Search results for: river flow time series
8905 Application of Extreme Learning Machine Method for Time Series Analysis
Authors: Rampal Singh, S. Balasundaram
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In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.Keywords: Chaotic time series, Extreme learning machine, Generalization performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35078904 Streamflow Modeling for a Small Watershed Using Limited Hydrological Data
Authors: S. Chuenchooklin
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This research was conducted in the Pua Watershed whereas located in the Upper Nan River Basin in Nan province, Thailand. Nan River basin originated in Nan province that comprises of many tributary streams to produce as inflow to the Sirikit dam provided huge reservoir with the storage capacity of 9510 million cubic meters. The common problems of most watersheds were found i.e. shortage water supply for consumption and agriculture utilizations, deteriorate of water quality, flood and landslide including debris flow, and unstable of riverbank. The Pua Watershed is one of several small river basins that flow through the Nan River Basin. The watershed includes 404 km2 representing the Pua District, the Upper Nan Basin, or the whole Nan River Basin, of 61.5%, 18.2% or 1.2% respectively. The Pua River is a main stream producing all year streamflow supplying the Pua District and an inflow to the Upper Nan Basin. Its length approximately 56.3 kilometers with an average slope of the channel by 1.9% measured. A diversion weir namely Pua weir bound the plain and mountainous areas with a very steep slope of the riverbed to 2.9% and drainage area of 149 km2 as upstream watershed while a mild slope of the riverbed to 0.2% found in a river reach of 20.3 km downstream of this weir, which considered as a gauged basin. However, the major branch streams of the Pua River are ungauged catchments namely: Nam Kwang and Nam Koon with the drainage area of 86 and 35 km2 respectively. These upstream watersheds produce runoff through the 3-streams downstream of Pua weir, Jao weir, and Kang weir, with an averaged annual runoff of 578 million cubic meters. They were analyzed using both statistical data at Pua weir and simulated data resulted from the hydrologic modeling system (HEC–HMS) which applied for the remaining ungauged basins. Since the Kwang and Koon catchments were limited with lack of hydrological data included streamflow and rainfall. Therefore, the mathematical modeling: HEC-HMS with the Snyder-s hydrograph synthesized and transposed methods were applied for those areas using calibrated hydrological parameters from the upstream of Pua weir with continuously daily recorded of streamflow and rainfall data during 2008-2011. The results showed that the simulated daily streamflow and sum up as annual runoff in 2008, 2010, and 2011 were fitted with observed annual runoff at Pua weir using the simple linear regression with the satisfied correlation R2 of 0.64, 062, and 0.59, respectively. The sensitivity of simulation results were come from difficulty using calibrated parameters i.e. lag-time, coefficient of peak flow, initial losses, uniform loss rates, and missing some daily observed data. These calibrated parameters were used to apply for the other 2-ungauged catchments and downstream catchments simulated.
Keywords: Streamflow, hydrological model, ungauged catchments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19778903 Model-free Prediction based on Tracking Theory and Newton Form of Polynomial
Authors: Guoyuan Qi , Yskandar Hamam, Barend Jacobus van Wyk, Shengzhi Du
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The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.Keywords: Forecast, model-free predictor, prediction, time series
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17698902 Two-Dimensional Modeling of Seasonal Freeze and Thaw in an Idealized River Bank
Authors: Jiajia Pan, Hung Tao Shen
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Freeze and thaw occurs seasonally in river banks in northern countries. Little is known on how the riverbank soil temperature responds to air temperature changes and how freeze and thaw develops in a river bank seasonally. This study presents a two-dimensional heat conduction model for numerical investigations of seasonal freeze and thaw processes in an idealized river bank. The model uses the finite difference method and it is convenient for applications. The model is validated with an analytical solution and a field case with soil temperature distributions. It is then applied to the idealized river bank in terms of partially and fully saturated conditions with or without ice cover influence. Simulated results illustrate the response processes of the river bank to seasonal air temperature variations. It promotes the understanding of freeze and thaw processes in river banks and prepares for further investigation of frost and thaw impacts on riverbank stability.Keywords: Freeze and thaw, river banks, 2D model, heat conduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3988901 Signal Processing Approach to Study Multifractality and Singularity of Solar Wind Speed Time Series
Authors: Tushnik Sarkar, Mofazzal H. Khondekar, Subrata Banerjee
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This paper investigates the nature of the fluctuation of the daily average Solar wind speed time series collected over a period of 2492 days, from 1st January, 1997 to 28th October, 2003. The degree of self-similarity and scalability of the Solar Wind Speed signal has been explored to characterise the signal fluctuation. Multi-fractal Detrended Fluctuation Analysis (MFDFA) method has been implemented on the signal which is under investigation to perform this task. Furthermore, the singularity spectra of the signals have been also obtained to gauge the extent of the multifractality of the time series signal.Keywords: Detrended fluctuation analysis, generalized Hurst exponent, holder exponents, multifractal exponent, multifractal spectrum, singularity spectrum, time series analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12998900 Estimation of the Parameters of Muskingum Methods for the Prediction of the Flood Depth in the Moudjar River Catchment
Authors: Fares Laouacheria, Said Kechida, Moncef Chabi
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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.
Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11798899 Using Time-Series NDVI to Model Land Cover Change: A Case Study in the Berg River Catchment Area, Western Cape, South Africa
Authors: A. S. Adesuyi, Z. Munch
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This study investigates the use of a time-series of MODIS NDVI data to identify agricultural land cover change on an annual time step (2007 - 2012) and characterize the trend. Following an ISODATA classification of the MODIS imagery to selectively mask areas not agriculture or semi-natural, NDVI signatures were created to identify areas cereals and vineyards with the aid of ancillary, pictometry and field sample data for 2010. The NDVI signature curve and training samples were used to create a decision tree model in WEKA 3.6.9 using decision tree classifier (J48) algorithm; Model 1 including ISODATA classification and Model 2 not. These two models were then used to classify all data for the study area for 2010, producing land cover maps with classification accuracies of 77% and 80% for Model 1 and 2 respectively. Model 2 was subsequently used to create land cover classification and change detection maps for all other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices. Over the years as predicted by the land cover classification. Forty one percent of the catchment comprised of cereals with 35% possibly following a crop rotation system. Vineyards largely remained constant with only one percent conversion to vineyard from other land cover classes.Keywords: Change detection, Land cover, NDVI, time-series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22788898 Treatment of the Modern Management Mechanism of the Debris Flow Processes Expected in the Mletiskhevi
Authors: G. Chakhaia, S. Gogilava, L. Tsulukidze, Z. Laoshvili, I. Khubulava, S. Bosikashvili, T. Gugushvili
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The work reviewed and evaluated various genesis debris flow phenomena recently formatted in the Mletiskhevi, accordingly it revealed necessity of treatment modern debris flow against measures. Based on this, it is proposed the debris flow against truncated semi cone shape construction, which elements are contained in the car’s secondary tires. its constituent elements (sections), due to the possibilities of amortization and geometric shapes is effective and sustainable towards debris flow hitting force. The construction is economical, because after crossing the debris flows in the river bed, the riverbed is not cleanable, also the elements of the building are resource saving. For assessment of influence of cohesive debris flow at the construction and evaluation of the construction effectiveness have been implemented calculation in the specific assumptions with approved methodology. According to the calculation, it was established that after passing debris flow in the debris flow construction (in 3 row case) its hitting force reduces 3 times, that causes reduce of debris flow speed and kinetic energy, as well as sedimentation on a certain section of water drain in the lower part of the construction. Based on the analysis and report on the debris flow against construction, it can be said that construction is effective, inexpensive, technically relatively easy-to-reach measure, that’s why its implementation is prospective.
Keywords: Construction, debris flow, sections, theoretical calculation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3898897 Evaluation of Best-Fit Probability Distribution for Prediction of Extreme Hydrologic Phenomena
Authors: Karim Hamidi Machekposhti, Hossein Sedghi
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The probability distributions are the best method for forecasting of extreme hydrologic phenomena such as rainfall and flood flows. In this research, in order to determine suitable probability distribution for estimating of annual extreme rainfall and flood flows (discharge) series with different return periods, precipitation with 40 and discharge with 58 years time period had been collected from Karkheh River at Iran. After homogeneity and adequacy tests, data have been analyzed by Stormwater Management and Design Aid (SMADA) software and residual sum of squares (R.S.S). The best probability distribution was Log Pearson Type III with R.S.S value (145.91) and value (13.67) for peak discharge and Log Pearson Type III with R.S.S values (141.08) and (8.95) for maximum discharge in Jelogir Majin and Pole Zal stations, respectively. The best distribution for maximum precipitation in Jelogir Majin and Pole Zal stations was Log Pearson Type III distribution with R.S.S values (1.74&1.90) and then Pearson Type III distribution with R.S.S values (1.53&1.69). Overall, the Log Pearson Type III distributions are acceptable distribution types for representing statistics of extreme hydrologic phenomena in Karkheh River at Iran with the Pearson Type III distribution as a potential alternative.
Keywords: Karkheh river, log pearson type III, probability distribution, residual sum of squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8658896 Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models
Authors: Maria C. Mariani, Md Al Masum Bhuiyan, Osei K. Tweneboah, Hector G. Huizar
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This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties.Keywords: Augmented Dickey Fuller Test, geophysical time series, maximum likelihood estimation, stochastic volatility model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8518895 Modeling of Flood Mitigation Structures for Sarawak River Sub-basin Using Info Works River Simulation (RS)
Authors: Rosmina Bustami, Charles Bong, Darrien Mah, Afnie Hamzah, Marina Patrick
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The distressing flood scenarios that occur in recent years at the surrounding areas of Sarawak River have left damages of properties and indirectly caused disruptions of productive activities. This study is meant to reconstruct a 100-year flood event that took place in this river basin. Sarawak River Subbasin was chosen and modeled using the one-dimensional hydrodynamic modeling approach using InfoWorks River Simulation (RS), in combination with Geographical Information System (GIS). This produces the hydraulic response of the river and its floodplains in extreme flooding conditions. With different parameters introduced to the model, correlations of observed and simulated data are between 79% – 87%. Using the best calibrated model, flood mitigation structures are imposed along the sub-basin. Analysis is done based on the model simulation results. Result shows that the proposed retention ponds constructed along the sub-basin provide the most efficient reduction of flood by 34.18%.Keywords: Flood, Flood mitigation structure, InfoWorks RS, Retention pond, Sarawak River sub-basin.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27008894 An Improved Prediction Model of Ozone Concentration Time Series Based On Chaotic Approach
Authors: N. Z. A. Hamid, M. S. M. Noorani
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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly Ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.
Keywords: Chaotic approach, phase space, Cao method, local linear approximation method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17718893 The Application of an Ensemble of Boosted Elman Networks to Time Series Prediction: A Benchmark Study
Authors: Chee Peng Lim, Wei Yee Goh
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In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16798892 Artificial Neural Network Model for a Low Cost Failure Sensor: Performance Assessment in Pipeline Distribution
Authors: Asar Khan, Peter D. Widdop, Andrew J. Day, Aliaster S. Wood, Steve, R. Mounce, John Machell
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This paper describes an automated event detection and location system for water distribution pipelines which is based upon low-cost sensor technology and signature analysis by an Artificial Neural Network (ANN). The development of a low cost failure sensor which measures the opacity or cloudiness of the local water flow has been designed, developed and validated, and an ANN based system is then described which uses time series data produced by sensors to construct an empirical model for time series prediction and classification of events. These two components have been installed, tested and verified in an experimental site in a UK water distribution system. Verification of the system has been achieved from a series of simulated burst trials which have provided real data sets. It is concluded that the system has potential in water distribution network management.Keywords: Detection, leakage, neural networks, sensors, water distribution networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17348891 Evaluation of Water Quality of the Beshar River
Authors: Fardin Boustani, Mohammah Hosein Hojati, Masoud Hashemi
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The Beshar River is one aquatic ecosystem, which is located next to the city of Yasuj in southern Iran. The Beshar river has been contaminated by industrial factories such as effluent of sugar factory, agricultural and other activities in this region such as, Imam Sajjad hospital, drainage from agricultural farms, Yasuj urban surface runoff and effluent of wastewater treatment plants ,specially Yasuj waste water treatment plant. In order to evaluate the effects of these pollutants on the quality of the Beshar river, five monitoring stations were selected along its course. The first station is located upstream of Yasuj near the Dehnow village; stations 2 to 4 are located east, south and west of city; and the 5th station is located downstream of Yasuj. Several water quality parameters were sampled. These include pH, dissolved oxygen, biological oxygen demand (BOD), temperature, conductivity, turbidity, total dissolved solids and discharge or flow measurements. Water samples from the five stations were collected and analyzed to determine the following physicochemical parameters: EC, pH, T.D.S, T.H, No2, DO, BOD5, COD during 2008 to 2010. The study shows that the BOD5 value of station 1 is at a minimum (1.7 ppm) and increases downstream from stations 2 to 4 to a maximum (11.6 ppm), and then decreases at station 5. The DO values of station 1 is a maximum (8.45 ppm), decreases downstream to stations 2 - 4 which are at a minimum (3.1 ppm), before increasing at station 5. The amount of BOD and TDS are highest at the 4th station and the amount of DO is lowest at this station, marking the 4th station as more highly polluted than the other stations .This study shows average amount of the water quality parameters in first year of sampling (2008) have had a better quality relation to third year in 2010 because of recent drought in this region and pollutant increasing .As the Beshar river path after 5th station goes through the mountain area with more slope and flow velocity ,so the physicochemical parameters improve at the 5th station due to pollutant degradation and dilution. Finally the point and nonpoint pollutant sources of Beshar river were determined and compared to the monitoring results.Keywords: Beshar river, physicochemical parameter, waterpollution, water quality, Yasuj
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16378890 Nodal Load Profiles Estimation for Time Series Load Flow Using Independent Component Analysis
Authors: Mashitah Mohd Hussain, Salleh Serwan, Zuhaina Hj Zakaria
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This paper presents a method to estimate load profile in a multiple power flow solutions for every minutes in 24 hours per day. A method to calculate multiple solutions of non linear profile is introduced. The Power System Simulation/Engineering (PSS®E) and python has been used to solve the load power flow. The result of this power flow solutions has been used to estimate the load profiles for each load at buses using Independent Component Analysis (ICA) without any knowledge of parameter and network topology of the systems. The proposed algorithm is tested with IEEE 69 test bus system represents for distribution part and the method of ICA has been programmed in MATLAB R2012b version. Simulation results and errors of estimations are discussed in this paper.Keywords: Electrical Distribution System, Power Flow Solution, Distribution Network, Independent Component Analysis, Newton Raphson, Power System Simulation for Engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29008889 Representing Data without Lost Compression Properties in Time Series: A Review
Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan
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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.
Keywords: Compression properties, uncertainty, uncertain time series, mining technique, weather prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16118888 Numerical Simulations of Flood and Inundation in Jobaru River Basin Using Laser Profiler Data
Authors: Hiroto Nakashima, Toshihiro Morita, Koichiro Ohgushi
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Laser Profiler (LP) data from aerial laser surveys have been increasingly used as topographical inputs to numerical simulations of flooding and inundation in river basins. LP data has great potential for reproducing topography, but its effective usage has not yet been fully established. In this study, flooding and inundation are simulated numerically using LP data for the Jobaru River basin of Japan’s Saga Plain. The analysis shows that the topography is reproduced satisfactorily in the computational domain with urban and agricultural areas requiring different grid sizes. A 2-D numerical simulation shows that flood flow behavior changes as grid size is varied.
Keywords: LP data, numerical simulation, topological analysis, mesh size.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15228887 Reduced Dynamic Time Warping for Handwriting Recognition Based on Multidimensional Time Series of a Novel Pen Device
Authors: Muzaffar Bashir, Jürgen Kempf
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The purpose of this paper is to present a Dynamic Time Warping technique which reduces significantly the data processing time and memory size of multi-dimensional time series sampled by the biometric smart pen device BiSP. The acquisition device is a novel ballpoint pen equipped with a diversity of sensors for monitoring the kinematics and dynamics of handwriting movement. The DTW algorithm has been applied for time series analysis of five different sensor channels providing pressure, acceleration and tilt data of the pen generated during handwriting on a paper pad. But the standard DTW has processing time and memory space problems which limit its practical use for online handwriting recognition. To face with this problem the DTW has been applied to the sum of the five sensor signals after an adequate down-sampling of the data. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of performance in single character and word recognition. Further excellent accuracy in recognition was achieved which is mainly due to the reduced dynamic time warping RDTW technique and a novel pen device BiSP.Keywords: Biometric character recognition, biometric person authentication, biometric smart pen BiSP, dynamic time warping DTW, online-handwriting recognition, multidimensional time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23958886 Implementation of Neural Network Based Electricity Load Forecasting
Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw
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This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.Keywords: Neural network, Load forecast, Time series, wavelettransform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24828885 A New Quantile Based Fuzzy Time Series Forecasting Model
Authors: Tahseen A. Jilani, Aqil S. Burney, C. Ardil
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Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.
Keywords: Quantile Regression, Fuzzy time series, fuzzy logicalrelationship groups, heuristic trend prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19858884 Statistical Reliability Based Modeling of Series and Parallel Operating Systems using Extreme Value Theory
Authors: Mohamad Mahdavi, Mojtaba Mahdavi
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This paper tries to represent a new method for computing the reliability of a system which is arranged in series or parallel model. In this method we estimate life distribution function of whole structure using the asymptotic Extreme Value (EV) distribution of Type I, or Gumbel theory. We use EV distribution in minimal mode, for estimate the life distribution function of series structure and maximal mode for parallel system. All parameters also are estimated by Moments method. Reliability function and failure (hazard) rate and p-th percentile point of each function are determined. Other important indexes such as Mean Time to Failure (MTTF), Mean Time to repair (MTTR), for non-repairable and renewal systems in both of series and parallel structure will be computed.Keywords: Reliability, extreme value, parallel, series, lifedistribution
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20818883 A New Technique for Solar Activity Forecasting Using Recurrent Elman Networks
Authors: Salvatore Marra, Francesco C. Morabito
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In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Keywords: Elman neural networks, sunspot, solar activity, time series prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18468882 Pollution and Water Quality of the Beshar River
Authors: Fardin Boustani , Mohammah Hosein Hojati
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The Beshar River is one aquatic ecosystem,which is affected by pollutants. This study was conducted to evaluate the effects of human activities on the water quality of the Beshar river. This river is approximately 190 km in length and situated at the geographical positions of 51° 20' to 51° 48' E and 30° 18' to 30° 52' N it is one of the most important aquatic ecosystems of Kohkiloye and Boyerahmad province next to the city of Yasuj in southern Iran. The Beshar river has been contaminated by industrial, agricultural and other activities in this region such as factories, hospitals, agricultural farms, urban surface runoff and effluent of wastewater treatment plants. In order to evaluate the effects of these pollutants on the quality of the Beshar river, five monitoring stations were selected along its course. The first station is located upstream of Yasuj near the Dehnow village; stations 2 to 4 are located east, south and west of city; and the 5th station is located downstream of Yasuj. Several water quality parameters were sampled. These include pH, dissolved oxygen, biological oxygen demand (BOD), temperature, conductivity, turbidity, total dissolved solids and discharge or flow measurements. Water samples from the five stations were collected and analysed to determine the following physicochemical parameters: EC, pH, T.D.S, T.H, No2, DO, BOD5, COD during 2008 to 2009. The study shows that the BOD5 value of station 1 is at a minimum (1.5 ppm) and increases downstream from stations 2 to 4 to a maximum (7.2 ppm), and then decreases at station 5. The DO values of station 1 is a maximum (9.55 ppm), decreases downstream to stations 2 - 4 which are at a minimum (3.4 ppm), before increasing at station 5. The amount of BOD and TDS are highest at the 4th station and the amount of DO is lowest at this station, marking the 4th station as more highly polluted than the other stations. The physicochemical parameters improve at the 5th station due to pollutant degradation and dilution. Finally the point and nonpoint pollutant sources of Beshar river were determined and compared to the monitoring results.Keywords: Beshar river, physicochemical parameter, waterpollution, Yasuj
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15928881 Physical Habitat Simulation and Comparison within a Lerma River Reach, with Respect to the Same but Modified Reach, to Create a Linear Park
Authors: Ezequiel Garcia-Rodriguez, Luis A. Ochoa-Franco, Adrian I. Cervantes-Servin
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In this work, the Ictalurus punctatus species estimated available physical habitat is compared with the estimated physical habitat for the same but modified river reach, with the aim of creating a linear park, along a length of 5 500 m. To determine the effect of ecological park construction, on physical habitat of the Lerma river stretch of study, first, the available habitat for the Ictalurus punctatus species was estimated through the simulation of the physical habitat, by using surveying, hydraulics, and habitat information gotten at the river reach in its actual situation. Second, it was estimated the available habitat for the above species, upon the simulation of the physical habitat through the proposed modification for the ecological park creation. Third, it is presented a comparison between both scenarios in terms of available habitat estimated for Ictalurus punctatus species, concluding that in cases of adult and spawning life stages, changes in the channel to create an ecological park would produce a considerable loss of potentially usable habitat (PUH), while in the case of the juvenile life stage PUH remains virtually unchanged, and in the case of life stage fry the PUH would increase due to the presence of velocities and depths of lesser magnitude, due to the presence of minor flow rates and lower volume of the wet channel. It is expected that habitat modification for linear park construction may produce the lack of Ictalurus punktatus species conservation at the river reach of the study.Keywords: Habitat modification, Ictalurus punctatus, Lerma, river, linear park.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16008880 Effect of a Multiple Stenosis on Blood Flow through a Tube
Authors: Vipin Kumar Verma, Praveen Saraswat
Abstract:
The development of double stenosis in an artery can have serious consequences and can disrupt the normal functioning of the circulatory system. It has been realized that various hydrodynamics effects (i.e. wall shear, pressure distribution etc.) play important role in the development of this disease. Generally in the literature, the cross-section of the artery is assumed to be uniform with a single stenosis. However, in real situation the multiple stenosis develops in series along the length of artery whose cross-section varies slowly. Therefore, the flow of blood is laminar through a small diameter artery with axisymmetric identical double stenosis in series.
Keywords: Wall shear, multiple stenosis, artery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18908879 Power Series Solution to Sliding Velocity in Three-Dimensional Multibody Systems with Impact and Friction
Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat
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The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge- Kutta solution using 38 time steps.Keywords: Impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19018878 Fast Short-Term Electrical Load Forecasting under High Meteorological Variability with a Multiple Equation Time Series Approach
Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou
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We present a multiple equation time series approach for the short-term load forecasting applied to the electrical power load consumption for the whole Quebec province, in Canada. More precisely, we take into account three meteorological variables — temperature, cloudiness and wind speed —, and we use meteorological measurements taken at different locations on the territory. Our final model shows an average MAPE score of 1.79% over an 8-years dataset.
Keywords: Short-term load forecasting, special days, time series, multiple equations, parallelization, clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2618877 Metal(loids) Speciation Using HPLC-ICP-MS Technique in Klodnica River, Upper Silesia, Poland
Authors: Magdalena Jabłońska-Czapla
Abstract:
The work allowed gaining knowledge about redox and speciation changes of As, Cr and Sb ionic forms in Klodnica River water. This kind of studies never has been conducted in this region of Poland. In study optimized and validated previously HPLC-ICP-MS methods for determination of As, Sb and Cr was used. Separation step was done using high-performance liquid chromatograph equipped with ion-exchange column followed by ICP-MS spectrometer detector. Preliminary studies included determination of the total concentration of As, Sb and Cr, pH, Eh, temperature and conductivity of the water samples. The study was conducted monthly from March to August 2014, at six points on the Klodnica River. The results indicate that exceeded at acceptable concentration of total Cr and Sb was observed in Klodnica River and we should qualify Klodnica River waters below the second purity class. In Klodnica River waters dominates oxidized antimony and arsenic forms, as well as the two forms of chromium Cr(VI) and Cr(III). Studies have also shown the methyl derivative of arsenic's presence.
Keywords: Antimony, arsenic, chromium, HPLC-ICP-MS, river water, speciation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21238876 Quality of Non-Point Source Pollutant Identification using Digital Image and Remote Sensing Image
Authors: Riki Mukhaiyar
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The integration between technology of remote sensing, information from the data of digital image, and modeling technology for the simulation of water quality will provide easiness during the observation on the quality of water changes on the river surface. For example, Ciliwung River which is contaminated with non-point source pollutant from household wastes, particularly on its downstream. This fact informed that the quality of water in this river is getting worse. The land use for settlements and housing ranges between 62.84% - 81.26% on the downstream of Ciliwung River, give a significant picture in seeing factors that affected the water quality of Ciliwung River.Keywords: Digital Image, Digitize, Landuse, Non-Point SourcePollutant, Qual2e Simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1698