Loading...
Search for:
zamani--reza
0.119 seconds
Total 2246 records
Design, Static and Dynamic Analysis of Crossbeam of a Gantry Milling Machine
, M.Sc. Thesis Sharif University of Technology ; Movahhedy, Mohammad Reza (Supervisor) ; Akbari, Javad (Supervisor)
Abstract
Gantry milling machines are one of the types of machine tools that have vast application in various industries. Considering requirements such as quality and roughness of work pieces which are becoming restricted day after day, it is necessary that various parts of this machine have sufficient functionality and precision so that it can fulfill the quality requirements; and production of these expensive machines be cost-effective. One of the most important parts of a gantry milling machines is its crossbeam that undergoes deflections when exposed to applied forces during work conditions and can have undesirable effect on work piece precision. Therefore, the goal of this research is to design...
Continuous-time Mean-Variance Portfolio Selection with Partial Information
, M.Sc. Thesis Sharif University of Technology ; Moghadasi, Reza (Supervisor) ; Zamani, Shiva (Co-Advisor)
Abstract
In this thesis, we study a continuous time financial market of some risky assets and a risk-free asset for investment in a finite time period. We use mean-variance approach for investment in this market. In the model considered here, the mean returns of individual assets are explicitly affected by underlying Gaussian economic factors. Using past and present information of the asset prices, a partial-information stochastic optimal control problem with random coefficients is formulated. Here, the partial information is due to the fact that the economic factors can not be directly observed. In first step, by filtering and in secound step by solving the stochastic control problem, we show that...
A Model to Determine the Inventory Policy to Allow the Transshipment of Goods between Retailers Warehouses in Vendor-Managed Inventory System
, M.Sc. Thesis Sharif University of Technology ; Akbari Jokar, Mohamad Reza (Supervisor)
Abstract
The integrative supply chain management is one of the main business processes between final consumer and supplier and it is formed by responsibilities such as production, services and information those have added value for customers and beneficiaries. Therefore and as the goal of a chain is maximization of gained value for the factors involved in chain, so, this goal can be more accessible by decreasing transportation (transportation method, tracking, …) and stock costs (conservation, ordering, …). As its purpose, this thesis intends to introduce and increase the options of goods transportation possibilities between retailers’ warehouses and evaluation of its effect on transportation and...
Portfolio Management: Combining Hierarchical Models with Prior Hierarchical Structure
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
I investigate methods of integrating prior hierarchical structure into hierarchical portfolio optimization methods. My contributions to the literature are forming a prior hierarchical structure based on investors' priorities and generating a unique representative distance matrix, which can be used as an input to other portfolio optimization methods too. In addition, I use SIC and GICs industry classifications as priory information for S&P500 companies and use them as a complementary input to the Hierarchical Risk Parity model and Hierarchical Equal Risk Contribution and compare the resultant portfolios' performance with (López de Prado, 2019)’s method of integrating prior information and...
Integrating Supervised and Unsupervised Machine Learning Algorithms for Profit-based Credit Scoring
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
In this study, we combined supervised and unsupervised machine learning algorithms, included the benefits of true identification of good borrowers and costs of false identification of bad borrowers, and then proposed a model for predicting the default of loan applicants with a profit-based approach. The results show that our proposed model has the best performance in profit measure in comparison with individual supervised models. In fact, we first divided the data into two train sets and one test set. We have constructed our model by training unsupervised models on the first train set and supervised models on the second train set. The results of implementing the model on the Australian and...
Calculating Value at Risk for Bond Portfolios by Selecting Basic Scenarios in the Historical Simulation Method
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor) ; Arian, Hamid Reza (Supervisor)
Abstract
In many methods of calculating Value-at-Risk (VaR), we need to calculate the value of the portfolio several times for different scenarios. Because an explicit formula is not available to calculate the value of some fixed income assets, calculating VaR for portfolios containing these assets imposes a heavy computational burden. In this study, we introduce a new method for calculating VaR for such portfolios. In this method, some of the existing scenarios are selected as basic scenarios and the value of the portfolio is calculated only for each of them. Next, using the calculated values, the portfolio values for other scenarios are estimated by interpolation (or extrapolation). Finally, by...
Solving High Dimensional PDEs with Machine Learning Methods and Its Application in Option Pricing
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
differential equations. These methods have extensive applications in the financial domain, including in risk hedging and derivative pricing. One of the main advantages of using deep learning methods in this area is their high capability to solve high-dimensional problems. Despite the introduction of these new methods, some of them have not performed well in certain problems. In this research, efforts have been made to improve the efficiency of these methods by enhancing the neural network architecture and modifying the learning process
Optimal Distance Calculation Method for Portfolio Optimization using
Nested Cluster Optimization
,
M.Sc. Thesis
Sharif University of Technology
;
Arian, Hamid Reza
(Supervisor)
;
Zamani, Shiva
(Supervisor)
Abstract
In the basic model of this thesis, which is called nested cluster optimization, only one distance function is used for clustering to form clusters with similar characteristics, while depending on whether the optimization model is long-only or long-short, different functions can be used. The aim of this thesis is to find the optimal distance function between assets in the simple nested cluster optimization so that during three different and separate strategies, based on three criteria of the lowest risk, the highest Sharpe ratio, and the highest return, the optimal distance function of assets is selected and clustering and finally weighting the portfolio to be done. The optimal distance...
Numerical Evaluation of Capability of Spectral Analysis Method for Laminar Damage Detection in Structures
, M.Sc. Thesis Sharif University of Technology ; Mohtatasham Dolatshahi, Kiarash (Supervisor) ; Rafiee Dehkhareghani, Reza ($item.subfieldsMap.e)
Abstract
Damage detection and rehabiltation is one of the most economical methods of increasing safety and service life of the structures. In this research, a wave-based methodology is introduced for laminar damage location in single axial members and combined axial-flexural members within a structure. Laminar damage is a kind of local damage in which the cross section area of a member decreases within a specific length. In the proposed wave-based methodology, a structure with a laminar damage is analyzed using a Finite Element (FE) software under a high frequency loading, and the strain values in specific points of the structure is collected. Thereafter, using the wave propagation theories and the...
Assessment of Risk Arising from Changes in Implied Volatility in Option Portfolios
, M.Sc. Thesis Sharif University of Technology ; Arian, Hamid Reza (Supervisor) ; Zamani, Shiva (Supervisor)
Abstract
This study delves into the intricate realm of risk evaluation within the domain of specific financial derivatives, notably options. Unlike other financial instruments, like bonds, options are susceptible to broader risks. A distinctive trait characterizing this category of instruments is their non-linear price behavior relative to their pricing parameters. Consequently, evaluating the risk of these securities is notably more intricate when juxtaposed with analogous scenarios involving fixed-income instruments, such as debt securities. A paramount facet in options risk assessment is the inherent uncertainty stemming from first-order fluctuations in the underlying asset’s volatility. The...
Hybrid LSTM-KAN variants with Quantile Loss for Value-at-Risk Forecasting
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor) ; Arian, Hamid Reza (Supervisor)
Abstract
This study proposes a novel framework for Value-at-Risk (VaR) forecasting by integrating Long Short-Term Memory (LSTM) networks with recently developed Kolmogorov-Arnold Network (KAN) variants, trained directly on a quantile loss objective. We benchmark the proposed models, including an enhanced LSTM-MultKAN variant, against a standard LSTM-Multi-Layer Perceptron (MLP) and a suite of ARMA-GARCH models. Unlike traditional approaches that rely on information criteria, we optimize the specifications of the GARCH benchmarks using a machine-learning-based validation based on the out-of-sample performance as measured by quantile loss, ensuring a fair comparison. Furthermore, to address the...
Reaction-diffusion equations with polynomial drifts driven by fractional brownian motions
, Article Stochastic Analysis and Applications ; Volume 28, Issue 6 , Oct , 2010 , Pages 1020-1039 ; 07362994 (ISSN) ; Sharif University of Technology
2010
Abstract
A reaction-diffusion equation on [0, 1]d with the heat conductivity k > 0, a polynomial drift term and an additive noise, fractional in time with H > 1/2, and colored in space, is considered. We have shown the existence, uniqueness and uniform boundedness of solution with respect to k Also we show that if k tends to infinity, then the corresponding solutions of the equation converge to a process satisfying a stochastic ordinary differential equation
New method of determination for pressure and shear frictions in the ring rolling process as analytical function
, Article Journal of Solid Mechanics ; Vol. 6, issue. 3 , 2014 , pp. 322-333 ; ISSN: 20083505 ; Sharif University of Technology
2014
Abstract
Ring rolling is one of the most significant methods for producing rings with highly precise dimensions and superior qualities such as high strength uniformity, all accomplished without wasting any materials. In this article, we have achieved analytical formulas for calculating the pressure and shear friction over the contact arcs between the rollers and ring in the ring rolling process for the material in general nonlinear hardening property. We have also asserted the best mathematical model to predict friction for rolling processes. The method we use is based on calculating the analytical stress distribution. In other words, by using of Saint-Venan principal the stress components are...
Sparse array design for millimeter-wave imaging
, Article 2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016 - Proceedings, 26 June 2016 through 1 July 2016 ; 2016 , Pages 1039-1040 ; 9781509028863 (ISBN) ; Fakharzadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
In this paper, the design of an efficient sparse array, used to reconstruct the image from millimeter-wave signals, is presented. The proposed array takes advantage of the sparsity concept of the image in the spatial Fourier domain to reduce the number of array elements such that the beam pattern of the designed array meets the desired beamwidth and sidelobe level. Simulation and measured results confirm the effectiveness of the proposed design on high-quality reconstruction of the image, while 85% reduction in the number of elements is achieved as well as the reduction in scan time and system complexity
A feature fusion based localized multiple kernel learning system for real world image classification
, Article Eurasip Journal on Image and Video Processing ; Volume 2017, Issue 1 , 2017 ; 16875176 (ISSN) ; Jamzad, M ; Sharif University of Technology
2017
Abstract
Real-world image classification, which aims to determine the semantic class of un-labeled images, is a challenging task. In this paper, we focus on two challenges of image classification and propose a method to address both of them simultaneously. The first challenge is that representing images by heterogeneous features, such as color, shape and texture, helps to provide better classification accuracy. The second challenge comes from dissimilarities in the visual appearance of images from the same class (intra class variance) and similarities between images from different classes (inter class relationship). In addition to these two challenges, we should note that the feature space of...
1.5-D sparse array for millimeter-wave imaging based on compressive sensing techniques
, Article IEEE Transactions on Antennas and Propagation ; Volume 66, Issue 4 , April , 2018 , Pages 2008-2015 ; 0018926X (ISSN) ; Fakharzadeh, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
The goal of this paper is to reduce the antenna count in a millimeter (mm)-wave imaging system by proposing both hardware and software solutions. The concept of image sparsity in the transform domain is utilized to present the compressive sensing (CS) formulation for both mono-static and multistatic imaging at mm-wave frequencies. To reduce the complexity of the imaging system and reconstruction process, we introduce 1.5-D array structure, which is a random sparse array with orthogonal element locations. It is shown that the peak signal-to-noise ratio (PSNR) of the reconstructed image obtained by a 1.5-D array with 65% sparsity is very close to the PSNR of a uniform 2-D array for mono-static...
An efficient strategy to overproduce glutamic acid in Corynebacterium glutamicum fermentation
, Article Scientia Iranica ; Volume 8, Issue 3 , 2001 , Pages 203-206 ; 10263098 (ISSN) ; Roostaazad, R ; Sharif University of Technology
Sharif University of Technology
2001
Abstract
In this paper, effect of penicillin addition in enhancing the secretion of glutamic acid by Corynebacterium glutamicum was studied. The proper time of adding penicillin to maximize glutamic acid production was found to drift at repeated trials. In contrast, maximum acid productivity was obtained when penicillin was injected at a proper biomass concentration of about 7.7 gram dry weight per lit (gdw/l). Moreover, rate of consumption of sugar and ammonia through the course of glutamic acid fermentation was monitored. In production phase, these two rates were correlated properly with a ratio of 3.2:1 which is comparable to the theoretical stoichiometric value of 5:1. Therefore, through feeding...
Credit Risk Analysis of a Bank's Loan Portfolio
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor)
Abstract
Risk management is one of the most important topics in banking. Risk management in banking is divided to several categories including credit risk. Credit risk is also divided to individual credit risk and portfolio credit risk. In Iran many of banks have worked on individual credit risk models, but few of them have worked on portfolio models because these models have developed only in recent years. In our project we present three categories of credit risk models and then analyze the data of a private bank in Iran with CreditPortfolioView model. In CreditPortfolioView model, macroeconomic parameters are used to analyze the correlated behavior of individuals as a benchmark in different...
Project Finance and Motivations and Optimum Approach of Using it in LNG Industry of Iran
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor)
Abstract
Project Finance is a novel approach in financing big projects. High debt ratio, independency to promoter credit and establishing a special purpose company, are some of project finance characteristics that could be very beneficial in some projects. Liquid Natural Gas (LNG) is a solution for exporting natural gas to far destination. As economical and environmental benefits of using natural gas have been increased in recent years, LNG industry has been experienced rapid growth. In this project we analyze project finance and then describe economical motivation of using this method in LNG industry of Iran.
Collapsible Behavior of Gorgan Loess Using Odeometer
, M.Sc. Thesis Sharif University of Technology ; Haeri, Mohsen (Supervisor)
Abstract
In nature, there are types of soils that when goinging under stress at constant moisture, or increase of moisture at constant stress, or change of both characters, they show a sudden and high level decrease in their volume. These type of soils are named as Collapsible soils. Iran is one of the countries that at some parts of its land collapsible soils are found. In this research by using of laboratory equipments, the volume change behavior of collapsible loess soils of Gorgan plain (North of Iran) is evaluated under increase of water content and inundation stress. In these experiments, the usual odeometer cell has been used for exploring the behaviour of collapsibility and volume change of...