簡易檢索 / 詳目顯示

回結果列表
研究生： 容德慶
Dedy - Kurniawan Wibowo
論文名稱： Predicting Productivity Loss Caused by Change Orders Using Evolutionary Fuzzy Support Vector Machine Inference Model
Predicting Productivity Loss Caused by Change Orders Using Evolutionary Fuzzy Support Vector Machine Inference Model
指導教授： 鄭明淵
Min-Yuan Cheng
口試委員: 楊亦東
I-Tung Yang
郭斯傑
Sy-Jye Guo
學位類別： 碩士
Master
系所名稱： 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 126
外文關鍵詞： Change orders, Productivity loss, EFSIM
相關次數： 點閱：169  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • Change orders in construction projects are very common and result in many negative impacts. The impact of change orders on labor productivity is difficult to quantify. A complex input-output relationship that measures the effect of change orders cannot be calculated using a traditional approach. In this study, Evolutionary Fuzzy Support Vector Machines Inference Model (EFSIM), which combines fuzzy logic (FL), support vector machine (SVM), and fast messy genetic algorithm (fmGA) is developed as a tool for predicting productivity loss caused by change orders. The SVM is utilized as a supervised learning technique for solving classification and regression problems. The advantages of FL in reckoning vagueness and uncertainty are exploited. Furthermore, fmGA is applied to optimize the model’s parameters. A case study regarding productivity loss caused by change orders is presented to demonstrate and to validate the performance of the proposed prediction model. Simulation results demonstrate EFSIM’s ability to predict the impact of change orders is outperformed compared to artificial neural network (ANN), support vector machine (SVM) and evolutionary support vector machine inference model (ESIM). Validation with previous studies shows that EFSIM successfully improve the accuracy and reliability of the prediction model.

    ABSTRACT i ACKNOWLEDGEMENT iii TABLE OF CONTENTS v ABBREVIATIONS AND SYMBOLS viii LIST OF FIGURES xi LIST OF TABLES xii 1 INTRODUCTION 1 1.1 Research Motivation 1 1.2 Research Objective 3 1.3 Scope Definition and Basic Assumption 3 1.4 Research Methodology 4 1.4.1 Problem Formulation 6 1.4.2 Literature Review 6 1.4.3 Model Construction 7 1.4.4 Productivity Loss Prediction Model 7 1.4.5 Prediction Result 7 1.4.6 Conclusion 8 1.5 Study Outline 8 2 LITERATURE REVIEW 10 2.1 Productivity Loss Caused by Change Orders 10 2.2 Data Preprocessing 16 2.3 Fuzzy Logic (FL) 19 2.4 Support Vector Machines (SVMs) 22 2.5 Fast Messy Genetic Algorithm (fmGA) 24 3 EVOLUTIONARY SUPPORT VECTOR MACHINE INFERENCE MODEL 27 3.1 Model Architecture 27 3.1.1 Training Data 28 3.1.2 Fuzzification 28 3.1.3 SVM training model 29 3.1.4 Defuzzification 29 3.1.5 fmGA Parameter Search 30 3.1.6 Fitness Evaluation 32 3.1.7 Termination Criteria 33 3.1.8 Optimal Prediction Model 33 3.2 Model Adaptation 33 3.2.1 Study Case Feasibility 33 3.2.2 Identify Factors of Influence 34 3.2.3 Collect Input and Output Patterns 35 3.2.4 Data Preprocessing 35 3.2.5 Execute EFSIM Process 36 3.2.6 Validation 36 4 PRODUCTIVITY LOSS PREDICTION USING EFSIM 39 4.1 Model Application Case Study 1 39 4.2 Model Application Case Study 2 43 5 RESULT AND DISCUSSION 47 5.1 Result Case Study 1 47 5.1.1 Training Process and Result 47 5.1.2 Testing Process and Result 52 5.1.3 Comparison 55 5.2 Result Case Study 2 61 5.2.1 Training Process and Result 61 5.2.2 Testing Process and Result 64 5.2.3 Comparison 64 6 CONCLUSIONS AND RECOMMENDATIONS 66 6.1 Review of Purpose 66 6.2 Summary 66 6.3 Conclusions 67 6.4 Future Recommendations 67 References 69 Appendix A A-1 Appendix B B-1 Appendix C C-1

    Ahn, Y. H., Annie, R. P., and Kwon, H. (2012). "Key Competencies for U.S. Construction Graduates: Industry Perspective." Journal of Professional Issues in Engineering Education and Practice, 138(2), 123-130.
    Alnuaimi, A. S., Taha, R. A., Mohsin, M. A., and Al-Harthi, A. S. (2010). "Causes, Effects, Benefits, and Remedies of Change Orders on Public Construction Projects in Oman." Journal of Construction Engineering and Management, 136(5), 615-622.
    Assem, I. (2000). "Estimating productivity losses due to change orders." Master, Concordia University, Montreal.
    Bent, J., and Thuman, A. (1988). Project management for engineering and construction, Prentice-Hall, Englewood Cliffs, NJ.
    Bojadziev, G., and Bojadziev, M. (2007). Fuzzy Logic for Business, Finance, and Management 2nd, World Scientific, Singapore.
    Borra, S., and Di Ciaccio, A. (2010). "Measuring the prediction error. A comparison of cross-validation, bootstrap and covariance penalty methods." Computational Statistics & Data Analysis, 54(12), 2976-2989.
    Bruggink, M. J. (1997). "An investigation into the impacts of change orders on labor efficiency in the electrical construction industry." Master, University of Wisconsin-Madison, Madison.
    Burges, C. J. C. (1998). "A Tutorial on Support Vector Machines for Pattern Recognition." Data Min. Knowl. Discov., 2(2), 121-167.
    Cheng, M.-Y., and Roy, A. F. V. (2010). "Evolutionary fuzzy decision model for construction management using support vector machine." Expert Systems with Applications, 37(8), 6061-6069.
    Cheng, M.-Y., and Wu, Y.-W. (2009). "Evolutionary support vector machine inference system for construction management." Automation in Construction, 18(5), 597-604.
    Chou, J.-S., Chiu, C.-K., Farfoura, M., and Al-Taharwa, I. (2011). "Optimizing the Prediction Accuracy of Concrete Compressive Strength Based on a Comparison of Data-Mining Techniques." Journal of Computing in Civil Engineering, 25(3), 242-253.
    Cruz, D. (2007). "Application of Data Screening Procedures in Stress Research." The New School Psychology Bulletin, 5(2), 41-45.
    Deb, K., and Goldberg, D. E. (1991). "mGA in C: A Messy Genetic Algorithm in C." IllGAL Technical Report 91008, University of Illinois at Urbana-Champaign, Urbana, Illinois.
    Feng, C.-W., and Wu, H.-T. (2006). "Integrating fmGA and CYCLONE to optimize the schedule of dispatching RMC trucks." Automation in Construction, 15(2), 186-199.
    Goldberg, D., Deb, K., Kargupta, H., and Harik, G. (1993). "Rapid accurate optimization of difficult problems using fast messy genetic algorithms." Proceedings of the 5th International Conference on Genetic Algorithms, Morgan Kaufmann Publishers Inc.
    Grzymala-Busse, J. W., and Grzymala-Busse, W. J. (2010). "Handling Missing Attribute Values." Data Mining and Knowledge Discovery Handbook, O. Maimon, and L. Rokach, eds., Springer US, 33-51.
    Han, J., and Kamber, M. (2007). Data Mining: Concept and Techniques (2nd Edition), Morgan Kaufmann Publisher, San Fransisco.
    Hanna, A. S., Lotfallah, W. B., and Lee, M.-J. (2002). "Statistical-Fuzzy Approach to Quantify Cumulative Impact of Change Orders." Journal of Computing in Civil Engineering, 16(4), 252-258.
    Hanna, A. S., Russell, J. S., Gotzion, T. W., and Nordheim, E. V. (1999a). "Impact of Change Orders on Labor Efficiency for Mechanical Construction." Journal of Construction Engineering and Management, 125(3), 176-184.
    Hanna, A. S., Russell, J. S., Nordheim, E. V., and Bruggink, M. J. (1999b). "Impact of Change Orders on Labor Efficiency for Electrical Construction." Journal of Construction Engineering and Management, 125(4), 224-232.
    Hester, W. T., Kuprenas, J. A., and Chang, T. C. (1991). "Construction changes and change orders: Their magnitude and impact." Construction Industry Institute, Univ. of Texas at Austin, Austin, Tex.
    Hsu, C.-W., Chang, C.-C., and Lin, C.-J. (2003). "A Practical Guide to Support Vector Classification." National Taiwan University, Taipei, Taiwan.
    Hwang, B.-G., and Low, L. K. (2011). "Construction project change management in Singapore: Status, importance and impact." International Journal of Project Management(0).
    Ibbs, W. (2005). "Impact of Change's Timing on Labor Productivity." Journal of Construction Engineering and Management, 131(11), 1219-1223.
    Ishigami, H., Fukuda, T., Shibata, T., and Arai, F. (1995). "Structure optimization of fuzzy neural network by genetic algorithm." Fuzzy Sets and Systems, 71(3), 257-264.
    Johnson, J. A., and Smartt, H. B. (1995). "Advantages of an alternative form of fuzzy logic." Fuzzy Systems, IEEE Transactions on, 3(2), 149-157.
    Keane, P., Sertyesilisik, B., and Ross, A. D. (2010). "Variations and Change Orders on Construction Projects." Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, 2(2), 89-96.
    Kecman, V. (2005). "Support Vector Machine - An Introduction." Support Vector Machines: Theory and Applications, L. Wang, ed., Springer-Verlag, Berlin Heidelberg, 1-47.
    Ko, C. H. (2002). "Evolutionary fuzzy neural inference model (EFNIM) for decision-making in construction management." Ph.D, National Taiwan University of Science and Technology, Taipei, Taiwan.
    Lah, M. T., Zupančič, B., and Krainer, A. (2005). "Fuzzy control for the illumination and temperature comfort in a test chamber." Building and Environment, 40(12), 1626-1637.
    Leonard, C. A. (1988). "The effects of change orders on productivity " Masters, Concordia University, Montreal, Quebec.
    Liu, G., Shen, Q., Li, H., and Shen, L. (2004). "Factors constraining the development of professional project management in China's construction industry." International Journal of Project Management, 22(3), 203-211.
    Maletic, J. I., and Marcus, A. (2010). "Data Cleansing: A Prelude to Knowledge Discovery." Data Mining and Knowledge Discovery Handbook, O. Maimon, and L. Rokach, eds., Springer US, 19-32.
    Martinez, C., Castillo, O., and Montiel, O. (2008). "Comparison between Ant Colony and Genetic Algorithms for Fuzzy System Optimization." Soft Computing for Hybrid Intelligent Systems, O. Castillo, P. Melin, J. Kacprzyk, and W. Pedrycz, eds., Springer Berlin / Heidelberg, 71-86.
    Moselhi, O., Assem, I., and El-Rayes, K. (2005). "Change Orders Impact on Labor Productivity." Journal of Construction Engineering and Management, 131(3), 354-359.
    Moselhi, O., Leonard, C., and Fazio, P. (1991). "Impact of change orders on construction productivity." Canadian Journal of Civil Engineering, 18(3), 484-492.
    NECA, N. E. C. A. (1983). "Rate of manpower consumption in electrical construction." NECA, Washington, D.C.
    Park, H.-S. (2006). "Conceptual framework of construction productivity estimation." KSCE Journal of Civil Engineering, 10(5), 311-317.
    Park, H.-S., Thomas, S. R., and Tucker, R. L. (2005). "Benchmarking of Construction Productivity." Journal of Construction Engineering and Management, 131(7), 772-778.
    Ross, T. J. (2010). Fuzzy Logic with Engineering Applications, John Wiley & Sons, Ltd, Chichester.
    Shahi, A., Atan, R. B., and Sulaiman, M. N. (2009). "An Effective Fuzzy C-Mean and Type-2 Fuzzy Logic for Weather Forecasting." Journal of Theoritical and Applied Information Technology, 5(5), 556-567.
    Tabachnick, B. G., and Fidell, L. S. (2007). Using Multivariate Statistics (5th Edition), Allyn & Bacon, Boston.
    Tanaka, Y. "An overview of fuzzy logic." Proc., WESCON/'93. Conference Record, 446-450.
    Yongqiao, W., Shouyang, W., and Lai, K. K. (2005). "A new fuzzy support vector machine to evaluate credit risk." Fuzzy Systems, IEEE Transactions on, 13(6), 820-831.
    Zadeh, L. A. (1973). "Outline of a New Approach to the Analysis of Complex Systems and Decision Processes." Systems, Man and Cybernetics, IEEE Transactions on, SMC-3(1), 28-44.
    Zhang, S., Zhang, C., and Yang, Q. (2003). "Data preparation for data mining." Applied Artificial Intelligence, 17(5-6), 375-381.

    QR CODE