List of Articles Decision support system

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  1 - Investigate the role of Internet objects in decision support and supply chain systems
  fatemeh ranjbar parizi
  The purpose of this research is to develop a framework for understanding the convergence between the Internet of objects and the future of decision support systems and supply chain. Research results have shown that when large data are available, it is necessary to use m More

  The purpose of this research is to develop a framework for understanding the convergence between the Internet of objects and the future of decision support systems and supply chain. Research results have shown that when large data are available, it is necessary to use mathematical algorithms and complex analytical techniques. The Internet of objects improves the intelligence of business intelligence with the accumulation of data and the extraction of information. This improvement is due to the use of information technology to conclude and provide solutions based on past experiences. Manuscript profile
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  2 - Provide a new architecture for the decision support system to manage stock trading based on a combination of financial indicators
  Masoud Mansoury bijan mansouri S. Alireza hashemi G.
  Financial indicators are often used to analyze the market and predict the future of stocks. But because of the complexity of the stock market, what index to use and how reliable the output of the index used is has always been an issue. In this paper, a hybrid approach i More

  Financial indicators are often used to analyze the market and predict the future of stocks. But because of the complexity of the stock market, what index to use and how reliable the output of the index used is has always been an issue. In this paper, a hybrid approach in the form of a decision support system is used to offer the best stocks to buy or sell. The best stocks are selected from a set of stocks using a set of financial indicators. Each of these indicators acts as a model and shows its status in the future, given the stock situation in the past. Therefore, using a combination of indicators allows us to make decisions with more certainty. The efficiency of this system has been evaluated on the Iranian stock market data collection collected from 2001 to 2011. The results show that the indicators used and the combined use of them have led to the decision support system to produce proposals with high accuracy Manuscript profile
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  3 - DBCACF: A Multidimensional Method for Tourist Recommendation Based on Users’ Demographic, Context and Feedback
  Maral Kolahkaj Ali Harounabadi Alireza Nikravan shalmani Rahim Chinipardaz
  10.7508/jist.2018.04.004
  By the advent of some applications in the web 2.0 such as social networks which allow the users to share media, many opportunities have been provided for the tourists to recognize and visit attractive and unfamiliar Areas-of-Interest (AOIs). However, finding the appropr More

  By the advent of some applications in the web 2.0 such as social networks which allow the users to share media, many opportunities have been provided for the tourists to recognize and visit attractive and unfamiliar Areas-of-Interest (AOIs). However, finding the appropriate areas based on user’s preferences is very difficult due to some issues such as huge amount of tourist areas, the limitation of the visiting time, and etc. In addition, the available methods have yet failed to provide accurate tourist’s recommendations based on geo-tagged media because of some problems such as data sparsity, cold start problem, considering two users with different habits as the same (symmetric similarity), and ignoring user’s personal and context information. Therefore, in this paper, a method called “Demographic-Based Context-Aware Collaborative Filtering” (DBCACF) is proposed to investigate the mentioned problems and to develop the Collaborative Filtering (CF) method with providing personalized tourist’s recommendations without users’ explicit requests. DBCACF considers demographic and contextual information in combination with the users' historical visits to overcome the limitations of CF methods in dealing with multi- dimensional data. In addition, a new asymmetric similarity measure is proposed in order to overcome the limitations of symmetric similarity methods. The experimental results on Flickr dataset indicated that the use of demographic and contextual information and the addition of proposed asymmetric scheme to the similarity measure could significantly improve the obtained results compared to other methods which used only user-item ratings and symmetric measures. Manuscript profile
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  4 - Smart Pre-Seeding Decision Support System for Agriculture
  Ahmed Wasif Reza Kazi  Saymatul Jannat MD.Shariful  Islam Surajit  Das Barman
  10.52547/jist.15698.10.38.102
  In recent years, the Internet of Things (IoT) brings a new dimension for establishing a precision network connectivity of sensors, especially in the agriculture and farming industry, medical, economic, and several sectors of modern society. Agriculture is an important a More

  In recent years, the Internet of Things (IoT) brings a new dimension for establishing a precision network connectivity of sensors, especially in the agriculture and farming industry, medical, economic, and several sectors of modern society. Agriculture is an important area for the sustainability of mankind engulfing manufacturing, security, and resource management. Due to the exponential diminishing of the resources, innovative techniques to support the subsistence of agriculture and farming. IoT aims to extend the use of internet technology to a large number of distributed and connected devices by representing standard and interoperable communication protocols. This paper brings up a solution by IoT, presents the design and implementation of a smart pre-seeding decision support system for agricultural modernization. This project is accomplished by understanding the real-time circumstances in the agriculture field using wireless technology that highlighted the features including pH and temperature sensors, hardware, mobile application, system’s frontend, and backend analysis, and stores the extracted information in the cloud using IoT. The system is made up of frontend data acquisition, data transmission, data processing, and reception, and is also experimentally validated to find out all possible crops that can be cultivated in a specific land with the required amount of fertilizers as well as the overall crops distribution lists. Manuscript profile
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  5 - A Decision Support System based on Rough sets for Enterprise Planning under uncertainty
  سید امیرهادی مینوفام Hassan Rashidi
  Increasing rate of novice technology in global marketing arises some challenges in the economic enterprise planning. One of the appropriate approaches to resolve these challenges is using rough set theory along with decision making. In this paper, a decision support sys More

  Increasing rate of novice technology in global marketing arises some challenges in the economic enterprise planning. One of the appropriate approaches to resolve these challenges is using rough set theory along with decision making. In this paper, a decision support system with an algorithm based on rough set theory is provided. The proposed algorithm is implemented for a product line in one of the organizations under supervision of mining, industry and trade ministry. The variable effects on the enterpise aims are evaluated by analysing the strength and support criteria of rough sets. The rules are classeified as three different classes and 3 out of 12 have high reasonable averagewhie the last 3 have a relatively high violation probability. The other rules have heterogenious distribution and are not certain. The advantages of the proposed system are avoidance of enterprse capital wasting, prevention of errors due to data uncertainty, and high precision of decitions. The decision makers in the enterprise validated the increasment of simplicity and speeds of vital decision making by using the proposed system. Manuscript profile
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  6 - A Fuzzy Decision Support System For Scoring Suggestions (Case Study: Fars Regional Electric Company)
  Mohammad salehi
  10.52547/jstpi.20695.15.59.37
  Fars Regional Electric Company is one of 16 regional energy companies in the country, which is responsible for managing power transmission in the provinces of Fars and Bushehr. The company uses a variety of management systems to promote its offering of services, which i More

  Fars Regional Electric Company is one of 16 regional energy companies in the country, which is responsible for managing power transmission in the provinces of Fars and Bushehr. The company uses a variety of management systems to promote its offering of services, which is one of these systems Suggestion System. In accordance with the executive procedure of the admission, examination and implementation system of the Suggestion System, each stage of acceptance and implementation of the Suggestion is also intended to reward the position of thought. The reward of each offer is proportional to the score that it receives after approval by its specialized committee. In order to standardize the scoring for each suggestion, indicators and criteria are also included in the company's method of implementation, which is categorized in three areas of technical, non-technical and financial criteria. Given the lack of tools for calculating indices, each index must first be described and then converted into a number as a score. In this paper, while introducing the Fars Regional Electric Company, the position of the Suggestion System and the current scoring method for any Suggestion in this company, using a fuzzy inference, Using the various criteria of each Suggestion, system suggest a total score for each suggestion is close to expert opinion. The results of using this system indicate that the decision quality in the allocation of score to each Suggestion is increased and the rules in the system fuzzy inference engine provide a better score. Manuscript profile
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  7 - Choose the best suppliers with a decision support system based on self-organizing neural networks in Oil Projects
  Meysam Jafari Eskandari mostafa yousefi
  One of the most essential activities to create the appropriate supply chain is supplier selection process. The system must be capable of providing buyer's requirements in terms of quality products, at affordable prices and at the appropriate time and volume. The nature More

  One of the most essential activities to create the appropriate supply chain is supplier selection process. The system must be capable of providing buyer's requirements in terms of quality products, at affordable prices and at the appropriate time and volume. The nature of these decisions is usually complex and unstructured. In this study, self-organizing neural networks for decision making for the supplier selection decision is provided in a decision support system environment. Using self-organizing neural networks as a clustering techniques, suppliers clustered. new supplier standards compared with spikes winner and will decide on accepting or rejecting provider. The output of the model is supplier selection and evaluation by appropriate conditions for new suppliers. Manuscript profile