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estimation-method
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Identification and Abnormal Condition Detection of a Cement Rotary Kiln
, M.Sc. Thesis Sharif University of Technology ; Fatehi, Alireza (Supervisor)
Abstract
One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this thesis, we employed a nonlinear system identification method for identification,...
Hedonic Analysis of Land Price Case Study in Tehran, Zone 8
, M.Sc. Thesis Sharif University of Technology ; Fatemi, Farshad (Supervisor) ; Barakchian, Mahdi (Supervisor)
Abstract
The land market is one of the most important markets in the economy. Land is a factor of production, store of value, and a major part of household’s portfolio. Although price of land is an essential information for institutions like municipalities whom tax the landlords, or for financial intermediaries like banks whom use the land as collateral, studies about price of land and its spatial and time variations are scrace in Iran. Furthermore, most of studies in other countries are usually based on inflexible OLS estimators. Thus, this study has two main contributions. First, to analyze the usefulness of hedonic modeling in explaining the price of land, utilizing a unique dataset for Tehran...
A Novel Methodology for Reserve and Energy Scheduling Incorporating Vpps in High Penetration of Renewable Resources
, M.Sc. Thesis Sharif University of Technology ; Abbaspour Tehranifard, Ali (Supervisor) ; Fotuhi Firozabad, Mahmoud (Supervisor)
Abstract
Considering the high penetration of renewable energy resources in modern power systems, independent system operator faces considerable uncertainty and variability in the system under supervision. In this regard, determining and providing the appropriate amount of operational reserve is critical to overcoming uncertainty and variability to have reliable system performance. In practice, power system operators prefer to use deterministic approaches to schedule operational reserve. Such approaches have benefits in simplicity and fast calculations. Nevertheless, increasing share of renewable resources causes a considerable error in these approaches. Therefore, many researchers have proposed...
Performance Optimization of Cu Wires for Network-on-chip Based Many-core Architectures
, M.Sc. Thesis Sharif University of Technology ; Sarvari, Reza (Supervisor)
Abstract
The exponential increase in power density within a chip due to higher frequency of operation in recent years (Moor's law) is a major limiting factor for designers. Increasing the number of parallel cores instead of increasing the frequency of operation is a possible solution. The design of connections within the cores can be followed by the old process but the global interconnectsbetween the cores instead of point to point can be replaced byNetwork-on-Chip (NoC). In this thesis, The dimensions of global interconnects in many-core chips are optimized for maximum bandwidth density and minimum delay taking into account network-on-chip router latency and size effects of coppe. The optimal...
Traffic Data Modelling with Gaussian Processes
, M.Sc. Thesis Sharif University of Technology ; Gholampour, Iman (Supervisor)
Abstract
In the transportation industry, one of the most important and fundamental problems is the traffic of vehicles in the transportation roads. This problem is especially seen in large and densely populated cities such as Tehran. If traffic control is not done properly, it can lead to problems such as reduced traffic dynamics, environmental pollution, wasted drivers' time, disorder and loss of energy. If the traffic control is done after creating a traffic problem, it will not bring good results and will have low efficiency. For this reason, optimal traffic management and control has been raised as an important issue, especially in large cities. Predicting traffic flow is one of the important and...
Motion estimation of uncooperative space objects: A case of multi-platform fusion
, Article Advances in Space Research ; Volume 62, Issue 9 , 2018 , Pages 2665-2678 ; 02731177 (ISSN) ; Malaek, S. M. B ; Sharif University of Technology
Elsevier Ltd
2018
Abstract
This work describes an efficient technique to sequentially combine estimates resulting from individual sets of measurements provided by a network of satellites. The prescribed method is especially effective to estimate motion states of an uncooperative space object using range image data. The technique, which is fast and suitable for on-line applications, could also be effective to capture stray objects or those satellites that require periodic servicing. Such missions call for high degree of precision and reliable estimation methods. In fact, the proposed estimation architecture consists of a network of synchronized platforms, i.e., Observer Satellites (OS), each with processing power and...
Reliability-based network flow estimation with day-to-day variation: a model validation on real large-scale urban networks
, Article Journal of Intelligent Transportation Systems: Technology, Planning, and Operations ; Volume 22, Issue 2 , 2018 , Pages 121-143 ; 15472450 (ISSN) ; Mirjafari, P. S ; Poorzahedy, H ; Sharif University of Technology
Taylor and Francis Inc
2018
Abstract
Day-to-day variation in the travel times of congested urban transportation networks is a frustrating phenomenon to the users of these networks. These users look pessimistically at the path travel times, and learn to spend additional time to safeguard against serious penalties that await late arrivals at the destinations. These additional expenses are charges similar to the tolls in system equilibrium flow problem, but may not be collected. With this conjecture, the user equilibrium (UE) formulation of congested network flow problem would lack some necessary factors in addressing appropriate path choices. This study, following a previous work proposing pessimistic UE (PUE) flow, aims to show...
Estimating ground-level PM2.5 concentrations by developing and optimizing machine learning and statistical models using 3 km MODIS AODs: case study of Tehran, Iran
, Article Journal of Environmental Health Science and Engineering ; Volume 19, Issue 1 , 2021 ; 2052336X (ISSN) ; Arhami, M ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2021
Abstract
Purpose: In this study we aimed to develop an optimized prediction model to estimate a fine-resolution grid of ground-level PM2.5 levels over Tehran. Using remote sensing data to obtain fine-resolution grids of particulate levels in highly polluted environments in areas such as Middle East with the abundance of brightly reflecting deserts is challenging. Methods: Different prediction models implementing 3 km AOD products from the MODIS collection 6 and various effective parameters were used to obtain a reliable model to estimate ground-level PM2.5 concentrations. In this regards, the linear mixed effect model (LME), multi-variable linear regression model (MLR), Gaussian process model (GPM),...
A probabilistic modeling of photo voltaic modules and wind power generation impact on distribution networks
, Article IEEE Systems Journal ; Volume 6, Issue 2 , 2012 , Pages 254-259 ; 19328184 (ISSN) ; Aien, M ; Ehsan, M ; Sharif University of Technology
2012
Abstract
The rapid growth in use of renewable intermittent energy resources, like wind turbines (WTs) and solar panels, in distribution networks has increased the need for having an accurate and efficient method of handling the uncertainties associated with these technologies. In this paper, the unsymmetrical two point estimate method (US2PEM) is used to handle the uncertainties of renewable energy resources. The uncertainty of intermittent generation of WT, photo voltaic cells, and also electric loads, as input variables, are taken into account. The variation of active losses and imported power from the main grid are defined as output variables. The US2PEM is compared to symmetrical two point...
Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment
, Article IET Generation, Transmission and Distribution ; Volume 5, Issue 9 , 2011 , Pages 961-972 ; 17518687 (ISSN) ; Ehsan, M ; Caire, R ; Hadjsaid, N ; Sharif University of Technology
Abstract
In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution...
A probabilistic framework for water budget estimation in low runoff regions: A case study of the central Basin of Iran
, Article Journal of Hydrology ; Volume 586 , 2020 ; Ataie Ashtiani, B ; Danesh Yazdi, M ; Simmons, C. T ; Sharif University of Technology
Elsevier B.V
2020
Abstract
Utilizing ground-based measurements to obtain water budget components, especially in large scale basins, is challenging due to the limitation in the spatiotemporal availability of in-situ data. In this paper, we propose a probabilistic framework for estimating water budgets in low runoff regions using remote sensing products. By studying water budgets in the Central Basin of Iran (CBI) over 8 years period (2009–2016), we investigate the locations and time scales at which the water budget calculated from satellite products provides most closure. To this end, we use precipitation from the Tropical Rainfall Measuring Mission (TRMM), evapotranspiration from the Water Productivity Open Access...
Channel estimation and iterative equalization for long-haul coherent optical OFDM communication systems
, Article Proceedings of the 13th International Conference on Telecommunications, ConTEL 2015 ; 2015 ; 9781479989720 (ISBN) ; Ghanaatian, R ; Salehi, J. A ; Plank T ; Sharif University of Technology
Abstract
In this paper, we propose an iterative block equalizer for long-haul Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM) communication systems. The proposed scheme is based on a soft Minimum Mean-Squared Error (MMSE) iterative block equalizer. Two different channel estimation methods are also discubed. The performance and computational complexity of the proposed iterative equalization and channel estimation techniques are evaluated as well. The obtained Bit Error Rate (BER) performance reveal that the iterative equalizer outperforms the linear equalizers by almost two orders of magnitude
Optimal tuner selection using Kalman lter for a real-time modular gas turbine model
, Article Scientia Iranica ; Volume 27, Issue 2 , 2021 , Pages 806-818 ; 10263098 (ISSN) ; Vossughi, G ; Alasty, A ; Sharif University of Technology
Sharif University of Technology
2021
Abstract
In this study, a real-time exible modular modeling approach to simulating the dynamic behavior of gas turbine engines based on nonlinear thermodynamic and dynamic laws is addressed. The introduced model, which is developed in the Matlab-Simulink environment, is an object-oriented high-speed real-time computer model and is capable of simulating the dynamic behavior of a broad group of gas turbine engines due to its modular structure. Moreover, a Kalman lter-based model tuning procedure is applied to decrease the modeling errors. Modeling errors are de ned as the mismatch between simulation results and available experimental data. This tuning procedure is an underdetermined estimation problem,...
Improving the first-order structural reliability estimation by monte carlo simulation
, Article Proceedings of the Institution of Civil Engineers: Structures and Buildings ; Volume 170, Issue 7 , 2017 , Pages 532-540 ; 09650911 (ISSN) ; Barkhordari, M. A ; Barkhori, M ; Barkhori, M ; Sharif University of Technology
Abstract
The first-order reliability method (FORM) is a well-known procedure for reliability analysis in the engineering community. It provides an efficient way to calculate the failure probability of a structure. However, it introduces an unknown error in the estimations for non-linear limit states. This paper seeks a correction for the FORM by employing Monte Carlo simulation. The proposed method combines the efficiency of FORM with the robustness of the Monte Carlo method. The merits of the proposed method are illustrated through benchmark examples. The results show the high accuracy of the proposed method and a substantial reduction in the number of samples compared with crude Monte Carlo. ©...
Application of the Active Learning Method for the estimation of geophysical variables in the Caspian Sea from satellite ocean colour observations
, Article International Journal of Remote Sensing ; Volume 28, Issue 20 , 2007 , Pages 4677-4683 ; 01431161 (ISSN) ; Schaale, M ; Fell, F ; Fischer, J ; Preusker, R ; Vatandoust, M ; Shouraki, B ; Tajrishy, M ; Khodaparast, H ; Tavakoli, A ; Sharif University of Technology
Taylor and Francis Ltd
2007
Abstract
Remotely sensed data inherently contain noise. The development of inverse modelling methods with a low sensitivity to noise is in demand for the estimation of geophysical variables from remotely sensed data. The Active Learning Method (ALM) is well known to have a low sensitivity to noise. For the first time, ALM was utilized for the inversion of radiative transfer calculations with the aim of estimating chlorophyll a (Chl a), coloured dissolved organic matter (CDOM), and suspended particulate matter (SPM) in the Caspian Sea using MERIS (MEdium Resolution Imaging Spectrometer) data. ALM training is straightforward and fast. The ALM inversion models revealed the most relevant variables and...
A practical O-D matrix estimation model based on fuzzy set theory for large cities
, Article Proceedings - 23rd European Conference on Modelling and Simulation, ECMS 2009, 9 June 2009 through 12 June 2009, Madrid ; 2009 , Pages 77-83 ; 0 ; 9780955301889 (ISBN) ; Faturechi, R ; Sharif University of Technology
Abstract
Estimanon of the origin-destination trip danad matrix (O-D) plays a key role in travel analysis and transportation planning and operations. Many researchers have developed different O-D maths estimation mediods using traffic counts, which allow simple data collection as opposed to die costly traditional direct estimation methods based on home and roadside interviews. In mis papet, a new fuzzy O-D matrix estimation model (FODMEM) is proposed to estimate die O-D matrix from traffic count. A gradient-based aigoridnn. containing 3 fuzzy rule based approach to control die estimated O-D matrix changes, is proposed to solve FODMEM Since link data only represents a snapshot situation, resulting in...
Multiple interactive pollutants in water quality trading
, Article Environmental Management ; Volume 42, Issue 4 , 2008 , Pages 620-646 ; 0364152X (ISSN) ; Lence, B. J ; Shamsai, A ; Sharif University of Technology
2008
Abstract
Efficient environmental management calls for the consideration of multiple pollutants, for which two main types of transferable discharge permit (TDP) program have been described: separate permits that manage each pollutant individually in separate markets, with each permit based on the quantity of the pollutant or its environmental effects, and weighted-sum permits that aggregate several pollutants as a single commodity to be traded in a single market. In this paper, we perform a mathematical analysis of TDP programs for multiple pollutants that jointly affect the environment (i.e., interactive pollutants) and demonstrate the practicality of this approach for cost-efficient maintenance of...
Incorporating a novel confidence scoring method in a Persian spoken dialogue system
, Article SPA 2011 - Signal Processing: Algorithms, Architectures, Arrangements, and Applications - Conference Proceedings, 29 September 2011 through 30 September 2011, Poznan ; September , 2011 , Pages 74-78 ; 9781457714863 (ISBN) ; Sameti, H ; Babaali, B ; Sharif University of Technology
2011
Abstract
Reliability assessment of phonemes, syllabi, words, concepts or utterances has become the key feature of Automatic Speech Recognition (ASR) engines in order to make a decision to accept or reject a hypothesis. In this paper, we propose utterance-level confidence annotation based on combination of features extracted from multiple knowledge sources in Persian language. The experiment was conducted first to examine the performance of individual features, then to combine them using statistical data analysis and density estimation methods to assign a confidence score to utterances. Using the data collected from a Persian spoken dialogue system, we show that combining features from independent...
Identification, prediction and detection of the process fault in a cement rotary kiln by locally linear neuro-fuzzy technique
, Article 2009 International Conference on Computer and Electrical Engineering, ICCEE 2009, 28 December 2009 through 30 December 2009 ; Volume 1 , 2009 , Pages 174-178 ; 9780769539256 (ISBN) ; Fatehi, A ; Sharif University of Technology
Abstract
In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes...
Identification, prediction and detection of the process fault in a cement rotary kiln by Locally Linear Neuro-Fuzzy technique
, Article World Academy of Science, Engineering and Technology ; Volume 58 , 2009 , Pages 1128-1134 ; 2010376X (ISSN) ; Fatehi, A ; Sharif University of Technology
2009
Abstract
In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes...