scholarly journals A Cox Process with State-Dependent Exponential Pulses to Model Rainfall

2021 ◽  
Author(s):  
Nadarajah I Ramesh ◽  
Gayatri Rode ◽  
Christian Onof
Keyword(s):  
Markov Chain ◽  
Process Model ◽  
Mathematical Formulation ◽  
Arrival Rate ◽  
Rainfall Data ◽  
Model Assessment ◽  
Method Of Moment ◽  
State Dependent ◽  
Proposed Model ◽  
Hourly Rainfall

AbstractA point process model based on a class of Cox processes is developed to analyse precipitation data at a point location. The model is constructed using state-dependent exponential pulses that are governed by an unobserved underlying Markov chain. The mathematical formulation of the model where both the arrival rate of the rain cells and the initial pulse depth are determined by the Markov chain is presented. Second-order properties of the rainfall depth process are derived and utilised in model assessment. A method of moment estimation is employed in model fitting. The proposed model is used to analyse 69 years of sub-hourly rainfall data from Germany and 15 years of English rainfall data. The results of the analysis using variants of the proposed model with fixed pulse lifetime and variable pulse duration are presented. The performance of the proposed model, in reproducing second-moment characteristics of the rainfall, is compared with that of two stochastic models where one has exponential pulses and the other has rectangular pulses. The proposed model is found to capture most of the empirical rainfall properties well and outperform the two alternative models considered in our analysis.

scholarly journals Charging Station Allocation for Electric Vehicle Network Using Stochastic Modeling and Grey Wolf Optimization

2021 ◽  
Vol 13 (6) ◽  
pp. 3314
Author(s):  
Rawan Shabbar ◽  
Anemone Kasasbeh ◽  
Mohamed M. Ahmed
Keyword(s):  
Markov Chain ◽  
Electric Vehicles ◽  
Process Model ◽  
Transportation Network ◽  
Optimal Placement ◽  
Death Process ◽  
Chain Model ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Net Profit

Optimal placement of Charging stations (CSs) and infrastructure planning are one of the most critical challenges that face the Electric Vehicles (EV) industry nowadays. A variety of approaches have been proposed to address the problem of demand uncertainty versus the optimal number of CSs required to build the EV infrastructure. In this paper, a Markov-chain network model is designed to study the estimated demand on a CS by using the birth and death process model. An investigation on the desired number of electric sockets in each CS and the average number of electric vehicles in both queue and waiting times is presented. Furthermore, a CS allocation algorithm based on the Markov-chain model is proposed. Grey Wolf Optimization (GWO) algorithm is used to select the best CS locations with the objective of maximizing the net profit under both budget and routing constraints. Additionally, the model was applied to Washington D.C. transportation network. Experimental results have shown that to achieve the highest net profit, Level 2 chargers need to be installed in low demand areas of infrastructure implementation. On the other hand, Level 3 chargers attain higher net profit when the number of EVs increases in the transportation network or/and in locations with high charging demands.

Calculation of Effective Ground Depth of Cut by Means of Grinding Process Model

2011 ◽  
Vol 496 ◽  
pp. 7-12 ◽  
Author(s):  
Takazo Yamada ◽  
Michael N. Morgan ◽  
Hwa Soo Lee ◽  
Kohichi Miura
Keyword(s):  
Process Model ◽  
Ground Surface ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Wheel Wear ◽  
Elastic Deformations ◽  
Proposed Model ◽  
Effective Depth ◽  
Grinding Machine

In order to obtain the effective depth of cut on the ground surface, a new grinding process model taking into account thermal expansions of the grinding wheel and the workpiece, elastic deformations of the grinding machine, the grinding wheel and the workpiece and the wheel wear was proposed. Using proposed model, the effective depth of cut was calculated using measured results of the applied depth of cut and the normal grinding force.

Movement of Large Convective Rainstorms in Relation to Winds Aloft

1958 ◽  
Vol 39 (3) ◽  
pp. 129-136 ◽  
Author(s):  
C. W. Newton ◽  
Sey Katz
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Rainfall Data ◽  
Squall Lines ◽  
Hourly Rainfall ◽  
The Difference ◽  
Strong Winds

By means of hourly rainfall data from the Hydroclimatic Network, the motions of large rainstorms, of the kind associated with squall lines, are examined in relation to the winds aloft. Very little correlation is found between the speed of movement of the rainstorms and the wind speed at any level, although the fastest moving storms were associated with strong winds aloft. Significant correlation is found between direction of motion of rainstorms, and wind direction at 700 mb or higher levels. On the average, the rainstorms move with an appreciable component toward right of the wind direction. The difference between these results, and those from other studies based on small precipitation areas, is ascribed to propagation. The mechanism involved is discussed briefly.

scholarly journals Analytical Model for Estimating the Impact of Changing the Nominal Power Parameter in LTE

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
A. B. Vallejo-Mora ◽  
M. Toril ◽  
S. Luna-Ramírez ◽  
M. Regueira ◽  
S. Pedraza
Keyword(s):  
Analytical Model ◽  
Mobile Networks ◽  
Radio Resource Management ◽  
Estimation Accuracy ◽  
Model Assessment ◽  
Power Parameter ◽  
Management Procedure ◽  
Proposed Model ◽  
A Cell ◽  
The Impact

UpLink Power Control (ULPC) is a key radio resource management procedure in mobile networks. In this paper, an analytical model for estimating the impact of increasing the nominal power parameter in the ULPC algorithm for the Physical Uplink Shared CHannel (PUSCH) in Long Term Evolution (LTE) is presented. The aim of the model is to predict the effect of changing the nominal power parameter in a cell on the interference and Signal-to-Interference-plus-Noise Ratio (SINR) of that cell and its neighbors from network statistics. Model assessment is carried out by means of a field trial where the nominal power parameter is increased in some cells of a live LTE network. Results show that the proposed model achieves reasonable estimation accuracy, provided uplink traffic does not change significantly.

scholarly journals Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

2014 ◽  
Vol 18 (1) ◽  
pp. 353-365 ◽  
Author(s):  
U. Haberlandt ◽  
I. Radtke
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Model Calibration ◽  
Hydrological Model ◽  
Probability Distributions ◽  
Flood Frequency ◽  
Rainfall Data ◽  
Flood Frequency Analysis ◽  
Peak Flows ◽  
Hourly Rainfall

Abstract. Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

scholarly journals Order-Dependent Event Models for Agent Interactions

2020 ◽  
Author(s):  
Debarun Bhattacharjya ◽  
Tian Gao ◽  
Dharmashankar Subramanian
Keyword(s):  
Arrival Rate ◽  
Event Data ◽  
Political Event ◽  
Instantaneous Rate ◽  
Agent Interactions ◽  
Occurrence Data ◽  
Proposed Model ◽  
Event Models ◽  
Better Than ◽  
Event Occurrence

In multivariate event data, the instantaneous rate of an event's occurrence may be sensitive to the temporal sequence in which other influencing events have occurred in the history. For example, an agent’s actions are typically driven by preceding actions taken by the agent as well as those of other relevant agents in some order. We introduce a novel statistical/causal model for capturing such an order-sensitive historical dependence, where an event’s arrival rate is determined by the order in which its underlying causal events have occurred in the recent past. We propose an algorithm to discover these causal events and learn the most influential orders using time-stamped event occurrence data. We show that the proposed model fits various event datasets involving single as well as multiple agents better than baseline models. We also illustrate potentially useful insights from our proposed model for an analyst during the discovery process through analysis on a real-world political event dataset.

Understanding the Progressive Nature of Inter-Organizational Systems (IOS) Adoption

2012 ◽  
pp. 51-71
Author(s):  
Mazen Ali ◽  
Sherah Kurnia ◽  
Robert B. Johnston
Keyword(s):  
Supply Chain ◽  
Process Model ◽  
Trading Partner ◽  
Organizational Systems ◽  
Proposed Model ◽  
Trading Partners

Inter-organizational Systems (IOS) cannot be adopted by any organizations in isolation from their trading partner. Their adoption requires cooperation and collaboration between trading partners and, therefore, is reliant on the nature of relationships between the parties involved. For organizations to progress in their IOS adoption, improvement in relationships between trading partners is required before they can adopt a more sophisticated IOS. In addition, through IOS adoption, trading partners can actually improve their relationships overtime. There has been some research that investigates relationships and how organizations progress from one level to the next level of adoption. However, these studies do not clearly define the concepts of relationship, IOS adoption and IOS adoption maturity. Furthermore, they do not adequately justify the exclusion of other variables in defining the relevant concepts and are not theoretically based. This research extends the Kurnia and Johnston (2000) process model of IOS adoption by incorporating the notion of IOS adoption maturity and reducing the scope from a supply chain to a dyadic level to enable better evaluations of IOS adoption progression. We argue that with the proposed model, the dynamics of IOS adoption maturity can be better examined empirically.

Towards Public Services and Process Integration

2013 ◽  
pp. 275-287
Author(s):  
Guillermo Infante Hernández ◽  
Aquilino A. Juan Fuente ◽  
Benjamín López Pérez ◽  
Edward Rolando Núñez-Valdéz
Keyword(s):  
Process Model ◽  
Public Services ◽  
Process Integration ◽  
Domain Specific ◽  
Modeling Environment ◽  
Proposed Model ◽  
Domain Specific Modeling ◽  
Hardware Platforms ◽  
Business Requirements ◽  
Integration Rules

Software platforms for e-government transactions may differ in developed functionalities, languages and technologies, hardware platforms, and operating systems that support them. Those differences can be found among public organizations that share common processes, services, and regulations. This scenario hinders interoperability between these organizations. Hence, to find a technique for integrating these platforms becomes a necessity. In this chapter, a rule-based domain-specific modeling environment for public services and process integration is suggested, which consists of common identified public service elements and a set of process integration rules. This approach provides the needed integration or interoperability pursued in this domain. Furthermore a service and process model is proposed to formalize the information needed for integration of both. A set of integration rules is also presented as part of the modeling environment. This set of integration rules completes the proposed model to meet the business requirements of this domain.

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