-based classification of building quality problems

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A novel methodology for knowledge discovery through mining associations between building operational data

Yu, Z. J., Haghighat, F., Fung, B. C. M., & Zhou, L. G. (2011) · Energy and Buildings · doi:10.1016/j.enbuild.2011.12.018 · Cited by 143 · see citing works

Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete

Akande, K. O., Owolabi, T. O., Twaha, S., & Olatunji, S. O. (2014) · IOSR Journal of Computer Engineering · doi:10.9790/0661-16518894 · Cited by 143 · see citing works

Temporal knowledge discovery in big BAS data for building energy management

Fan, C., Xiao, F., Madsen, H., & Wang, D. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2015.09.060 · Cited by 142 · see citing works

Data mining: manufacturing and service applications

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Component-based machine learning for performance prediction in building design

Geyer, P., & Singaravel, S. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.07.011 · Cited by 135 · see citing works

On the feature engineering of building energy data mining

Zhang, C., Cao, L., & Romagnoli, A. (2018) · Sustainable Cities and Society · doi:10.1016/j.scs.2018.02.016 · Cited by 130 · see citing works

A cloud-based system framework for performing online viewing, storage, and analysis on big data of massive BIMs

Chen, H.-M., Chang, K.-C., & Lin, T.-H. (2016) · Automation in Construction · doi:10.1016/j.autcon.2016.03.002 · Cited by 128 · see citing works

Energy consumption predicting model of VRV (Variable refrigerant volume) system in office buildings based on data mining

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Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques

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Construction Safety Clash Detection: Identifying Safety Incompatibilities among Fundamental Attributes using Data Mining

Tixier, A. J. ‐., Hallowell, M. R., Rajagopalan, B., & Bowman, D. (2016) · Automation in Construction · doi:10.1016/j.autcon.2016.11.001 · Cited by 126 · see citing works

Fuzzy probabilistic expert system for occupational hazard assessment in construction

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Evolutionary Deep Learning-Based Energy Consumption Prediction for Buildings

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Rule-based system to detect energy efficiency anomalies in smart buildings, a data mining approach

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Electrical consumption forecasting in hospital facilities: An application case

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Advances and challenges in building engineering and data mining applications for energy-efficient communities

Yu, Z. J., Haghighat, F., & Fung, B. C. M. (2015) · Sustainable Cities and Society · doi:10.1016/j.scs.2015.12.001 · Cited by 121 · see citing works

A framework for data-driven informatization of the construction company

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Attention and sentiment of Chinese public toward green buildings based on Sina Weibo

Liu, X., & Hu, W. (2018) · Sustainable Cities and Society · doi:10.1016/j.scs.2018.10.047 · Cited by 116 · see citing works

Machine learning and BIM visualization for maintenance issue classification and enhanced data collection

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Data fusion in predicting internal heat gains for office buildings through a deep learning approach

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Information extraction in molecular biology

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Analysis of an energy efficient building design through data mining approach

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Automated Color Model–Based Concrete Detection in Construction-Site Images by Using Machine Learning Algorithms

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Attitude of the Chinese public toward off-site construction: A text mining study

Wang, Y., Li, H., & Wu, Z. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.117926 · Cited by 107 · see citing works

Retrieving similar cases for alternative dispute resolution in construction accidents using text mining techniques

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Predicting the outcome of construction incidents

Ayhan, B. U., & Tokdemir, O. B. (2018) · Safety Science · doi:10.1016/j.ssci.2018.11.001 · Cited by 102 · see citing works

Text analytics to analyze and monitor construction project contract and correspondence

Marzouk, M. M., & Enaba, M. (2018) · Automation in Construction · doi:10.1016/j.autcon.2018.11.018 · Cited by 101 · see citing works

Towards occupant activity driven smart buildings via WiFi-enabled IoT devices and deep learning

Zou, H., Zhou, Y., Yang, J., & Spanos, C. J. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.08.010 · Cited by 100 · see citing works

Combining association rules mining with complex networks to monitor coupled risks

Zhou, Y., Li, C., Ding, L., et al. (2019) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2019.02.013 · Cited by 100 · see citing works

PPDM: A Privacy-Preserving Protocol for Cloud-Assisted e-Healthcare Systems

Zhou, J., Cao, Z., Dong, X., & Lin, X. (2015) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2015.2427113 · Cited by 99 · see citing works

Efficient privacy preservation of big data for accurate data mining

Chamikara, M. A. P., Bertök, P., Liu, D., Camtepe, S. A., & Khalil, I. (2019) · Information Sciences · doi:10.1016/j.ins.2019.05.053 · Cited by 99 · see citing works

Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands

Luo, X., Oyedele, L. O., Ajayi, A., Monyei, C. G., Akinadé, O. O., & Akanbi, L. (2019) · Advanced Engineering Informatics · doi:10.1016/j.aei.2019.100926 · Cited by 99 · see citing works

Assessing environmental performance in early building design stage: An integrated parametric design and machine learning method

Feng, K., Lu, W., & Wang, Y. (2019) · Sustainable Cities and Society · doi:10.1016/j.scs.2019.101596 · Cited by 97 · see citing works

An integrated system of text mining technique and case-based reasoning (TM-CBR) for supporting green building design

Shen, L.-Y., Yan, H., Fan, H., Wu, Y., & Zhang, Y. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.08.026 · Cited by 96 · see citing works

Dealing with construction cost overruns using data mining

Ahiaga-Dagbui, D. D., & Smith, S. D. (2014) · Construction Management and Economics · doi:10.1080/01446193.2014.933854 · Cited by 95 · see citing works

Data mining for tunnel support stability: neural network approach

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Modeling and predicting occupancy profile in office space with a Wi-Fi probe-based Dynamic Markov Time-Window Inference approach

Wang, W., Chen, J., & Song, X. (2017) · Building and Environment · doi:10.1016/j.buildenv.2017.08.003 · Cited by 85 · see citing works

Extracting knowledge from building-related data — A data mining framework

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GA‐based multi-level association rule mining approach for defect analysis in the construction industry

Cheng, Y., Yu, W., & Li, Q. (2015) · Automation in Construction · doi:10.1016/j.autcon.2014.12.016 · Cited by 79 · see citing works

Efficient data perturbation for privacy preserving and accurate data stream mining

Chamikara, M. A. P., Bertök, P., Liu, D., Camtepe, S. A., & Khalil, I. (2018) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2018.05.003 · Cited by 76 · see citing works

Incorporating machine learning with building network analysis to predict multi-building energy use

Xu, X., Wang, W., Hong, T., & Chen, J. (2019) · Energy and Buildings · doi:10.1016/j.enbuild.2019.01.002 · Cited by 76 · see citing works

Data based complex network modeling and analysis of shield tunneling performance in metro construction

Zhou, C., Ding, L., Skibniewski, M. J., et al. (2018) · Advanced Engineering Informatics · doi:10.1016/j.aei.2018.06.011 · Cited by 75 · see citing works

Extracting typical occupancy data of different buildings from mobile positioning data

Gu, J., Xu, P., Pang, Z., Chen, Y., Ji, Y., & Chen, Z. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.09.002 · Cited by 71 · see citing works

Content-based text mining technique for retrieval of CAD documents

Yu, W., & Hsu, J.-Y. (2012) · Automation in Construction · doi:10.1016/j.autcon.2012.11.037 · Cited by 70 · see citing works

The application of case-based reasoning in construction management research: An overview

Hu, X., Xia, B., Skitmore, M., & Chen, Q. (2016) · Automation in Construction · doi:10.1016/j.autcon.2016.08.023 · Cited by 70 · see citing works

Deep Learning for Risk Detection and Trajectory Tracking at Construction Sites

Zhao, Y., Chen, Q., Cao, W., Yang, J., Xiong, J., & Gui, G. (2019) · IEEE Access · doi:10.1109/access.2019.2902658 · Cited by 70 · see citing works

Forecasting performance comparison of two hybrid machine learning models for cooling load of a large-scale commercial building

Zhou, X., Xuehui, Z., Lie-quan, L., Zubing, F., Junwei, Y., & Dongmei, P. (2018) · Journal of Building Engineering · doi:10.1016/j.jobe.2018.10.006 · Cited by 69 · see citing works

Development of a ranking procedure for energy performance evaluation of buildings based on occupant behavior

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Discovering gradual patterns in building operations for improving building energy efficiency

Fan, C., Sun, Y., Shan, K., Xiao, F., & Wang, J. (2018) · Applied Energy · doi:10.1016/j.apenergy.2018.04.118 · Cited by 64 · see citing works

Mining electrical meter data to predict principal building use, performance class, and operations strategy for hundreds of non-residential buildings

Miller, C. C., & Meggers, F. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.09.056 · Cited by 63 · see citing works

Challenges of Sustainable Construction: A Study of Educational Buildings in Nigeria

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Viability of the BIM Manager Enduring as a Distinct Role: Association Rule Mining of Job Advertisements

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Analyze the energy consumption characteristics and affecting factors of Taiwan's convenience stores-using the big data mining approach

Kuo, C. J., Lin, C.-H., & Lee, M.-H. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.03.021 · Cited by 61 · see citing works

A data-driven study of important climate factors on the achievement of LEED-EB credits

Cheng, J. C. P., & Ma, J. (2014) · Building and Environment · doi:10.1016/j.buildenv.2014.11.029 · Cited by 57 · see citing works

BIM Log Mining: Measuring Design Productivity

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Integrating data mining with KJ method to classify bridge construction defects

Cheng, Y.-M., & Leu, S.-S. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.12.047 · Cited by 55 · see citing works

Effectiveness of using WiFi technologies to detect and predict building occupancy

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Comparison of Machine Learning Models for Hazardous Gas Dispersion Prediction in Field Cases

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Development of a dynamic operational rating system in energy performance certificates for existing buildings: Geostatistical approach and data-mining technique

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Multiple mechanical properties prediction of hydraulic concrete in the form of combined damming by experimental data mining

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Systematic data mining-based framework to discover potential energy waste patterns in residential buildings

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Hybridization of CBR and numeric soft computing techniques for mining of scarce construction databases

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Development of a prediction model for the cost saving potentials in implementing the building energy efficiency rating certification

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Thermal-Sensor-Based Occupancy Detection for Smart Buildings Using Machine-Learning Methods

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Thermal comfort, occupant control behaviour and performance gap – A study of office buildings in north-east China using data mining

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Data quality and data cleaning

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Knowledge discovery from post-project reviews

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Energy diagnosis of variable refrigerant flow (VRF) systems: Data mining technique and statistical quality control approach

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Towards data-driven sustainable design: decision support based on knowledge discovery in disparate building data

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Data Mining Framework to Optimize the Bid Selection Policy for Competitively Bid Highway Construction Projects

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Data Preprocessing–Based Parametric Cost Model for Building Projects: Case Studies of Korean Construction Projects

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Assessing Residual Value of Heavy Construction Equipment Using Predictive Data Mining Model

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Heterogeneity evaluation of China's provincial energy technology based on large-scale technical text data mining

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Improving Workplace Hazard Identification Performance Using Data Mining

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RG108 increases NANOG and OCT4 in bone marrow-derived mesenchymal cells through global changes in DNA modifications and epigenetic activation

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Knowledge discovery of data-driven-based fault diagnostics for building energy systems: A case study of the building variable refrigerant flow system

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Integrating Neurofuzzy System with Conceptual Cost Estimation to Discover Cost-Related Knowledge from Residential Construction Projects

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Data mining based framework to identify rule based operation strategies for buildings with power metering system

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Automated load disaggregation for residences with electrical resistance heating

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Analysis of correlation between actual heating energy consumption and building physics, heating system, and room position using data mining approach

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BIM-oriented data mining for thermal performance of prefabricated buildings

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UTILIZING DATA MINING TO DISCOVER KNOWLEDGE IN CONSTRUCTION ENTERPRISE PERFORMANCE RECORDS/UTILIZUOTAS DUOMENŲ KAUPIMAS

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Probabilistic performance prediction of shield tunnels in operation through data mining

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Using data mining algorithms to predict the bond strength of NSM FRP systems in concrete

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Characterization of Steel Bridge Superstructure Deterioration through Data Mining Techniques

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Modeling adiabatic temperature rise during concrete hydration: A data mining approach

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A VaFALCON neuro-fuzzy system for mining of incomplete construction databases

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Hybrid Soft Computing Approach for Mining of Complex Construction Databases

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Modelling the thermal behaviour of a building facade using deep learning

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Assessing the performance of naturally day-lit buildings using data mining

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Identification of workstations in earthwork operations from vehicle GPS data

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Exploring the potential use of building facade information to estimate energy performance

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Building a Construction Project Key-Phrase Network from Unstructured Text Documents

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Indoor tracking trajectory data similarity analysis with a deep convolutional autoencoder

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Aseismic ability estimation of school building using predictive data mining models

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Challenges of micro/mild hybridisation for construction machinery and applicability in UK

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Learning method for knowledge retention in CBR cost models

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Flexible and Tradeoff-Aware Constraint-Based Design Space Exploration for Streaming Applications on Heterogeneous Platforms

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Component-Based Machine Learning for Energy Performance Prediction by MultiLOD Models in the Early Phases of Building Design

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Distribution patterns of energy consumed in classified public buildings through the data mining process

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Modeling of mechanical properties and bond relationship using data mining process

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Mining hierarchical relations in building management variables

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Searchable Encryption to Reduce Encryption Degradation in Adjustably Encrypted Databases

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Erratum for “Knowledge-Based Simulation Modeling of Construction Fleet Operations Using Multimodal-Process Data Mining” by Reza Akhavian and Amir H. Behzadan

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Applications of natural language processing in construction

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Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities

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Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development—A Systematic Literature Review

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Cost Overrun Risk Assessment and Prediction in Construction Projects: A Bayesian Network Classifier Approach

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Review on Research of Marxism Popularity in 2008

Xia, T. (2009) · Journal of Bohai University

Effects of occupancy estimation on abundance–occupancy relationships

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Higher education popularity:an inevitable alternative of higher education in new century

Xin, L. (2002) · Journal of Changchun University

Analysis of a Sporting Event on a Social Network: True Popularity & Popularity Bond

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On Phenomena of the Popularity and the Marketing of Literature

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