fuzzy logic

List of Articles fuzzy logic

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1 - Trust evaluation in unsupervised network: A fuzzy logic approach
Golnar Assadat Afzali Monireh Hosseini
10.7508/jist.2014.04.005

Because of the possibility of anonymity and impersonation in social networks, trust plays an important role in these networks. Pear to pear networks, by eliminating the supervisor roles, besides its benefit in decreasing management costs, have problems in trust and secu More

Because of the possibility of anonymity and impersonation in social networks, trust plays an important role in these networks. Pear to pear networks, by eliminating the supervisor roles, besides its benefit in decreasing management costs, have problems in trust and security of users. In this research, by using social networks as supervised networks, trust level of users is evaluated and by identifying these users in unsupervised networks, appropriate trust level is assigned to them. Manuscript profile
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2 - Selecting Enterprise Resource Planning System Using Fuzzy Analytic Hierarchy Process Approach
hojatallah hamidi
10.7508/jist.2015.04.001

To select an enterprise resource planning (ERP) system is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively systematic selection policy for ERP system is very important to the success of ERP pro More

To select an enterprise resource planning (ERP) system is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively systematic selection policy for ERP system is very important to the success of ERP project. In this paper, we propose a fuzzy analytic hierarchy process (FAHP) method to evaluate the alternatives of ERP system. The selection criteria of ERP system are numerous and fuzzy, so how to select an adequate ERP system is crucial in the early phase of an ERP project. The framework decomposes ERP system selection into four main factors. The goal of this paper is to select the best alternative that meets the requirements with respect to product factors, system factors, management factors and vendor factors. The sub-attributes (sub-factors) related to ERP selection have been classified into thirteen main categories of Functionality, Reliability , Usability , Efficiency , Maintainability , Portability , Cost, Implementation time, User friendliness , Flexibility , Vendor Reputation , Consultancy Services, and R&D Capability and arranged in a hierarchy structure. These criteria and factors are weighted and prioritized and finally a framework is provided for ERP selection with the fuzzy AHP method. Also, a real case study from Iran (PARDIS-LO Company) is also presented to demonstrate efficiency of this method in practice. Manuscript profile
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3 - Short Time Price Forecasting for Electricity Market Based on Hybrid Fuzzy Wavelet Transform and Bacteria Foraging Algorithm
keyvan Borna Sepideh Palizdar
10.7508/jist.2016.04.001

Predicting the price of electricity is very important because electricity can not be stored. To this end, parallel methods and adaptive regression have been used in the past. But because dependence on the ambient temperature, there was no good result. In this study, lin More

Predicting the price of electricity is very important because electricity can not be stored. To this end, parallel methods and adaptive regression have been used in the past. But because dependence on the ambient temperature, there was no good result. In this study, linear prediction methods and neural networks and fuzzy logic have been studied and emulated. An optimized fuzzy-wavelet prediction method is proposed to predict the price of electricity. In this method, in order to have a better prediction, the membership functions of the fuzzy regression along with the type of the wavelet transform filter have been optimized using the E.Coli Bacterial Foraging Optimization Algorithm. Then, to better compare this optimal method with other prediction methods including conventional linear prediction and neural network methods, they were analyzed with the same electricity price data. In fact, our fuzzy-wavelet method has a more desirable solution than previous methods. More precisely by choosing a suitable filter and a multiresolution processing method, the maximum error has improved by 13.6%, and the mean squared error has improved about 17.9%. In comparison with the fuzzy prediction method, our proposed method has a higher computational volume due to the use of wavelet transform as well as double use of fuzzy prediction. Due to the large number of layers and neurons used in it, the neural network method has a much higher computational volume than our fuzzy-wavelet method. Manuscript profile
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4 - An Improved Sentiment Analysis Algorithm Based on Appraisal Theory and Fuzzy Logic
Azadeh Roustakiani Neda Abdolvand Saeideh Rajaei Harandi
10.7508/jist.2018.02.004

Millions of comments and opinions are posted daily on websites such as Twitter or Facebook. Users share their opinions on various topics. People need to know the opinions of other people in order to purchase consciously. Businesses also need customers’ opinions and big More

Millions of comments and opinions are posted daily on websites such as Twitter or Facebook. Users share their opinions on various topics. People need to know the opinions of other people in order to purchase consciously. Businesses also need customers’ opinions and big data analysis to continue serving customer-friendly services, manage customer complaints and suggestions, increase financial benefits, evaluate products, as well as for marketing and business development. With the development of social media, the importance of sentiment analysis has increased, and sentiment analysis has become a very popular topic among computer scientists and researchers, because it has many usages in market and customer feedback analysis. Most sentiment analysis methods suffice to split comments into three negative, positive and neutral categories. But Appraisal Theory considers other characteristics of opinion such as attitude, graduation and orientation which results in more precise analysis. Therefore, this research has proposed an algorithm that increases the accuracy of the sentiment analysis algorithms by combining appraisal theory and fuzzy logic. This algorithm was tested on Stanford data (25,000 comments on the film) and compared with a reliable dictionary. Finally, the algorithm reached the accuracy of 95%. The results of this research can help to manage customer complaints and suggestions, marketing and business development, and product testing. Manuscript profile

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List of Articles fuzzy logic