Generation of synthetic cross-correlated water demand time series

2013 ◽  
Vol 13 (4) ◽  
pp. 977-986 ◽  
Author(s):  
N. Ansaloni ◽  
S. Alvisi ◽  
M. Franchini
Keyword(s):  
Time Series ◽  
Water Demand ◽  
Distribution System ◽  
Water Distribution ◽  
Cross Correlation ◽  
Time Lags ◽  
Cross Correlations ◽  
The Cross ◽  
Water Districts

This paper presents a procedure for generating synthetic district-level series of hourly water demand coefficients cross-correlated in space (between districts) and time. The procedure consists of two steps: (1) generation of hourly water demand coefficients which respect, for each hour of the day, pre-assigned means and variances; and (2) introduction of the cross-correlation at different time lags through the application of a method which implies the reordering of the data generated at step 1. The procedure was applied to a case study of the Ferrara water distribution system with the aim of generating cross-correlated synthetic series of hourly water demand coefficients for the 19 water districts making it up. It was observed that the application of the method for introducing the cross-correlation (step 2) causes numerical problems when a large number of water districts are involved and the cross-correlations are considered at many time lags; this problem is solved by carrying out an appropriate regularization of the observed cross-correlation matrix. The results obtained show that overall the proposed procedure constitutes a valid tool for generating synthetic water demand time series with pre-assigned characteristics in terms of means, variances and cross-correlation at different time lags.

scholarly journals Modeling Complex System Correlation Using Detrended Cross-Correlation Coefficient

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Keqiang Dong ◽  
Hong Zhang ◽  
You Gao
Keyword(s):  
Complex System ◽  
Time Series ◽  
Correlation Coefficient ◽  
Cross Correlation ◽  
Heavy Tails ◽  
Correlation Property ◽  
Traffic Time Series ◽  
Cross Correlations ◽  
The Cross ◽  
Active Research

The understanding of complex systems has become an area of active research for physicists because such systems exhibit interesting dynamical properties such as scale invariance, volatility correlation, heavy tails, and fractality. We here focus on traffic dynamic as an example of a complex system. By applying the detrended cross-correlation coefficient method to traffic time series, we find that the traffic fluctuation time series may exhibit cross-correlation characteristic. Further, we show that two traffic speed time series derived from adjacent sections exhibit much stronger cross-correlations than the two speed series derived from adjacent lanes. Similarly, we also demonstrate that the cross-correlation property between the traffic volume variables from two adjacent sections is stronger than the cross-correlation property between the volume variables of adjacent lanes.

scholarly journals Investigations of Broad Line Region Structure and Kinematics Using Variability

1989 ◽  
Vol 134 ◽  
pp. 93-95
Author(s):  
C. Martin Gaskell ◽  
Anuradha P. Koratkar ◽  
Linda S. Sparke
Keyword(s):  
Time Series ◽  
Cross Correlation ◽  
Sampling Interval ◽  
Broad Line ◽  
Line Flux ◽  
Line Region ◽  
Cross Correlations ◽  
The Mean ◽  
The Cross ◽  
The Continuum

Gaskell and Sparke (1986) showed that one can determine the sizes of BLRs more accurately that the mean sampling interval by cross-correlating the continuum flux time series with a line flux time series. The position of the peak in the cross-correlation function (CCF) and its shape give an indication of the BLR size. The technique is explained in detail in Gaskell and Peterson (1987). The widely propagated misunderstanding is that the method involves simply interpolating both time series and cross-correlating them (in which case the CCF is dominated by the cross-correlations of “made-up” data). Actually the method involves cross correlating the observed points in one time series (continuum, say) with the linear interpolations of the other series (line flux). The line flux time series must always be smoother than the continuum time series it is derived from. We have usually employed the method with the interpolation done both ways round and averaged them (to reduce errors due to the interpolation) and we can intercompare the two results (to investigate errors).

Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series

2019 ◽  
Vol 18 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Jingjing Huang ◽  
Danlei Gu
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
High Frequency ◽  
Cross Correlation ◽  
Financial Time Series ◽  
Chinese Market ◽  
Change Of Scale ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5[Formula: see text]min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of [Formula: see text], the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes.

scholarly journals Estimating High Resolution Temporal Scale of Water Demand Time Series – Disaggregation Approach (Case Study)

10.29007/4vfl ◽  
2018 ◽  
Author(s):  
Peyman Yousefi ◽  
Gholamreza Naser ◽  
Hadi Mohammadi
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Water Demand ◽  
Distribution System ◽  
Urban Areas ◽  
Water Distribution ◽  
Demand Forecasting ◽  
Temporal Scale ◽  
A New Technique ◽  
Cascade Method

A comprehensive understanding of water demand and its availability is essential for decision-makers to manage their resources and understand related risks effectively. Historical data play a crucial role in developing an integrated plan for management of water distribution system. The key is to provide high-resolution temporal-scale of demand data in urban areas. In the literature, many studies on water demand forecasting are available; most of them were focused on monthly-scales. Since monitoring of time series is a prolonged and costly procedure, the popularity of disaggregation methods is a most recent desirable trend. The objective of this research is to transfer low-resolution into high-resolution temporal scale using random cascade disaggregation and non-linear deterministic methods. This study defines a new technique to apply previously proposed random cascade method to disaggregate continuous data of the city of Peachland. The accuracy of the results is more than 90%. It represents a satisfactory application of the models. The proposed approach helps operators to have access to daily demand without acquiring high-resolution temporal scale values. Although the disaggregated values may not be precisely equal with observed values, it offers a practical solution for the low equipped WDS and leads to lesser number of drinking water-related problems.

scholarly journals Enhanced Water Demand Analysis via Symbolic Approximation within an Epidemiology-Based Forecasting Framework

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 246 ◽  
Author(s):  
Claudia Navarrete-López ◽  
Manuel Herrera ◽  
Bruno Brentan ◽  
Edevar Luvizotto ◽  
Joaquín Izquierdo
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Asset Management ◽  
Water Demand ◽  
Distribution System ◽  
Water Distribution ◽  
Knowledge Generation ◽  
Target Area ◽  
Neural Network Models ◽  
Symbolic Approximation

Epidemiology-based models have shown to have successful adaptations to deal with challenges coming from various areas of Engineering, such as those related to energy use or asset management. This paper deals with urban water demand, and data analysis is based on an Epidemiology tool-set herein developed. This combination represents a novel framework in urban hydraulics. Specifically, various reduction tools for time series analyses based on a symbolic approximate (SAX) coding technique able to deal with simple versions of data sets are presented. Then, a neural-network-based model that uses SAX-based knowledge-generation from various time series is shown to improve forecasting abilities. This knowledge is produced by identifying water distribution district metered areas of high similarity to a given target area and sharing demand patterns with the latter. The proposal has been tested with databases from a Brazilian water utility, providing key knowledge for improving water management and hydraulic operation of the distribution system. This novel analysis framework shows several benefits in terms of accuracy and performance of neural network models for water demand.

scholarly journals Models for forecasting water demand using time series analysis: a case study in Southern Brazil

2021 ◽  
Author(s):  
Danielle C. M. Ristow ◽  
Elisa Henning ◽  
Andreza Kalbusch ◽  
Cesar E. Petersen
Keyword(s):  
Time Series ◽  
Water Consumption ◽  
Water Demand ◽  
Web Application ◽  
Water Resource Management ◽  
Distribution Systems ◽  
Water Distribution ◽  
Demand Forecasting ◽  
Model Quality

Abstract Technology has been increasingly applied in search for excellence in water resource management. Tools such as demand-forecasting models provide information for utility companies to make operational, tactical and strategic decisions. Also, the performance of water distribution systems can be improved by anticipating consumption values. This work aimed to develop models to conduct monthly urban water demand forecasts by analyzing time series, and adjusting and testing forecast models by consumption category, which can be applied to any location. Open language R was used, with automatic procedures for selection, adjustment, model quality assessment and forecasts. The case study was conducted in the city of Joinville, with water consumption forecasts for the first semester of 2018. The results showed that the seasonal ARIMA method proved to be more adequate to predict water consumption in four out of five categories, with mean absolute percentage errors varying from 1.19 to 15.74%. In addition, a web application to conduct water consumption forecasts was developed.

Study of Cross-Correlations in Traffic Networks with Applications to Perimeter Control

2017 ◽  
Vol 2623 (1) ◽  
pp. 108-116
Author(s):  
Lele Zhang ◽  
Callum Stuart ◽  
Samithree Rajapaksha ◽  
Gentry White ◽  
Timothy Garoni
Keyword(s):  
Network Performance ◽  
Cross Correlation ◽  
Network Flows ◽  
Control Strategies ◽  
Single Point ◽  
Traffic Demand ◽  
Cross Correlations ◽  
The Mean ◽  
The Cross

A cross-correlation is proposed between network-aggregated density and flow as a natural indicator of traffic phases for two-dimensional road networks. An online estimator of the cross-correlation was studied with the use of empirical data. The result suggests that the measure can be used to identify traffic phases. To understand better the behavior of the true statistical cross-correlation, generic networks were simulated. With homogeneously distributed densities, the simulations suggested that the cross-correlation monotonically decreases with the growth of the mean density and vanishes when the network is at capacity. As a consequence, for such networks, the phase can be identified from a single point on the curve of the cross-correlation versus mean density. A case study of cross-correlation–based perimeter-control strategies was performed, with gate traffic flowing into the network when the cross-correlation was below a (negative) threshold to improve network flows. The simulation results suggest that even with anisotropic traffic demand, the cross-correlation–based control strategy can improve network performance, specifically traffic flow and density heterogeneity.

Coupling compositional data analysis (CoDA) with hierarchical cluster analysis (HCA) for preliminary understanding of the dynamics of a complex water distribution system: the Naples (south Italy) case study

2021 ◽  
Author(s):  
Pooria Ebrahimi ◽  
Stefano Albanese ◽  
Leopoldo Esposito ◽  
Daniela Zuzolo ◽  
Domenico Cicchella
Keyword(s):  
Distribution System ◽  
Water Distribution ◽  
Compositional Data ◽  
Tap Water ◽  
Hierarchical Cluster ◽  
Compositional Data Analysis ◽  
Anthropogenic Pressure ◽  
South Italy ◽  
Global Concern

Providing safe tap water has been a global concern. Water scarcity, the ever-increasing water demand, temporal variation of water consumption, aging urban water infrastructure and anthropogenic pressure on the water...

Study on the impacts of peaking factors on a water distribution system in Germany

2010 ◽  
Vol 10 (2) ◽  
pp. 165-172 ◽  
Author(s):  
K. Diao ◽  
M. Barjenbruch ◽  
U. Bracklow
Keyword(s):  
Energy Consumption ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Distribution Network ◽  
Design Stage ◽  
Water Age ◽  
Specific System ◽  
Average Water

This paper aims to explore the impacts of peaking factors on a water distribution system designed for a small city in Germany through model-based analysis. As a case study, the water distribution network was modelled by EPANET and then two specific studies were carried out. The first study tested corresponding system-wide influences on water age and energy consumption if the peaking factors used at design stage are inconsistent with ones in real situation. The second study inspected the possible relationship between the choice of peaking factors and budgets by comparing several different pipe configurations of the distribution system, obtained according to variety of peaking factors. Given the analysis results, the first study reveals that average water age will increase if peaking factors estimated at design stage are larger than real values in that specific system, and vice versa. In contrast, energy consumption will increase if peaking factors defined for system design are smaller than ones in real case, and vice versa. According to the second study, it might be possible to amplify peaking factors for design dramatically by a slight increase in the investment on this system. However, further study on budget estimation with more factors and detailed information considered should be carried out.

Understanding and forecasting taste-and-odour formation in a drinking water distribution system: case study of Lyon (France)

2009 ◽  
Vol 9 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Elise Corbi ◽  
Valérie Jacquemet ◽  
Alain Quendo ◽  
Francine Manciot ◽  
Adeline Lamy ◽  
...  
Keyword(s):  
Drinking Water ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Distribution Network ◽  
Drinking Water Distribution ◽  
First Results ◽  
Mechanisms Of Formation

Lyon, France has the opportunity to distribute in abundance a groundwater resource with a good quality for drinking water. However, the length and the complexity of the distribution network can lead to consumer complaints in some areas of the water distribution system. In order to improve the organoleptic quality of distributed water, the water supplier wants to get a better understanding of potential taste and odour formation and to succeed in controlling it. Since 2006, activities have been taken with targeted analyses and sensory evaluation of water, taking into account both the consumers' private networks and the citywide distribution network. The first results were focused on the occurrence of bromophenols along the water distribution system, the understanding of the mechanisms of formation of such compounds, as well as their incidence on taste-and-odour events at the consumer's home.

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