지하수위 영향인자에 따른 인공신경망 기반의 지하수위 예측 성능 분석

목차 (Table of Contents)

• Abstract
• 요지
• 1. 서론
• 2. 인공신경망(artificial neural network, ANN)과 지하수위 예측
• 3. 지하수위 영향인자 분석
• 4. 영향인자에 따른 지하수위 예측
• 5. 결론
• 참고문헌 (References)

참고문헌 (Reference)

1 양정석, "한국의 지하수위와 강우이동평균간의 상관관계" 대한토목학회 31 (31): 265-276, 2011

2 김인철, "지반 및 수문특성을 고려한 하천인근 지역의 지하수위 변동 영향인자 분석" 응용생태공학회 5 (5): 72-81, 2018

3 김인철, "인공신경망을 이용한 지하수위 예측과 계절효과 반영을 위한 입력치의 영향" 응용생태공학회 5 (5): 125-133, 2018

4 Wen, X., "Wavelet and Adaptive Neuro-fuzzy Inference System Conjunction Model for Groundwater Level Predicting in a Coastal Aquifer" 26 : 1203-1215, 2015

5 Mohammad A. Shahriar, "Water Table Correction Factors for Settlements of Shallow Foundations in Granular Soils" American Society of Civil Engineers (ASCE) 15 (15): 06014015-, 2015

6 Uddameri, V., "Using Statistical and Artificial Neural Network Models to Forecast Potentiometric Levels at a Deep Well in South Texas" 51 : 885-895, 2007

7 Wilhite, D. A., "Understanding the Drought Phenomenon : The Role of Definitions" 10 : 110-120, 1985

8 Nourani, V., "Spatiotemporal Groundwater Level Modeling Using Hybrid Artificial Intelligence-meshless Method" 536 : 10-25, 2016

9 Shamsudduha, M., "Resent Trends in Groundwater Levels in a Highly Seasonal Hydrological System : The Ganges-Brahmaputra-Meghna Delta" 13 : 2373-2385, 2009

10 Batelaan, O., "Regional Groundwater Discharge : Phreatophyte Mapping, Groundwater Modeling and Impact Analysis of Land-use Change" 275 : 86-108, 2003

11 Kim, I., "Proposed Correlation Model for Groundwater Level Prediction based on River Stage Considering Changes in Hydrological and Geological Conditions" 24 (24): 1-14, 2019

12 Incheol Kim, "Prediction Model for Spatial and Temporal Variation of Groundwater Level Based on River Stage" American Society of Civil Engineers (ASCE) 23 (23): 06018002-, 2018

13 Serrano, S. E., "Modeling Transient Stream/aquifer Interaction with the Non-linear Boussinesq Equation and its Analytical Solution" 206 : 145-255, 1998

14 Ausilio, E., "Influence of Groundwater on the Bearing Capacity of Shallow Foundations" 42 : 663-672, 2005

15 Yasuhara, K., "Influence of Global Warming on Coastal Infrastructural Instability" 2 : 13-25, 2007

16 Dawson, C. W., "Hydrological Modelling Using Artificial Neural Networks" 25 (25): 80-108, 2001

17 Sahoo, S., "Groundwater-level Prediction Using Multiple Linear Regression and Artificial Neural Network Techniques : A Comparative Assessment" 21 : 1865-1887, 2013

18 Daliakopoulos, I. N., "Groundwater Level Forecasting Using Artificial Neural Networks" 309 : 229-240, 2005

19 Park, D., "Groundwater Effect Factors for the Load-carrying behavior of Footings from Hydraulic Chamber Load Tests" 30 (30): 440-451, 2017

20 Gerken, W. C., "Genetic Algorithm for Optimization and Specification of a Neuron Model" 69 : 1039-1042, 2006

21 Park, D., "Effect of Groundwater Fluctuation on Load Carrying Performance of Shallow Foundation" 18 (18): 575-584, 2019

22 Hoque, M., "Declining Groundwater Level and Aquifer Dewatering in Dhaka Metropolitan Area, Bangladesh : Causes and Quantification" 15 : 1523-1534, 2007

23 Kim, I., "Comparative Influences of Precipitation and River Stage on Groundwater Levels in Near-river Areas" 8 (8): 1-16, 2016

24 Trichakis, I. C., "Artificial Neural Network(ANN)based Modeling for Karstic Groundwater Level Simulation" 25 : 1143-1152, 2011

25 Guttman, N. B., "Accepting the Standardized Precipitation Index : A Calculation Algorithm" 35 (35): 311-322, 1999

26 Rajaee, T., "A Review of the Artificial Intelligence Methods in Groundwater Level Modeling" 572 : 336-351, 2019

27 Coppola, E. A., "A Neural Network Model for Predicting Aquifer Water Level Elevations" 43 (43): 231-241, 2005