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Shoreline Change Estimation From Survey Image Coordinates And Neural Network Approximation

Tienfuan Kerh, Hsienchang Lu, Rob Saunders
2014 Zenodo  
Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of
more » ... ne can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.
doi:10.5281/zenodo.1091858 fatcat:jt76ybvq45c7fikrbt2cztjypu

Neural Network Approach for Analyzing Seismic Data to Identify Potentially Hazardous Bridges

Tienfuan Kerh, Chuhsiung Huang, David Gunaratnam
2011 Mathematical Problems in Engineering  
Examining the effect of strong ground motions on civil engineering structures is important as it concerns public safety. The present study initially selects twenty-one bridges with lengths over 500 m in the Formosa freeway of Taiwan and collects a series of recorded seismic data from checking stations near these bridges. Then, three seismic parameters including focal depth, epicenter distance, and local magnitude are used as the input data sets, and a model for estimating the key seismic
more » ... er—peak ground acceleration—for each of bridge site is developed by using the neural network approach. This model is finally combined with a simple distribution method and a new weight-based method to estimate peak ground acceleration at each of the bridges along the freeway. Based on the seismic design value in the current building code as the evaluation criteria, the model identifies five bridges, out of all the bridges investigated, as having the potential to be subjected to significantly higher horizontal peak ground accelerations than that recommended for design in the building code. The method presented in this study hence provides a valuable reference for dealing with nonlinear seismic data by developing neural network model, and the approach presented is also applicable to other areas of interest around the world.
doi:10.1155/2011/464353 fatcat:botuij2tfjf4pnwmfimldcz6vu

Artificial neural network for modeling reference evapotranspiration complex process in Sudano-Sahelian zone

Seydou Traore, Yu-Min Wang, Tienfuan Kerh
2010 Agricultural Water Management  
A B S T R A C T The major problem when dealing with modeling evapotranspiration process is its nonlinear dynamic high complexity. Researchers developed reference evapotranspiration (ET-ref) estimation models in rich and poor data situations. Thus, the well-known Penman-Monteith (PM) model always performs the highest accuracy results of ET-ref from a rich data situation. Its application in many areas particularly in developing countries such as Burkina Faso has been limited by the unavailability
more » ... of the enormous climatic data required. In such circumstances, simple empirical Hargreaves (HARG) equation is often used despite of its non-universal suitability. The present study assesses the artificial neural network (ANN) performance in ET-ref modeling based on temperature data in Bobo-Dioulasso region, located in the Sudano-Sahelian zone of Burkina Faso. The models of feed forward backpropagation neural network (BPNN) algorithm type ANN and Hargreaves (HARG) were employed to study their performance by comparing with the true PM. From the statistical results, BPNN temperature-based models perform better than HARG. Beside, when wind speed is introduced into the neural network models, the coefficient of determination (r 2 ) increases significantly up to 9.52%. While, sunshine duration and relative humidity might cause only 3.51 and 6.69% of difference, respectively. Wind is found to be the most effective variable extremely required for modeling with high accuracy the nonlinear complex process of ET-ref in the Sudano-Sahelian zone of Burkina Faso. ß
doi:10.1016/j.agwat.2010.01.002 fatcat:5qsgzpjcobe3ndnicxlr2bop2i

Estimation of groundwater recharge using the chloride mass-balance method, Pingtung Plain, Taiwan

Cheh-Shyh Ting, Tienfuan Kerh, Chiu-Jung Liao
1998 Hydrogeology Journal  
Due to rapid economic growth in the Pingtung Plain of Taiwan, the use of groundwater resources has changed dramatically. Over-pumping of the groundwater reservoir, which lowers hydraulic heads in the aquifers, is not only affecting the coastal area negatively but has serious consequences for agriculture throughout the plain. In order to determine the safe yield of the aquifer underlying the plain, a reliable estimate of groundwater recharge is desirable. In the present study, for the first
more » ... the chloride mass-balance method is adopted to estimate groundwater recharge in the plain. Four sites in the central part were chosen to facilitate the estimations using the ion-chromatograph and Thiessen polygon-weighting methods. Based on the measured and calculated results, in all sites, including the mountain and river boundaries, recharge to the groundwater is probably 15% of the annual rainfall, excluding recharge from additional irrigation water. This information can improve the accuracy of future groundwater-simulation and management models in the plain. Résumé Du fait de la croissance économique rapide de la plaine de Pingtung à Taiwan, l'utilisation des ressources en eau souterraine s'est considérablement modifié. La surexploitation des aquifères, qui a abaissé le niveau des nappes, n'affecte pas seulement la région côtière, mais a de sérieuses répercutions sur l'agriculture dans toute la plaine. Afin de déterminer les res-Resumen Debido al rápido crecimiento económico de la zona de la Llanura de Pingtung, Taiwan, el uso de los recursos de agua subterránea ha cambiado radicalmente. La sobreexplotación, con el consiguiente descenso de los niveles piezométricos en los acuíferos, no sólo afecta las áreas costeras, sino que está teniendo consecuencias importantes para la agricultura de la zona. Para determinar la extracción sostenible en el acuífero, es deseable una buena estimación de la recarga. En este estudio se adopta por primera vez el método de balance de cloruros para estimar la recarga en el llano. Se seleccionaron cuatro puntos en la parte central para facilitar las estimaciones mediante los métodos de cromatógrafo iónico y de polígonos de Thiessen. A partir de los resultados medidos y calculados en toda la zona, e incluyendo los contornos de montañ as y ríos, la recarga subterránea es de cerca del 15% de la precipitación anual, excluyendo la recarga que se produce por riego adicional. Este dato permitirá mejorar la precisión de los modelos de simulación de flujo y de gestión que se realizarán en el futuro. Key words Taiwan 7 groundwater recharge 7 water budget 7 chloride mass-balance method
doi:10.1007/s100400050151 fatcat:kajjimm2sngybfsfvn7hv325ga

Investigating Nonlinear Shoreline Multiperiod Change from Orthophoto Map Information by Using a Neural Network Model

Tienfuan Kerh, Hsienchang Lu, Rob Saunders
2014 Mathematical Problems in Engineering  
The effects of extreme weather and overdevelopment may cause some coastal areas to exhibit erosion problems, which in turn may contribute to creating disasters of varying scale, particularly in regions comprising islands. This study used aerial survey information from three periods (1990, 2001, and 2010) and used graphical software to establish the spatial data of six beaches surrounding the island of Taiwan. An overlaying technique was then implemented to compare the sandy area of each beach
more » ... the aforementioned study periods. In addition, an artificial neural network model was developed based on available digitised coordinates for predicting coastline variation for 2015 and 2020. An onsite investigation was performed using a global positioning system for comparing the beaches. The results revealed that two beaches from this study may have experienced significant changes in total sandy areas under a statistical 95% confidence interval. The proposed method and the result of this study may provide a valuable reference in follow-up research and applications.
doi:10.1155/2014/782525 fatcat:ctxgmbwdcvbu5pltcwxsj2tjmi

Experimental Evaluation of Anti-stripping Additives Mixing in Road Surface Pavement Materials

Tienfuan Kerh, Yu-Min Wang, Yulern Lin
2005 American Journal of Applied Sciences  
Most road surfaces in Taiwan are paved with asphalt concrete but the phenomena of rutting, cracking and stripping of the pavement are frequently occurring due to the effects of traffic flow, thermal variation and water erosion caused by rain. In this study, a series of experiments were performed to examine the effectiveness of anti-stripping fillers, which include; rock flour, rock flour with 1% lime and rock flour with 1% cement, respectively, in the mixture of asphalt concrete. The
more » ... l mixing results showed that the case of rock flour with 1% lime has a relatively better performance in several categories including stability value, flow value, retained strength, wrapped asphalt rate in grains, resilient modulus, dynamic stability and rate of rutting deformation. The evaluated information implies that this filler can increase the asphalt concrete's abilities to resist rutting deformation and stripping of the road surface, thus increasing the durability. The results also provide a good reference for using in road construction with similar regional characteristics to Taiwan.
doi:10.3844/ajassp.2005.1427.1433 fatcat:5s27ezthffae3aapcyi35j722e

Neural networks approach and microtremor measurements in estimating peak ground acceleration due to strong motion

Tienfuan Kerh, David Chu
2002 Advances in Engineering Software  
Peak ground acceleration is a very important factor that must be considered in construction site for examining the potential damage resulting from earthquake. The actual records by seismometer at stations related to the site may be taken as a basis, but a reliable estimating method may be useful for providing more detailed information of the strong motion characteristics. Therefore, the purpose of this study was by using back-propagation neural networks to develop a model for estimating peak
more » ... und acceleration at two main line sections of Kaohsiung Mass Rapid Transit in Taiwan. Additionally, the microtremor measurements with Nakamura transformation technique were taken to further validate the estimations. Three neural networks models with different inputs including epicentral distance, focal depth and magnitude of the earthquake records were trained and the output results were compared with available nonlinear regression analysis. The comparisons exhibited that the present neural networks model did have a better performance than that of the other methods, as the calculation results were more reasonable and closer to the actual seismic records. Besides, the distributions of estimating peak ground acceleration from both of computations and measurements might provide valuable information from theoretical and practical standpoints. q
doi:10.1016/s0965-9978(02)00081-9 fatcat:4kmiryjhsvds7l2szwr5dwtlay


Tienfuan Kerh, Yen-Ming Chen, I Tsou
2005 Journal of Marine Science and Technology  
An experimental method, the so-called color-coded Digital Particle Tracking Velocimetry system was set up in this study to investigate viscous flow through an artificial bileaflet valve with three different opening angles, 5°, 30°, and 45°, respectively. An oscilloscope that generated stable wave speed was taken to calibrate measuring result of the equipment. Besides, a fully developed pipe flow case was used to check the reliability of experimental system, and a statistical t-test was
more » ... to further enhance the comparison of analytical solution and measurement. From the details of randomly distributed velocities, interpolated velocity components, and velocity profiles for the studied flow case, it could be observed that three jetlike flows through upper, central and lower parts of the two leaflets occurred in this flow configuration. Due to the effect of shear layer at wall boundary and at valve wake, the jet-like flows interfered with each other, and caused that the larger the opening angle, the stronger the recirculation region at downstream of valve structure. As a result, the velocity distributions exhibited more oscillating phenomenon in both axial and radius directions for larger opening angle case. From error analysis, although these measured results might involve some uncertainties and incompleteness, they might provide basic flow characteristics in this type of flow case and relative applications.
doi:10.51400/2709-6998.2098 fatcat:vmdv33srqzb5hfo3zq6a7ttctq

Nonlinear Autoregressive Network with the Use of a Moving Average Method for Forecasting Typhoon Tracks

Tienfuan Kerh, Shin-Hung Wu
2017 International Journal of Artificial Intelligence & Applications  
Authors Tienfuan Kerh received his Ph.D degree in Civil Engineering from University of Southern California, USA.  ... 
doi:10.5121/ijaia.2017.8605 fatcat:2y4gxoysrfaadbrxdm52lcyrxm

Seismic Design Value Evaluation Based on Checking Records and Site Geological Conditions Using Artificial Neural Networks

Tienfuan Kerh, Yutang Lin, Rob Saunders
2013 Abstract and Applied Analysis  
This study proposes an improved computational neural network model that uses three seismic parameters (i.e., local magnitude, epicentral distance, and epicenter depth) and two geological conditions (i.e., shear wave velocity and standard penetration test value) as the inputs for predicting peak ground acceleration—the key element for evaluating earthquake response. Initial comparison results show that a neural network model with three neurons in the hidden layer can achieve relatively better
more » ... formance based on the evaluation index of correlation coefficient or mean square error. This study further develops a new weight-based neural network model for estimating peak ground acceleration at unchecked sites. Four locations identified to have higher estimated peak ground accelerations than that of the seismic design value in the 24 subdivision zones are investigated in Taiwan. Finally, this study develops a new equation for the relationship of horizontal peak ground acceleration and focal distance by the curve fitting method. This equation represents seismic characteristics in Taiwan region more reliably and reasonably. The results of this study provide an insight into this type of nonlinear problem, and the proposed method may be applicable to other areas of interest around the world.
doi:10.1155/2013/242941 fatcat:py4fg57hjbfq5aictmlh25cvsi


2001 International Conference on Aerospace Sciences and Aviation Technology  
Tienfuan Kerh, [3] , investigated numerically the interaction of a viscous incompressible fluid with a control valve which was conducted by using the finite element method and the network approach.  ... 
doi:10.21608/asat.2001.24773 fatcat:xirhltmc7jd7rbsldir3xntk2m