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uncertainty-analysis
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Pandemic-Aware Day-Ahead demand forecasting using ensemble learning
, Article IEEE Access ; Volume 10 , 2022 , Pages 7098-7106 ; 21693536 (ISSN) ; Ahmadi, A ; Taheri, S ; Fotuhi Firuzabad, M ; Moeini Aghtaie, M ; Lehtonen, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
Electricity demand forecast is necessary for power systems' operation scheduling and management. However, power consumption is uncertain and depends on several factors. Moreover, since the onset of covid-19, the electricity consumption pattern went through significant changes across the globe, which made the forecasting demand more challenging. This is mainly due to the fact that pandemic-driven restrictions changed people's lifestyles and work activities. This calls for new forecasting algorithms to more effectively handle these conditions. In this paper, ensemble-based machine learning models are utilized for this task. The lockdown temporal policies are added to the feature set in order...
Addressing the epistemic uncertainty in seismic hazard analysis as a basis for seismic design by emphasizing the knowledge aspects and utilizing imprecise probabilities
, Article Bulletin of Earthquake Engineering ; Volume 20, Issue 2 , 2022 , Pages 741-764 ; 1570761X (ISSN) ; Rofooei, F. R ; Sharif University of Technology
Springer Science and Business Media B.V
2022
Abstract
Epistemic uncertainty in seismic hazard analysis is traditionally addressed by utilizing a logic-tree structure with subjective probabilities for branches. However, many studies have argued that probability is not a suitable choice for addressing epistemic uncertainties; in particular in addressing the background knowledge supporting the probabilities. In this regard, the application of imprecise probability (IP) is investigated. It is discussed that IP could provide a flexible tool for a more objective presentation of experts' knowledge. Moreover, the importance of addressing the strength of knowledge and surprises relative to knowledge in seismic hazard analysis along with methods to do...
Probabilistic analysis to analyze uncertainty incorporating copula theory
, Article Journal of Electrical Engineering and Technology ; Volume 17, Issue 1 , 2022 , Pages 61-71 ; 19750102 (ISSN) ; Shahzad, M ; Munir, H. M ; Nawaz, A ; Fahal, N. A. M ; Khan, M. Y. A ; Ahmed, S ; Sharif University of Technology
Korean Institute of Electrical Engineers
2022
Abstract
The emerging trend of distribution generation with existing power system network leads uncertainty factor. To handle this uncertainty, it is a provocation for the power system control, planning, and operation engineers. Although there are numerous techniques to model and evaluate these uncertainties, but in this paper the integration of Copula theory with Improved Latin-hypercube Sampling (ILHS) are incorporated for Probabilistic load Flow (PLF) evaluation. In probabilistic research approaches, the dominant interest is to achieve appropriate modelling of input random variables and reduce the computational burden. To address the said problem, Copula theory is applied to execute the modelling...
Efficient seismic risk assessment of irregular steel-framed buildings through endurance time analysis of consistent fish-bone model
, Article Structural Design of Tall and Special Buildings ; Volume 31, Issue 2 , 2022 ; 15417794 (ISSN) ; Hosseini, M ; E. Estekanchi, H ; Sharif University of Technology
John Wiley and Sons Ltd
2022
Abstract
The seismic risk framework of building structures has been presented to reduce earthquake-induced adverse consequences. In this context, probabilistic analysis of engineering demand parameters (EDPs) is always associated with many uncertainties and high computational demand for use in practical applications. This study has been presented to efficiently estimate the distribution of EDPs in probabilistic seismic risk assessment of irregular steel moment-resisting frames (SMRFs). For this purpose, the incorporation of the consistent fish-bone (CFB) model and the endurance time (ET) analysis method has been used. The proposed method (i.e., CFB-ET) has a substantial impact on reducing the...
Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations
, Article Environmental Science and Pollution Research ; Volume 20, Issue 7 , 2013 , Pages 4777-4789 ; 09441344 (ISSN) ; Kamali, N ; Rajabi, M. M ; Sharif University of Technology
2013
Abstract
Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to...
Multivariable control of an industrial boiler-turbine unit with nonlinear model: A comparison between gain scheduling and feedback linearization approaches
, Article Scientia Iranica ; Volume 20, Issue 5 , 2013 , Pages 1485-1498 ; 10263098 (ISSN) ; Alasty, A ; Saffar Avval, M ; Bakhtiari Nejad, F ; Sharif University of Technology
Sharif University of Technology
2013
Abstract
Due to demands for the economical operations of power plants and environmental awareness, performance control of a boiler-turbine unit is of great importance. In this paper, a nonlinear Multi Input-Multi Output model (MIMO) of a utility boilerturbine unit is considered. Drum pressure, generator electric output and drum water level (as the output variables) are controlled by manipulation of valves position for fuel, feedwater and steam flows. After state space representation of the problem, two controllers, based on gain scheduling and feedback linearization, are designed. Tracking performance of the system is investigated and discussed for three cases of 'near', 'far' and 'so far' setpoints....
Model-based needle control in prostate percutaneous procedures
, Article Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine ; Volume 227, Issue 1 , 2013 , Pages 58-71 ; 09544119 (ISSN) ; Jahed, M ; Sharif University of Technology
2013
Abstract
In percutaneous applications, needle insertion into soft tissue is considered as a challenging procedure, and hence, it has been the subject of many recent studies. This study considers a model-based dynamics equation to evaluate the needle movement through prostate soft tissue. The proposed model estimates the applied force to the needle using the tissue deformation data and finite element model of the tissue. To address the role of mechanical properties of the soft tissue, an inverse dynamics control method based on sliding mode approach is used to demonstrate system performance in the presence of uncertainties. Furthermore, to deal with inaccurate estimation of mechanical parameters of...
On the quantification of seismic performance factors of Chevron Knee Bracings, in steel structures
, Article Engineering Structures ; Volume 46 , 2013 , Pages 155-164 ; 01410296 (ISSN) ; Mofid, M ; Sharif University of Technology
Abstract
As a matter of fact, it is necessary to have the values of Response Modification Factor R, Over-strength Factor Ω0, and Deflection Amplification Factor Cd in order to design seismic-force-resisting systems according to design and loading codes. This study is intended to evaluate these factors for a structural lateral bracing system called Chevron Knee Bracing (CKB). In this type of bracing, the knee elements assist the system to dissipate energy through the formation of plastic flexural and/or shear hinges within the presented bracing system. The approach utilized in this study is according to FEMA P695 based on low probability of structural collapse and involves nonlinear static and dynamic...
Stochastic modeling of the energy supply system with uncertain fuel price - A case of emerging technologies for distributed power generation
, Article Applied Energy ; Volume 93 , 2012 , Pages 668-674 ; 03062619 (ISSN) ; Saboohi, Y ; Sharif University of Technology
2012
Abstract
A deterministic energy supply model with bottom-up structure has limited capability in handling the uncertainties. To enhance the applicability of such a model in an uncertain environment two main issues have been investigated in the present paper. First, a binomial lattice is generated based on the stochastic nature of the source of uncertainty. Second, an energy system model (ESM) has been reformulated as a multistage stochastic problem. The result of the application of the modified energy model encompasses all uncertain outcomes together and enables optimal timing of capacity expansion. The performance of the model has been demonstrated with the help of a case study. The case study has...
Robust DTC control of doubly-Fed induction machines based on input-output feedback linearization using recurrent neural networks
, Article Journal of Power Electronics ; Volume 11, Issue 5 , 2011 , Pages 719-725 ; 15982092 (ISSN) ; Hashemnia, M. N ; Faiz, J ; Sharif University of Technology
2011
Abstract
This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine...
Adaptive sliding mode control of a piezo-actuated bilateral teleoperated micromanipulation system
, Article Precision Engineering ; Volume 35, Issue 2 , 2011 , Pages 309-317 ; 01416359 (ISSN) ; Ahmadian, M. T ; Vossoughi, G ; Rezaei, S. M ; Zareinejad, M ; Sharif University of Technology
Abstract
Piezoelectric actuators are widely used in micro manipulation applications. However, hysteresis nonlinearity limits the accuracy of these actuators. This paper presents a novel approach for utilizing a piezoelectric nano-stage as the slave manipulator of a teleoperation system based on a sliding mode controller. The Prandtl-Ishlinskii (PI) model is used to model actuator hysteresis in feedforward scheme to cancel out this nonlinearity. The presented approach requires full state and force measurements at both the master and slave sides. Such a system is costly and also difficult to implement. Therefore, sliding mode unknown input observer (UIO) is proposed for full state and force...
Spatial-temporal assessment and redesign of groundwater quality monitoring network: A case study
, Article Environmental Monitoring and Assessment ; Volume 172, Issue 1-4 , January , 2011 , Pages 263-273 ; 01676369 (ISSN) ; Abrishamchi, A ; Tajrishy, M ; Sharif University of Technology
2011
Abstract
Assessment of groundwater quality monitoring networks requires methods to determine the potential efficiency and cost-effectiveness of the current monitoring programs. To this end, the concept of entropy has been considered as a promising method in previous studies since it quantitatively measures the information produced by a network. In this study, the measure of transinformation in the discrete entropy theory and the transinformation- distance (T-D) curves, which are used frequently by other researchers, are used to quantify the efficiency of a monitoring network. This paper introduces a new approach to decrease dispersion in results by performing cluster analysis that uses fuzzy...
Pareto-based robust optimization of water-flooding using multiple realizations
, Article Journal of Petroleum Science and Engineering ; Volume 132 , 2015 , Pages 18-27 ; 09204105 (ISSN) ; Pishvaie, M. R ; Sharif University of Technology
Elsevier
2015
Abstract
Robust optimization (RO) approach is inherently a multi-objective paradigm. The proposed multi-objective optimization formulation would attempt to find the optimum - yet robust - water injection policies. Two multi-objective, Pareto-based robust optimization scenarios have been investigated to encounter the permeability uncertainties. These multi-objective RO scenarios have been done based on a small representative set of realizations but they have introduced optimum points that could be reliable for the original set of realizations either. In both scenarios, the desired objective functions are expected value and variance of Net Present Value (NPV). The underlying RO scenarios have been done...
Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling
, Article Advances in Water Resources ; Volume 76 , 2015 , Pages 127-139 ; 03091708 (ISSN) ; Ataie Ashtiani, B ; Janssen, H ; Sharif University of Technology
Abstract
The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of...
Design of an expert system to estimate cost in an automated jobshop manufacturing system
, Article 40th International Conference on Computers and Industrial Engineering: Soft Computing Techniques for Advanced Manufacturing and Service Systems, CIE40 2010, 25 July 2010 through 28 July 2010, Awaji ; 2010 ; 9781424472956 (ISBN) ; Mahdavi Amiri, N ; Sharif University of Technology
2010
Abstract
We propose a cost estimation model based on a fuzzy rule back-propagation network (BPN), configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach we determine the optimal path in the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty
A queueing approach to production-inventory planning for supply chain with uncertain demands: Case study of PAKSHOO Chemicals Company
, Article Journal of Manufacturing Systems ; Volume 29, Issue 2-3 , July , 2010 , Pages 55-62 ; 02786125 (ISSN) ; Modarres, M ; Ghasemzadeh, F ; Fathi, M ; Sharif University of Technology
2010
Abstract
In some industries such as the consumable product industry because of small differences between products made by various companies, customer loyalty is directly related to the availability of products required at that time. In other words, in such industries demand cannot be backlogged but can be totally or partly lost. So companies of this group use make-to-stock (MTS) production policy. Therefore, in these supply chains, final product warehouses play a very important role, which will be highlighted by considering the demand uncertainty as it happens in real world, especially in the consumable product industries in which demand easily varies according to the customer's taste variation,...
Adaptive attitude and position control of an insect-like flapping wing air vehicle
, Article Nonlinear Dynamics ; Volume 85, Issue 1 , 2016 , Pages 47-66 ; 0924090X (ISSN) ; Taymourtash, N ; Sharif University of Technology
Springer Netherlands
Abstract
This study describes an adaptive sliding mode technique for attitude and position control of a rigid body insect-like flapping wing model in the presence of uncertainties. For this purpose, a six-degrees-of-freedom nonlinear and time-varying dynamic model of a typical hummingbird is considered for simulation studies. Based on the quasi-steady assumptions, three major aerodynamic loads including delayed stall, rotational lift and added mass are presented and analyzed, respectively. Using the averaging theory, a time-varying system is then transformed into the time-invariant system to design the adaptive controller. The controller is designed so that the closed-loop system will follow any...
A review of global gas flaring and venting and impact on the environment: Case study of Iran
, Article International Journal of Greenhouse Gas Control ; Volume 49 , 2016 , Pages 488-509 ; 17505836 (ISSN) ; Zohrabian, A ; Gholipour, M. J ; Kalnay, E ; Sharif University of Technology
Elsevier Ltd
Abstract
After a brief review of the global gas flaring and venting in oil industries including the emission of air pollutants and greenhouse gases and the amount of energy resources wasted, the focus is on Iran as a major oil producing and the world's third largest gas flaring country. Gas flaring is also practiced in natural gas industries, petroleum refining and petrochemical plants, although the level of emission is very low compared with emissions from oil production. The historical emission of these gases globally and Iran specifically, geographic location of emission sources, composition of gases, environmental impacts of gas flaring and the current and future projects to mitigate emissions...
Sea-level rise impacts on seawater intrusion in coastal aquifers: review and integration
, Article Journal of Hydrology ; Volume 535 , 2016 , Pages 235-255 ; 00221694 (ISSN) ; Mahmoodzadeh, D ; Ataie Ashtiani, B ; Simmons, C. T ; Sharif University of Technology
Abstract
Sea-level rise (SLR) influences groundwater hydraulics and in particular seawater intrusion (SWI) in many coastal aquifers. The quantification of the combined and relative impacts of influential factors on SWI has not previously been considered in coastal aquifers. In the present study, a systematic review of the available literature on this topic is first provided. Then, the potential remaining challenges are scrutinized. Open questions on the effects of more realistic complexities such as gradual SLR, parameter uncertainties, and the associated influences in decision-making models are issues requiring further investigation.We assess and quantify the seawater toe location under the impacts...
Design of a fractional order PID controller for an AVR using particle swarm optimization
, Article Control Engineering Practice ; Volume 17, Issue 12 , 2009 , Pages 1380-1387 ; 09670661 (ISSN) ; Karimi Ghartemani, M ; Sadati, N ; Parniani, M ; Sharif University of Technology
Abstract
Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned design procedure. PSO is an advanced search procedure that has proved to have very high efficiency. A novel cost function is defined to facilitate the control strategy over both the time-domain and the frequency-domain specifications. Comparisons are made with a PID controller and it is shown...