Sharif Digital Repository

Accurate housing price prediction has long been a strategic issue in economic market analysis and urban decision-making. Due to the structural complexity of the housing market—characterized by hidden variables, incomplete data, and nonlinear relationships among influencing factors—traditional models often fail to provide sufficient accuracy. This study aims to design and evaluate a hierarchical machine learning framework to improve housing price prediction under the non-ideal data conditions of Iran’s market. In the first stage, latent or incomplete macroeconomic variables such as daily exchange rate and gold price were estimated using intermediate models, including the SARIMA algorithm. The... 

The location problem is one of the main topics at the strategic level. This problem is investigated along with many areas such as network design and path covering problems. Routing between source and destination nodes is done in such a way that maximizes traffic coverage and reduces costs as much as possible. Routing problems are considered in goods distribution areas and urban transit systems. Goods distribution from set of cross-docks can help to reduce costs and improve resource efficiency. So, this topic is considered in this research and a suitable model is proposed. Defining and developing of the road and rail transportation networks are main topics in urban traffic management which... 

The pharmaceutical industry, as one of the most vital pillars of the healthcare system, plays a key role in improving quality of life. Rising global demand, coupled with threats such as natural disasters, pandemics, and shortages of raw materials, has highlighted the necessity of redesigning pharmaceutical supply chains with a resilience-oriented approach. This study proposes a multi-objective mathematical model for designing a pharmaceutical supply chain network that enhances system efficiency by minimizing costs, unmet demand, and delivery time. The model also accounts for drug perishability and defines disposal centers for the safe elimination of expired medicines. To address demand... 

In recent years, the popularity and applications of Non-Fungible Tokens (NFTs) have increased dramatically. For this reason, especially in the current decade, many researches have been conducted in different fields about the use of these tokens at the global level. One of the important and vital topics in the field of non-exchangeable tokens is the issues related to price prediction and the factors affecting their prices, which are mainly investigated using data analysis approaches. In this research, the factors affecting the price of non-exchangeable tokens of Bored Ape Yacht Club (BAYC) have been studied. These factors include traits, transaction data, rarity scores, transaction volume,... 

Today, demand function forecasting is one of the fundamental and critical challenges in organizational decision-making at both strategic and operational levels. Key decisions that significantly impact the success or failure of organizations -such as pricing, production planning, resource allocation, and market development- are directly influenced by the accuracy of demand forecasting. Since the demand function is typically affected by multiple factors including price, quality, economic conditions, social factors, and other variables shaping customer behavior, precise estimation requires employing diverse and accurate methods. Various approaches have been proposed in the literature for demand... 

Cloud Manufacturing (CMfg) is a service-oriented manufacturing (SOM) paradigm that provides a dynamic, scalable, and virtualized working ecosystem. The CMfg collaborative structure can be modeled as a hyper-network-based service-demand matching architecture. It is enriched with quality of service (QoS) characteristics to produce customized products in a stable and reliable network. This stability should be considered in the overall manufacturing network mechanism. This Thesis has developed a multi-dimentional model and improved it by providing absorptive and adaptive strategies utilizing available resources and capacities to enhance the system’s stability and reliability against the... 

Cardiovascular disease is one of the leading causes of death and mortality. among these diseases, heart muscle inability, especially acute decompensated heart failure is very common. There are several methods to diagnose and monitor this disease, but a method that is accurate, non-invasive, portable and easy to access and easy to measure without multiple visits to the clinic; Priority for use. Early detection and continuous monitoring of fluid status by measuring the bio-impedance (Bio-Z) measurement of thoracic magnitude or phase is critical in reducing the mortality of chronic heart failure (CHF) patients. In this dissertation, for monitoring chronic heart failure, bio-impedance chips with... 

Wheat and flour are vital components of the food supply chain, and disruptions in their supply can have profound economic, social, and political impacts. This study focuses on optimizing the costs of the wheat and flour supply chain, encompassing production, imports, transportation, and shortages, while fostering economic and social development. A two-objective Mixed Integer Linear Programming (MILP) model is developed, integrating uncertainty through a two-stage stochastic programming approach based on scenarios. The augmented epsilon constraint method is utilized to address the bi-objective optimization problem. Key outcomes include identifying optimal locations for silo construction,... 

High Swirl Combustors can provide stable flames in wide range of operating conditions. Double swirl combustors, as one of the newest designs in this field, have particular effects on improving the efficiency of combustion chambers in terms of flame stability, mixing process quality and reducing combustion pollutants. In this study, a double swirl gas turbine combustor, SGTMC, which is redesigned version of a German combustor (GTMC), has been investigated. According to experimental section of this study, lean stability limits, UHCs, CO and NOx has been measured and analyzed. Results show that this burner can provide a stable flame even in very low equivalence ratios. Also in some specific... 

The importance of routers in information transfer among networks is critical. Thus, vulnerabilities and security deficiencies in routers and the related services like routing protocols can be destructive not only for some hosts, but also for the whole network. Hence, it is necessary that 1) vulnerabilities related to the routers and their services be evaluated and analyzed, and 2) the functional aspects of routers related to the vulnerabilities be formally modeled and analyzed. In this thesis, we present a method for the evaluation and the analysis of OSPF routing protocol from the security point of view. First, reported vulnerabilities on the OSPF are collected and evaluated by a... 

Due to the development of heat pipes in different industries and special characteristics of heat pipes, in this study, it has been tried using computational fluid dynamics (CFD) method to simulate a heat pipe heat exchanger that can be a replacement for the normal radiator. The experimental model of this heat exchanger has been tested at past studies and the numerical simulation of the heat exchanger will analyze at present study. The use of heat pipe in the car radiator has many advantages such as reducing fluid pressure drop through the heat exchanger, high reliability due to the particular structure of the heat exchanger (individual performance of each heat pipe) and improving heat... 

We explain a new trust region algorithm for solving unconstrained optimization problems where the redius update is computed using the model information at the current iterate rather than at the preceding one, recently proposed by Bastin, Malmedy, Mouffe, Toint and Tomanos. Then we discuss a modification mixing the concepts of nonmonotone trust region, line search and internal doubling. We use line search to finds a point that satisfies the Wolfe conditions. After that, we explain a new trust region algorithm for solving unconstrained optimization problems where simultaneously satisfies the quasi-Newton condition at each iteration and maintains a positive-definite approximation to the Hessian... 

In the contemporary era where organizations face increasing competition in the global market, human resources analytics has emerged as a crucial strategic tool. Human resources data analysis enables organizations to make more effective workforce management decisions through a systematic and data-driven approach. The primary challenge addressed in this research is the complexity of optimal human resource allocation across various job positions. This challenge stems from multiple variables involved in the process, including candidate competencies, organizational requirements, and labor market conditions. The high volume of applicants and job positions in today’s labor market has further...