scholarly journals An approach to identify time consistent model parameters: sub-period calibration

2013 ◽  
Vol 17 (1) ◽  
pp. 149-161 ◽  
Author(s):  
S. Gharari ◽  
M. Hrachowitz ◽  
F. Fenicia ◽  
H. H. G. Savenije
Keyword(s):  
Model Performance ◽  
Realistic Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
New Approach ◽  
Consistent Model ◽  
Set Up ◽  
Consistent Parameter

Abstract. Conceptual hydrological models rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of testing model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time-consistent parameter sets. The approach is applied to a case study in Luxembourg using the HyMod hydrological model as an example.

scholarly journals Moving beyond traditional model calibration or how to better identify realistic model parameters: sub-period calibration

2012 ◽  
Vol 9 (2) ◽  
pp. 1885-1918
Author(s):  
S. Gharari ◽  
M. Hrachowitz ◽  
F. Fenicia ◽  
H. H. G. Savenije
Keyword(s):  
Model Calibration ◽  
Model Performance ◽  
Realistic Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
New Approach ◽  
Consistent Model ◽  
Set Up

Abstract. Conceptual hydrological models often rely on calibration for the identification of their parameters. As these models are typically designed to reflect real catchment processes, a key objective of an appropriate calibration strategy is the determination of parameter sets that reflect a "realistic" model behavior. Previous studies have shown that parameter estimates for different calibration periods can be significantly different. This questions model transposability in time, which is one of the key conditions for the set-up of a "realistic" model. This paper presents a new approach that selects parameter sets that provide a consistent model performance in time. The approach consists of confronting model performance in different periods, and selecting parameter sets that are as close as possible to the optimum of each individual sub-period. While aiding model calibration, the approach is also useful as a diagnostic tool, illustrating tradeoffs in the identification of time consistent parameter sets. The approach is demonstrated in a case study where we illustrate the multi-objective calibration of the HyMod hydrological model to a Luxembourgish catchment.

scholarly journals Parameter stability and consistency in an alongshore-current model determined with Markov chain Monte Carlo

2008 ◽  
Vol 10 (2) ◽  
pp. 153-162 ◽  
Author(s):  
B. G. Ruessink
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Parameter Stability ◽  
Small Uncertainty ◽  
Best Fit ◽  
Stability And Consistency

When a numerical model is to be used as a practical tool, its parameters should preferably be stable and consistent, that is, possess a small uncertainty and be time-invariant. Using data and predictions of alongshore mean currents flowing on a beach as a case study, this paper illustrates how parameter stability and consistency can be assessed using Markov chain Monte Carlo. Within a single calibration run, Markov chain Monte Carlo estimates the parameter posterior probability density function, its mode being the best-fit parameter set. Parameter stability is investigated by stepwise adding new data to a calibration run, while consistency is examined by calibrating the model on different datasets of equal length. The results for the present case study indicate that various tidal cycles with strong (say, >0.5 m/s) currents are required to obtain stable parameter estimates, and that the best-fit model parameters and the underlying posterior distribution are strongly time-varying. This inconsistent parameter behavior may reflect unresolved variability of the processes represented by the parameters, or may represent compensational behavior for temporal violations in specific model assumptions.

scholarly journals Interpreting the Estimates from the Full VECH Model with Asymmetry: The Case of US and Canadian Equity Prices

2017 ◽  
Vol 6 (4) ◽  
pp. 236
Author(s):  
Chikashi Tsuji
Keyword(s):  
Parameter Estimates ◽  
Model Parameters ◽  
Model Structure ◽  
Equity Prices ◽  
Related Research ◽  
Asymmetric Effects ◽  
Equity Index ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Full Vector

This paper attempts to derive careful interpretation of the parameter estimates from one of the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) models, the full vector-half (VECH) model with asymmetric effects. We also consider and interpret the parameter estimates from a case study of US and Canadian equity index returns by applying this model. More specifically, we firstly inspect the model formula and derive general interpretation of the model parameters. We consider this is particularly useful for understanding not only the full VECH model structure but also similar MGARCH models. After the general considerations, we also interpret the case results that are derived from our application of the full VECH model to US and Canadian equity index returns. We consider that these concrete illustrations are also very helpful for future related research.

scholarly journals The Effect of the Size of Traffic Analysis Zones on the Quality of Transport Demand Forecasts and Travel Assignments

2018 ◽  
Author(s):  
Mehmet Fatih Altan ◽  
Yunus Emre Ayözen
Keyword(s):  
Regression Model ◽  
Traffic Analysis ◽  
Model Parameters ◽  
The Public ◽  
Employment Density ◽  
Exponential Regression Model ◽  
Demand Forecasts

In this work we have studied the selection criteria for traffic analysis zones and the effects of their size and number on the model’s forecasting capabilities. To do so we have focused on the corridor of İstanbul’s Kadıköy-Kartal Metro Line and evaluated the consistency of demand forecasts and travel assignments versus actual measurements under different sizes of the Traffic Analysis Zones (TAZ). Significant improvements in model accuracy were observed by decreasing the zone size. Specifically, studying the public transport network assignments for the metro line when increasing the number of traffic analysis zones from 540 to 1,788 the root mean square error (RMSE) of forecasted vs. actual station-based counts was reduced by 23%. Subsequently, the study used population density and employment density as independent variables for the determination of the optimal radius for the 1,788 zone area, and applied an exponential regression model. Appropriate model parameters were derived for the above case study. The regression model resulted in R2 values over 0.62.

scholarly journals Development of a Semantic Representation Model of Criminal Information to Support the Assessment of Risk Situations

2019 ◽  
Author(s):  
Jordan Ferreira Saran ◽  
Leonardo Botega
Keyword(s):  
Information Quality ◽  
Situational Awareness ◽  
Semantic Representation ◽  
New Approach ◽  
Level Of Consciousness ◽  
Human Operators ◽  
Or Team

Situational Awareness (SAW) refers to the level of consciousness that an individual or team holds over a situation. In the area of ​​risk management and criminal data analysis, SAW failures can induce human operators to make mistakes in decision making and pose risks to life or property. In this context, risk assessment processes, which commonly involves data mining, fusion and other methods, present opportunities to generate better information and contribute to the improvement of the SAW of crime and risk analysts. However, the characterization of complex scenarios is subject to problems of representation and expressiveness of the information, which may influence its interpretation due to their quality and significance, generating uncertainties. The state-of-the-art in representation of information on risk situations and related areas presents approaches with limited use of information quality. In addition, the solutions are restricted to syntactic mechanisms for the determination of relations between information, negatively restricting the assertiveness of the results. Thus, this paper aims to develop a new approach to semantic representation of information of risk situations, more specifically creating domain ontologies, instantiated with crime data and information quality. In a case study, real information on crimes, represented by the new semantic model and consumed by computational inference processes, was be processed, aiming to characterize robbery and theft situations.

scholarly journals A Novel Application Based on a Heuristic Approach for Planning Itineraries of One-Day Tourist

2021 ◽  
Vol 11 (19) ◽  
pp. 8989
Author(s):  
Agostino Marcello Mangini ◽  
Michele Roccotelli ◽  
Alessandro Rinaldi
Keyword(s):  
User Interaction ◽  
Technological Innovations ◽  
Optimization Approach ◽  
Information And Communications Technologies ◽  
New Approach ◽  
Communications Technologies ◽  
Intelligent Cities ◽  
The City

Technological innovations have revolutionized the lifestyle of the society and led to the development of advanced and intelligent cities. Smart city has recently become synonymous of a city characterized by an intelligent and extensive use of Information and Communications Technologies (ICTs) in order to allow efficient use of information. In this context, this paper proposes a new approach to optimize the planning of itineraries for one-day tourist. More in detail, an optimization approach based on Graph theory and multi-algorithms is provided to determine the optimal tourist itinerary. The aim is to minimize the travel times taking into account the tourist preferences. An Integer Linear Programming (ILP) problem is introduced to find the optimal outward and return paths of the touristic itinerary and a multi-algorithms strategy is used to maximize the number of attractions (PoIs) to be visited in the paths. Finally, a case study focusing on cruise tourist in the city of Bari, demonstrates the efficiency of the approach and the user interaction in the determination of the itinerary.

scholarly journals Infusing Local Tradition Values into School Culture: How Indonesian Islamic School Set Up Character Education?

2018 ◽  
Vol 26 (2) ◽  
pp. 495
Author(s):  
M Mulyadin ◽  
Amat Jaedun
Keyword(s):  
Character Education ◽  
Cultural Values ◽  
Interaction Model ◽  
Islamic School ◽  
Local Tradition ◽  
Collection Data ◽  
Data Validity ◽  
Set Up

<p>The purpose of this study is to reveal the internalization of the <em>maja labo dahu</em> values in character education. The method used is a case study with a qualitative approach. The determination of the research subject is carried out by purposive technique consisting of students and people in MTs Negeri 1 Bima. The sources of data are oral sources, artifacts, documents, and written records. Data are collected through observation, interviews, and documentation. Data validity test is carried out by using triangulation. Data are analyzed by using qualitative analysis techniques of interaction model with steps of data collection, data reduction, data presentation, and conclusions. The results showed that the values of the <em>maja labo dahu</em> are in accordance with the values in character education, namely religious values, honesty, discipline, independence, patriotism, and environmental awareness. Besides, these values have effectively provided moral knowledge to students. The constraints experienced by schools in internalizing these values in character education are the lack of consistency of students parents or the surrounding environment in supporting and developing the cultural values of the <em>maja labo dahu</em>.</p>

scholarly journals A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate – accounting for changing watershed behavior

2011 ◽  
Vol 15 (11) ◽  
pp. 3591-3603 ◽  
Author(s):  
R. Singh ◽  
T. Wagener ◽  
K. van Werkhoven ◽  
M. E. Mann ◽  
R. Crane
Keyword(s):  
Spatial Relationship ◽  
Model Performance ◽  
Climate Scenario ◽  
Hydrologic Model ◽  
Climatic Conditions ◽  
Low Flow ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Watershed Model ◽  
The Impact

Abstract. Projecting how future climatic change might impact streamflow is an important challenge for hydrologic science. The common approach to solve this problem is by forcing a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. However, several recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. So how can we calibrate a hydrologic model for historically unobserved climatic conditions? To address this issue, we propose a new trading-space-for-time framework that utilizes the similarity between the predictions under change (PUC) and predictions in ungauged basins (PUB) problems. In this new framework we first regionalize climate dependent streamflow characteristics using 394 US watersheds. We then assume that this spatial relationship between climate and streamflow characteristics is similar to the one we would observe between climate and streamflow over long time periods at a single location. This assumption is what we refer to as trading-space-for-time. Therefore, we change the limits for extrapolation to future climatic situations from the restricted locally observed historical variability to the variability observed across all watersheds used to derive the regression relationships. A typical watershed model is subsequently calibrated (conditioned) on the predicted signatures for any future climate scenario to account for the impact of climate on model parameters within a Bayesian framework. As a result, we can obtain ensemble predictions of continuous streamflow at both gauged and ungauged locations. The new method is tested in five US watersheds located in historically different climates using synthetic climate scenarios generated by increasing mean temperature by up to 8 °C and changing mean precipitation by −30% to +40% from their historical values. Depending on the aridity of the watershed, streamflow projections using adjusted parameters became significantly different from those using historically calibrated parameters if precipitation change exceeded −10% or +20%. In general, the trading-space-for-time approach resulted in a stronger watershed response to climate change for both high and low flow conditions.

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