A two‐step‐ahead recurrent neural network for stream‐flow forecasting     

Li‐Chiu Chang  Fi‐John Chang  Yen‐Ming Chiang 《水文研究》2004,18(1):81-92

In many engineering problems, such as flood warning systems, accurate multistep‐ahead prediction is critically important. The main purpose of this study was to derive an algorithm for two‐step‐ahead forecasting based on a real‐time recurrent learning (RTRL) neural network that has been demonstrated as best suited for real‐time application in various problems. To evaluate the properties of the developed two‐step‐ahead RTRL algorithm, we first compared its predictive ability with least‐square estimated autoregressive moving average with exogenous inputs (ARMAX) models on several synthetic time‐series. Our results demonstrate that the developed two‐step‐ahead RTRL network has efficient ability to learn and has comparable accuracy for time‐series prediction as the refitted ARMAX models. We then investigated the two‐step‐ahead RTRL network by using the rainfall–runoff data of the Da‐Chia River in Taiwan. The results show that the developed algorithm can be successfully applied with high accuracy for two‐step‐ahead real‐time stream‐flow forecasting. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   

Stochastic simulation of bivariate gamma distribution: a frequency-factor based approach     

Ke-Sheng Cheng  Ju-Chen Hou  Jun-Jih Liou  Yii-Chen Wu  Jie-Lun Chiang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(2):107-122

A frequency-factor based approach for stochastic simulation of bivariate gamma distribution is proposed. The approach involves generation of bivariate normal samples with a correlation coefficient consistent with the correlation coefficient of the corresponding bivariate gamma samples. Then the bivariate normal samples are transformed to bivariate gamma samples using the well-known general equation of hydrological frequency analysis. We demonstrate that the proposed bivariate gamma simulation approach is capable of generating random sample pairs which not only have the desired marginal densities of component random variables but also their correlation coefficient. Scatter plots of simulated bivariate sample pairs also exhibit appropriate linear patterns (dependence structure) that are commonly observed in environmental and hydrological applications. Caution should also be exercised when specifying combinations of coefficients of skewness and the correlation coefficient for bivariate gamma simulation.  相似文献   

Earthquake risk assessment and optimal risk management strategies for Hi-Tech Fabs in Taiwan     

Wen-Ko Hsu  Wei-Ling Chiang  Cheng-Wu Chen 《Natural Hazards》2013,65(3):2063-2076

In this paper, we build an event-based seismic hazard assessment and financial analysis model for Hi-Tech Fabs in Taiwan. As we know, the low occurrence rate, tremendous loss and high uncertainty are characteristics of earthquake disasters. To handle the above issues, the model integrates knowledge from many fields including earth science, seismology, geology, risk management, structural engineering, the insurance profession, financial engineering and facility management. The portfolio of data from the site survey indicates that the model can be used to calculate the event losses (including buildings, contents and business interruption losses); furthermore the average annual loss and loss exceeding probabilities also can be calculated. The total earthquake risk cost, which includes earthquake insurance premiums, average annual retained loss and equivalent annual retrofit cost, is defined as an indicator for selection of optimal risk management strategies.  相似文献   

Application of a feature-based approach to debris flow detection by numerical simulation     

Chih-Wei Lin  Cheng-Wu Chen  Wen-Ko Hsu  Chia-Yen Chen  Chung-Hung Tsai  Yi-Ping Hung  Wei-Ling Chiang 《Natural Hazards》2013,67(2):783-796

A debris flow is a serious natural disaster which can occur anywhere whether in a valley or on a mountain slope, destroying everything it passes through. Debris flows can occur suddenly and cause residents in the path to suffer casualties and property loss. An early warning system is necessary to reduce the damage in order to protect human life and personal property. However, most debris flow detection systems, like wireless sensors, satellite images and radar, are not suitable for general public use. Vision surveillance systems are generally erected in Taiwan as public devices for security. Therefore, we propose a novel debris early warning system that uses a computer vision technique and build a simulation environment to prove the feasibility.  相似文献   

Identification of the controlling factors for hydrological responses by artificial neural networks     

Ruo-Nan Hao  Yue-Ping Xu  Yen-Ming Chiang 《水文研究》2021,35(11):e14420

Identifying the controlling factors for hydrological responses is of great importance for artificial neural network-based flood forecasting models, which are often hindered by the lack of physical mechanisms. To explore the first-order controlling factors of hydrograph patterns, a hybrid neural network was designed to analyse the impacts of potential driving variables with different temporal and spatial resolutions on hydrograph patterns. The Jinhua River Basin in Southeast China was used as an example in this study. Flood events with different hydrograph patterns and six external factors denoting potential controlling factors were individually classified into specific clusters using self-organizing maps (SOMs). Based on the back-propagation neural network (BPNN) and leave-one-out cross-validation methods, the controlling factors of different flood patterns were identified by comparing the performances of flood simulation models trained with datasets before and after the potential controlling factor classification. The results showed that (i) the classification of controlling factors indicating various runoff regimes significantly improved the performance of data-driven models in flood simulation in terms of correlation coefficient, Nash-Sutcliffe coefficient, and normalized root mean square error; (ii) the spatial distribution of antecedent soil moisture and vegetation conditions as well as the temporal distribution of rainfall dominated different hydrograph patterns; and (iii) the transition of dominant rainfall-runoff processes could be identified in an individual flood event using the hybrid SOM–BPNN model, indicating the varying influence of potential controlling factors on streamflow. Overall, the hybrid neural network models trained with datasets classified by controlling factors provide a general analytical framework to identify the governing dynamics for different flood patterns and improve the accuracy of flood simulations. Additionally, more attention should be devoted to improving the time to peak error of hydrological models, which cannot be settled by data-driven models trained with different data-splitting strategies.  相似文献   

Automatic alignment of contemporary vector data and georeferenced historical maps using reinforcement learning     

Weiwei Duan  Yao-Yi Chiang  Stefan Leyk  Johannes H. Uhl  Craig A. Knoblock 《International journal of geographical information science》2020,34(4):824-849

ABSTRACT

With large amounts of digital map archives becoming available, automatically extracting information from scanned historical maps is needed for many domains that require long-term historical geographic data. Convolutional Neural Networks (CNN) are powerful techniques that can be used for extracting locations of geographic features from scanned maps if sufficient representative training data are available. Existing spatial data can provide the approximate locations of corresponding geographic features in historical maps and thus be useful to annotate training data automatically. However, the feature representations, publication date, production scales, and spatial reference systems of contemporary vector data are typically very different from those of historical maps. Hence, such auxiliary data cannot be directly used for annotation of the precise locations of the features of interest in the scanned historical maps. This research introduces an automatic vector-to-raster alignment algorithm based on reinforcement learning to annotate precise locations of geographic features on scanned maps. This paper models the alignment problem using the reinforcement learning framework, which enables informed, efficient searches for matching features without pre-processing steps, such as extracting specific feature signatures (e.g. road intersections). The experimental results show that our algorithm can be applied to various features (roads, water lines, and railroads) and achieve high accuracy.  相似文献   

A LiDAR study of the effective size of cirrus ice crystals over Chung-Li,Taiwan     

Subrata Kumar Das  Jan-Bai Nee  Chih-Wei Chiang 《Journal of Atmospheric and Solar》2010,72(9-10):781-788

In this paper, we estimated the effective size of ice crystals in cirrus clouds using fall velocity derived from LiDAR (light detection and ranging) measurements at Chung-Li (24.58°N, 121.1°E), Taiwan. Nine shapes of the ice crystals, viz. hexagonal plates, hexagonal columns, rimed long columns, crystals with sector-like branches, broad-branched crystals, stellar crystal with broad arms, side planes, bullet rosettes and assemblages of planar poly-crystals of specific dimensions have been analyzed. The results show that the lidar derived most probable mean effective size of ice crystals is 340±180 μm with a dominant size range of 200–300 μm. The lidar derived mean effective size of cirrus crystals are parameterized in terms of cloud mid-height temperature as well as optical depth. The discussed method will be useful to study the most probable effective size distribution of ice crystals in cirrus cloud.  相似文献   

Heterotrophic bacterial and <Emphasis Type="Italic">Synechococcus</Emphasis> spp. Growth and mortality along the inshore-offshore in the East China Sea in summer     

An-Yi Tsai  Gwo-Ching Gong  Robert W. Sanders  Kuo-Ping Chiang  Chien-Fu Chao 《Journal of Oceanography》2012,68(1):151-162

This study used the dilution method to examine growth and grazing rates of heterotrophic bacteria and an autotrophic picoplankton, Synechococcus spp., from 1 to 11 July 2007 in the East China Sea. The main influence of oceanographic conditions in this aquatic system was the introduction of fresh, high-nutrient water from Changjiang River and the extremely nutrient-poor, high-salinity waters of Kuroshio Water. In these experiments, deviation from linearity in the relationship between dilution factor and net growth rate was significant in a large number of cases. Growth rates for heterotrophic bacteria ranged from 0.024 to 0.24, and for Synechococcus spp. from 0.03 to 0.21 h⁻¹. Grazing rates ranged from 0.02 to 0.19 and 0.01 to 0.13 h⁻¹, respectively. The spatial variations of Synechococcus spp. production to the primary production ratio (SP/PP) were low (<5%) in high Chl a environments and increased exponentially in low Chl a environments, indicating that Synechococcus spp. contributes to a large extent to the photosynthetic biomass in the open sea, especially in the more oligotrophic Kuroshio Water. Furthermore, the results of our dilution experiments suggest that nanoflagellates largely depend on heterotrophic bacteria as an important energy source. On average, heterotrophic bacteria contributes to 76 and 59% of carbon consumed by nanoflagellates within the plume (salinity <31) and outside of it (salinity >31).  相似文献   

Implications of coseismic groundwater level changes observed at multiple-well monitoring stations     

Yeeping Chia  Jessie J. Chiu  Yi-Hsuan Chiang  Tsai-Ping Lee  Yih-Min Wu  Ming-Jame Horng 《Geophysical Journal International》2008,172(1):293-301

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Preliminary results of the Japan-Taiwan joint survey on combining ocean radar data in the Kuroshio upstream region     

Kaoru Ichikawa  Wen Chang Yang  Akihiko Morimoto  Yutaka Yoshikawa  Shigeo Sugitani  Wen-Shan Chiang  Jian-Wu Lai  En Yu Liang  Cho-Teng Liu  Chang-Wei Lee  Kei Yufu  Moeto Kyushima  Satoshi Fujii  Tomoharu Senju  Yoshihiko Ide 《Ocean Science Journal》2013,48(1):141-148

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