Fuzzy and Neural Network Models for Analyses of Piles
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[1] Michael M. Blendy. Rational Approach to Pile Foundations , 1980 .
[2] A. Goh. Seismic liquefaction potential assessed by neural networks , 1994 .
[3] P. Rao. Statistical Research Methods in the Life Sciences , 1997 .
[4] Charles W. Butler,et al. Naturally intelligent systems , 1990 .
[5] J. Kérisel,et al. FIELD TESTS OF PILES IN SAND , 1972 .
[6] M. R. Sharp,et al. The Use of Superposition for Evaluating Pile Capacity , 2002 .
[7] Jyh-Shing Roger Jang,et al. ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..
[8] Joseph E. Bowles,et al. Analytical and computer methods in foundation engineering , 1974 .
[9] Tuncer B. Edil,et al. ESTIMATING SOIL/PILE SET-UP , 2003 .
[10] N. R. McCammon,et al. SOME LOADING TESTS ON LONG PIPE PILES , 1970 .
[11] J. H. Long,et al. Measured and Predicted Capacity of H-Piles , 2002 .
[12] Mehmet Iscimen,et al. Shearing Behavior Of Curved Interfaces , 2004 .
[13] Weng Tat Chan,et al. NEURAL NETWORK: AN ALTERNATIVE TO PILE DRIVING FORMULAS , 1995 .
[14] Musharraf Zaman,et al. Modeling of soil behavior with a recurrent neural network , 1998 .
[15] Kyriazis Pitilakis,et al. Earthquake Geotechnical Engineering , 2007 .
[16] J H Garrett,et al. WHERE AND WHY ARTIFICIAL NEURAL NETWORKS ARE APPLICABLE IN CIVIL ENGINEERING , 1994 .
[17] J Biarez,et al. BEARING CAPACITY AND SETTLEMENT OF PILE FOUNDATIONS , 1977 .
[18] Philipp Slusallek,et al. Introduction to real-time ray tracing , 2005, SIGGRAPH Courses.
[19] M. Pando. A Laboratory and Field Study of Composite Piles for Bridge Substructures , 2006 .
[20] Artur Dubrawski,et al. HPC Strength Prediction Using Artificial Neural Network , 1995 .
[21] Timothy Masters,et al. Practical neural network recipes in C , 1993 .
[22] Aleksandar S. Vesic,et al. Tests on Instrumented Piles, Ogeechee River Site , 1970 .
[23] D. Hammerstrom,et al. Working with neural networks , 1993, IEEE Spectrum.
[24] F. Tavenas,et al. Load Tests Results on Friction Piles in Sand , 1971 .
[25] Mohamad H. Hassoun. Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems [Book review] , 1996, IEEE Transactions on Neural Networks.
[26] Harry G. Poulos,et al. Pile foundation analysis and design , 1980 .
[27] U Bergdahl,et al. BEARING CAPACITY OF DRIVEN FRICTION PILES IN LOOSE SAND , 1976 .
[28] Mohammed A. Gabr. MODEL FOR CAPACITY OF SINGLE PILES IN SAND USING FUZZY SETS a , 1991 .
[29] Hideaki Kishida,et al. Frictional Resistance at Yield between Dry Sand and Mild Steel , 1986 .
[30] Frank Rausche,et al. DESIGN AND CONSTRUCTION OF DRIVEN PILE FOUNDATIONS - VOLUME I , 1997 .
[31] Russell C. Eberhart,et al. Neural network PC tools: a practical guide , 1990 .
[32] G. David Garson,et al. Interpreting neural-network connection weights , 1991 .
[33] Raúl Rojas,et al. Neural Networks - A Systematic Introduction , 1996 .
[34] Vishnu Diyaljee,et al. Influence of Subsoil Characteristics on Embedment Depths and Load Capacity of Large Diameter Pipe Piles , 2002 .
[35] Anthony T. C. Goh,et al. PREDICTION OF PILE CAPACITY USING NEURAL NETWORKS , 1997 .
[36] Paul Engeling,et al. High Capacity Pile Foundations for China Steel Corporation Integrated Steel Mill , 1980 .
[37] Department of Transportation Federal Highway Administration 23 Cfr Part 515 Asset Management Plan Background , 2022 .
[38] M. R. Sayeh,et al. Pattern Recognition Using A Neural Network , 1988, Other Conferences.
[39] Holger R. Maier,et al. PREDICTING SETTLEMENT OF SHALLOW FOUNDATIONS USING NEURAL NETWORKS , 2002 .
[40] Lakhmi C. Jain. Recent Advances in Artificial Neural Networks , 2000 .
[41] Holger R. Maier,et al. ARTIFICIAL NEURAL NETWORK APPLICATIONS IN GEOTECHNICAL ENGINEERING , 2001 .
[42] Charles J Winter,et al. Applying Separate Safety Factors to End-of-Drive and Set-Up Components of Driven Pile Capacity , 2005 .
[43] Robert M. Pap,et al. Handbook of neural computing applications , 1990 .
[44] G G Goble,et al. FOUNDATION DESIGN AND EVALUATION FOR WINNEMUCCA VIADUCT , 1982 .
[45] Lucia Faravelli,et al. Use of Adaptive Networks in Fuzzy Control of Civil Structures , 1996 .
[46] Tarek Hegazy,et al. Developing Practical Neural Network Applications Using Back‐Propagation , 1994 .
[47] Herbert A. Simon,et al. WHY SHOULD MACHINES LEARN , 1983 .
[48] Má. PATTERN RECOGNITION USING NEURAL NETWORKS , 2008 .
[49] C. S. George Lee,et al. Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems , 1996 .
[50] Laurene V. Fausett,et al. Fundamentals Of Neural Networks , 1994 .
[51] In Mo Lee,et al. Prediction of pile bearing capacity using artificial neural networks , 1996 .
[52] Murray Smith,et al. Neural Networks for Statistical Modeling , 1993 .
[53] Walter G. Brusey,et al. SETUP AND RELAXATION IN GLACIAL SAND , 1994 .
[54] H. Guterman,et al. Knowledge extraction from artificial neural network models , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.
[55] A S Vesic,et al. DESIGN OF PILE FOUNDATIONS , 1977 .
[56] S. Rajasekaran,et al. Artificial fuzzy neural networks in civil engineering , 1996 .
[57] D. H. Lee,et al. Mapping Slope Failure Potential Using Fuzzy Sets , 1992 .
[58] Thomas M. Gurtowski,et al. Compression Load Tests on Concrete Piles in Alluvium , 1984 .
[59] David Bailey,et al. How to develop neural-network applications , 1990 .
[60] C. I. Mansur,et al. Pile Tests, Low-Sill Structures, Old River, La. , 1956 .
[61] Roger Howard,et al. High Capacity Pipe Piles at San Francisco International Airport , 2002 .
[62] Stephen K. Law,et al. SETUP AND RELAXATION IN GLACIAL SAND. DISCUSSIONS AND CLOSURE , 1996 .
[63] Jun Wang,et al. Fuzzy neural network models for liquefaction prediction , 2002 .
[64] Adrian J. Shepherd,et al. Second-order methods for neural networks - fast and reliable training methods for multi-layer perceptrons , 1997, Perspectives in neural computing.
[65] R. Lippmann,et al. An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.
[66] 上杉 守道,et al. FRICTIONAL RESISTANCE AT YIELD BETWEEN DRY SAND AND MILD STEEL , 1986 .
[67] D Milovic,et al. THE ULTIMATE BEARING CAPACITY OF PILES DETERMINED BY LOAD TESTS , 1976 .
[68] J. F. Nauroy,et al. The effects of time on the capacity of pipe piles in dense marine sand , 1996 .
[69] G. R. Dodagoudar,et al. RELIABILITY ANALYSIS OF SLOPES USING FUZZY SETS THEORY , 2000 .
[70] Howard B. Demuth,et al. Neutral network toolbox for use with Matlab , 1995 .
[71] Chuen-Tsai Sun,et al. Neuro-fuzzy And Soft Computing: A Computational Approach To Learning And Machine Intelligence [Books in Brief] , 1997, IEEE Transactions on Neural Networks.
[72] Gary Axelsson. A Conceptual Model of Pile Set-Up for Driven Piles in Non-Cohesive Soil , 2002 .
[73] James H. Garrett,et al. Knowledge-Based Modeling of Material Behavior with Neural Networks , 1992 .
[74] Bengt H. Fellenius,et al. DYNAMIC AND STATIC TESTING IN SOIL EXHIBITING SET-UP , 1989 .
[75] Hani H. Titi,et al. Numerical Procedure for Predicting Pile Capacity—Setup/Freeze , 1999 .
[76] James H. Long,et al. Measured Time Effects for Axial Capacity of Driven Piling , 1999 .
[77] Van E. Komurka,et al. Incorporating Set-Up and Support Cost Distributions into Driven Pile Design , 2004 .
[78] Jing-Wen Chen,et al. A fuzzy methodology for evaluation of the liquefaction potential , 1997 .
[79] Andrew J. Whittle,et al. Prediction of Pile Setup in Clay , 1999 .
[80] V E Komurka,et al. INCORPORATING SET-UP AND SUPPORT COST DISTRIBUTIONS INTO DRIVE PILE DESIGN. IN: CURRENT PRACTICES AND FUTURE TRENDS IN DEEP FOUNDATIONS , 2004 .