Global Parking Facility Management: Review and a Real-time Interactively Predictive Model

2014 ◽  
Vol 5 ◽  
pp. 1997-2021
Author(s):  
M. Riaz Khan ◽  
Luvai F. Motiwalla ◽  
Pranav Joshi
Keyword(s):  
Predictive Model ◽  
Real Time ◽  
Facility Management ◽  
Management Review

scholarly journals Waterborne illness and injury: a feasibility study of a site-specific predictive model for beach water quality at Beachway Park in the City of Burlington

2021 ◽  
Author(s):  
Ramien Sereshk
Keyword(s):  
Water Quality ◽  
Predictive Model ◽  
Real Time ◽  
Site Specific ◽  
E Coli ◽  
Time Basis ◽  
A Site ◽  
Persistence Model ◽  
Beach Water Quality ◽  
Beach Water

It is commonly assumed that the persistence model, using day-old monitoring results, will provide accurate estimates of real-time bacteriological concentrations in beach water. However, the persistence model frequently provides incorrect results. This study: 1. develops a site-specific predictive model, based on factors significantly influencing water quality at Beachway Park; 2. determines the feasibility of the site-specific predictive model for use in accurately predicting near real-time E. coli levels. A site-specific predictive model, developed for Beachway Park, was evaluated and the results were compared to the persistence model. This critical performance evaluation helped to identify the inherent inaccuracy of the persistence model for Beachway Park, which renders it an unacceptable approach for safeguarding public health from recreational water-borne illnesses. The persistence model, supplemented with a site-specific predictive model, is recommended as a feasible method to accurately predict bacterial levels in water on a near real-time basis.

scholarly journals PreCount: a predictive model for correcting real-time occupancy count data

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Fisayo Caleb Sangogboye ◽  
Mikkel Baun Kjærgaard
Keyword(s):  
Predictive Model ◽  
Real Time ◽  
Count Data

scholarly journals Driving energy management of front-and-rear-motor-drive electric vehicle based on hybrid radial basis function

2019 ◽  
Vol 49 (1) ◽  
pp. 47-58
Author(s):  
Binbin Sun ◽  
Tiezhu Zhang ◽  
Wenqing Ge ◽  
Cao Tan ◽  
Song Gao
Keyword(s):  
Radial Basis Function ◽  
Predictive Model ◽  
Real Time ◽  
Electric Vehicle ◽  
Energy Management ◽  
Basis Function ◽  
Motor Drive ◽  
Torque Distribution ◽  
Loss Models ◽  
Motor Operation

This paper presents mathematical methods to develop a high-efficiency and real-time driving energy management for a front-and-rear-motor-drive electric vehicle (FRMDEV), which is equipped with an induction motor (IM) and a permanent magnet synchronous motor (PMSM). First of all, in order to develop motor-loss models for energy optimization, database of with three factors, which are speed, torque and temperature, was created to characterize motor operation based on HALTON sequence method. The response surface model of motor loss, as the function of the motor-operation database, was developed with the use of Gauss radial basis function (RBF). The accuracy of the motor-loss model was verified according to statistical analysis. Then, in order to create a two-factor energy management strategy, the modification models of the torque required by driver (Td) and the torque distribution coefficient (β) were constructed based on the state of charge (SOC) of battery and the motor temperature, respectively. According to the motor-loss models, the fitness function for optimization was designed, where the influence of the non-work on system consumption was analyzed and calculated. The optimal β was confirmed with the use of the off-line particle swarm optimization (PSO). Moreover, to achieve both high accuracy and real-time performance under random vehicle operation, the predictive model of the optimal β was developed based on the hybrid RBF. The modeling and predictive accuracies of the predictive model were analyzed and verified. Finally, a hardware-in-loop (HIL) test platform was developed and the predictive model was tested. Test results show that, the developed predictive model of β based on hybrid RBF can achieve both real-time and economic performances, which is applicable to engineering application. More importantly, in comparison with the original torque distribution based on rule algorithm, the torque distribution based on hybrid RBF is able to reduce driving energy consumption by 9.51% under urban cycle.

Predictive model for hardware calibration to transmit real-time applications in VoIP networks

2019 ◽  
pp. e5190
Author(s):  
Nishant Gupta ◽  
Nitish Mahajan ◽  
Sakshi Kaushal ◽  
Naresh Kumar ◽  
Harish Kumar ◽  
...  
Keyword(s):  
Predictive Model ◽  
Real Time ◽  
Real Time Applications

scholarly journals MODELING OF PHOSPHORUS PRODUCTION PROCESSES AND DEVELOPING A MANAGEMENT STRUCTURE BASED ON GREY SYSTEMS

2021 ◽  
Author(s):  
Nigina Toktasynova ◽  
◽  
Batyrbek Suleimenov ◽  
Yelena Kulakova ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Predictive Model ◽  
Real Time ◽  
General Structure ◽  
Sinter Machine ◽  
Forecast Model ◽  
Practical Significance ◽  
Time Data ◽  
Vacuum Chambers ◽  
Model Based

The agglomeration process is one of the complex, multidimensional technological processes; it takes place under conditions of a large number of disturbing influences. As a result, the amount of return during sintering reaches 40-50%. The work is devoted to the development of a mathematical model capable of predicting and controlling the sintering point based on real-time data. As the main parameters for the construction of predictive models, data measured in real time were used – the temperature in the vacuum chambers and the gas velocity determined through the measured pressure (rarefaction) in the vacuum chambers. This paper describes the methodology and basic algorithms for modeling agglomeration processes, starting from the ingress of the charge into the sinter machine and ending with the production of a suitable agglomerate. The obtained curves of the developed mathematical model of temperature in vacuum chambers served as the basis for testing the forecast model based on the use of the theory of gray systems and the optimization algorithm of the "swarm of particles". Based on the developed mathematical model, a system for predicting the sintering point is constructed, which is the basis for determining the quality of the agglomerate, which will reduce the return volume during sintering. The general structure of the sinter control system based on a dynamic predictive model is also proposed. The practical significance of the developed predictive model based on the theory of gray systems is as follows: - forecast of the sintering point value of the agglomerate and synthesis of the control action based on the forecast; - the algorithm for constructing a mathematical model of the forecast can be used for any process that has the character of a "gray exponential law".

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