Sharif Digital Repository

Knowing different groups of customers and building effective communication with them in such a way as to guarantee the future economic interests of the organization is a very important issue in today's businesses. The attraction of profitable customers, as well as the preservation of valuable old customers, are both important, except for the precise identification of their features. The value of customer longevity plays an important role in customer segmentation, and there are numerous researches that focuses on customer value with the aim of making more profit for the organization, most of which have life-cycle customer value models as the main inputs for segmentation cCustomers have been... 

Obtaining high profit is the ultimate goal of an investor in the financial market. The key to achieve high profits in stock trading is to find the right time to trade with minimum business risk. However, it is difficult, often, to make decision about the best time to buy or sell some stocks due to the extremely dynamic and volatile behavior of the stock market. In order to resolve these problems, two steps have been followed in this research:1) Create a model to predict the final price of the stock with small error rate, and 2) Suggest the best stocks for trading to the trader. In order to achieve the goals of the first step, the stock price data of Hcltech, Maruti, Axisbank is selected and... 

Resistance spot welding is one of the fabrication processes of gas turbines. Due to few published works about using RSW for joining participation hardened nickel base super alloys like Nimonic C263 and solid solution hardened ones like Hastelloy X, this work tries to investigate the microstructure and mechanical properties of RSW joints of these super alloys. In phase one, effect of welding current on structural properties of welds, hardness profile from the center of the weld to the edge of it, failure mod and failure energy were investigated. In phase two, effect of standard heat treatment of Nimonic C263 and the initial microstructure of the base metal on the micro-structure and... 

Large amounts of relief resources such as water, tents, medical equipment and fuel after a major disaster need to reach the affected people. Satisfying the needs of victims is crucial to the success of crisis relief operations, as a lack of relief resources can lead to the suffering and loss of lives of victims. According to studies, large-scale catastrophes have occurred frequently in recent years. Therefore, it is necessary to pay more attention to the management of post-crisis resources. Since the distribution of emergency resources depends largely on the efficiency and effectiveness of logistics operations, the primary objectives include minimizing logistics time and cost, minimizing... 

in this study we intend to build a recommender system, more specifically We try to build a multi-criteria collaborative filtering. Collaborative filtering is one of the methods used in building of recommender systems. In this study, we use technical attributes to build a recommender system. Technical attributes refer to the attributes which focus on the writing style of the texts. After building the recommender system based on technical attributes, we also build a recommender system based on the conventional criteria in order to make a comparison between these two criteria. Collaborative filtering consists two major categories, namely memory-based and model-based that both of them have been... 

With the development of electrical engineering and the electrical industry, the use of copper and its alloys has grown tremendously. On the other hand, with development and modern industry, it will be difficult to meet the requirements such as high performance, cost reduction and weight reduction of the structure if only one metal material is used in the production of the desired component or structure. Aluminum can be used in combination with copper because of its properties such as high thermal and electrical conductivity. Al/Cu bonding is used in industries such as microelectronics, automobiles and batteries. This study has investigated parametrically the feasibility of uneven bonding of... 

In recent years, the attention of marketing researchers has shifted from numerical product rating to user-generated content. Because of this, customers' online reviews now play a very important role in the destiny of Internet businesses. Today, huge and comprehensive platforms have been developed to record and analyze online customer reviews. This type of unstructured data that users and Internet shoppers create based on their experiences of using products and services, has a significant impact on gaining and losing the trust of other users. After reading each review, each user can express their opinion about the usefulness of that comment, which can be seen by others. Large Internet... 

Recently, data scientists have been paying much attention to sports. Many researches have been done in this field, using data mining and machine learning techniques. The following research aims to predict the results of football matches, which consists of two general approaches. For the first and second approaches, we used video game data and match statistics, respectively. In both approaches, it was tried to predict not only the final result (win, draw, or loss) but also the final goal difference. In the first approach, the home team victory was predicted by 73% accuracy, the draw by 75.4%, and the home team defeat by 73.7%. Nevertheless, in the second approach, the home team victory was... 

Markets are becoming more saturated every day and competition between different businesses is increasing. The importance of managing Customer churn in various businesses has become increasingly important because the cost of attracting a new customer is many times greater than retaining an existing customer. With the development of data mining and its increasing expansion and the other side, the increase of stored information related to various organizations and businesses has accelerated the operations of extracting knowledge from data. Today, businesses are moving towards the use of intelligent knowledge extraction systems, of which Customer churn prediction systems are one of the most... 

Now a day, stock price prediction is known as one of the most challenging activities in the financial field. Research in price prediction models in financial markets, despite its many challenges, is still one of the most active areas for research. The price of non-linear financial assets is dynamic and unpredictable. Therefore, it is very difficult to arrangement and predict financial time series. Recently, many studies demonstrate that checking the news published in relation to a stock can significantly improve the accuracy of the prediction model.Among the latest techniques available for stock price prediction, we can mention deep learning models, which due to their high ability to... 

In today's world, decision-making has become one of the main problems and challenges for managers, despite the conflicting goals and the different scenarios. On the other hand, most existing decision-making methods are not applicable to all issues in different decision-making environments. Therefore, in this study, by presenting a new algorithm, these concerns have been reduced and a new method has been proposed using the concept of stratification recently introduced by Lotfi Zadeh. In the present study, a single system multi stratification and multi-system multi stratification are presented, which provide managers with an easier understanding and analysis of each system so that they can... 

In this thesis, a hybrid method is proposed to estimate the change point in the parameters of simple linear profiles in multistage processes under monotonic changes. In monotonic changes, the type of change is not known a priori, and the only assumption is the changes are of non-decreasing (isotonic) or non-increasing (monotonic) type. In the proposed method, at first, the stages and the parameters experiencing the change are identified and then, the changes occurred in these stages and parameters are identified and examined based on the moving window approach and support vector machine (SVM) algorithm. Finally, the maximum likelihood estimator of the change point is proposed. The... 

People's lives have been affected by the spread of the Covid-19 virus. Due to the high infectivity, governments have screened people, imposed curfews, mandated the use of masks, and so on to reduce the rate of transmission of the disease among people. Meanwhile, infected people are getting treatments: people who are slightly affected are quarantined at home, and those who are heavily affected are treated in hospitals. Hence there is an excessive increase in the hospital workload. On the one hand, this increased workload leads to physical fatigue and, on the other hand, to psychological problems, stress, etc. for the healthcare professionals. Therefore, it is very important to take care of... 

Darrieus turbines are one of the most widely used turbines in extracting energy from tidal currents. This study aimed to investigate the effect of utilizing helical blades and variable solidity ratio on the efficiency of Darrieus tidal turbines. For this purpose, three types of helical turbines with different solidity ratios have been designed, and computer simulation has been used to investigate the effect of the mentioned parameters on the efficiency of the Darrieus turbines. According to the simulation results, the helical turbine has less efficiency than the straight blade Darrieus turbine. The maximum hydrodynamic efficiency of the Darrieus turbine with straighted blades is 38.5,... 

Nowadays, capital markets play a key role in the economies of countries. Hence, this market is expanding more and more every day. In such circumstances, traditional analysis methods such as fundamental analysis and technical analysis have lost their position due to low speed and accuracy. In recent years, automated trading systems have been proposed as a solution to these problems. The online portfolio selection, which sequentially allocates capital among a set of assets aiming to maximize the final return of investment in the long run, is the core problem in algorithmic trading. In this research, we present an online portfolio selection algorithm based on pattern matching principle.... 

Algorithmic trading in financial markets with machine learning is a developing and promising field of research. Financial markets have a complex, uncertain, and dynamic nature, making them challenging for algorithmic trading. To cope with the challenges of algorithmic trading in financial markets, we propose a multi-agent deep reinforcement learning framework trained by Deep Q-learning (DQN) algorithm to perform financial trading. This framework consists of multiple cooperative agents, each of which trained on a specific timeframe, to perform financial trading on the collective intelligence of the agents. Numerical experiments are conducted on historical data of the EUR/USD currency pair.... 

Automotive steels are dominant material for the manufacturing of automotive structures and components. Since an automotive body is mostly assembled by spot welding, spot weld failure in different loading conditions has a great influence on the crashworthiness of vehicle. Therefore, investigation of microstructure and failure behavior of resistance spot welded automotive steels is an important issue. The first part of the research is dedicated to microstructural evolution and fusion zone hardness of spot welded automotive steels based on optical and SEM micrographs and hardness measurements. In the FZ of automotive steels, except for austenitic steels, a mainly martensitic microstructure was... 

With the expansion of industry, steel to copper joints applications in heat and electricity transmission equipment have increased. Steel has better mechanical properties and weldability and lower prices, and copper has better thermal and electrical conductivity properties; because of that, this dissimilar joint fits needs such as cost reduction and high efficiency. This study has parametrically investigated the feasibility of dissimilar welding of these metals using the resistance spot welding process.This study conducts three phases. In the first phase, low carbon steel and copper were directly welded, and it was found that the mechanical properties of the joint were affected by physical... 

Location-routing problems are a class of well-known supply chain problems. the purpose of these problems are to locate depots, assign customers to the located depots, and to determine the routes in a way to minimize the costs of the supply chain.In the past two decades, with a rise in environmental problems including air pollution, green location-routing problems have been introduced and studied, problems in which environmental aspects such as air pollution have been considered.In this study, first, we model a two-stage stochastic green location routing problem; this problem includes a certain number of cities that each represent a customer. the locations of the cities are known and each... 

Graphs are a language to describe and analyze connections and relations. Recent developments have increased graphs' applications in real-world problems such as social networks, researchers' collaborations, and chemical compounds. Now that we can extract graphs from real life, how can we model and generate graphs similar to a set of known graphs or that are very likely to exist but haven't been discovered yet? Therefore, this research will focus on the problem of graph generation. In graph generation, a set of graphs is a training dataset, and the goal of the thesis is to present an improved deep generative model to learn the training data's distribution, structure, and features.Identifying...