دانشگاه صنعتی نوشیروانی بابل
مجله علمی رایانش نرم و فناوری اطلاعات
2383-1006
2588-4913
3
4
2014
12
22
Localization in Wireless Sensor Networks Based on the Compromise between Range-Based and Range-Free Methods
FA
younes
ahmadi
younes.ahmady@gmail.com
naaser
neda
Assistant professor, Faculty of Engineering, Birjand University, nneda@birjand.ac.ir
naaser.neda@gmail.com
localization demonstrates one of the most important research scope in terms of the wireless sensor networks since much of the information distributed by the sensors are important when including the localization problem. In the present study, two new methods for sensor localization have been proposed, which are indeed a compromise between rangebased and range-free techniques. In the proposed methods, the sensors make use of omnidirectional antenna for transmission of their usual information, and information processing is performed only through some sensors called landmark. The lack of need for complex processing, reduction in the energy consumption, and high precision in locating the geographical coordinates are among the most important features of the suggested protocols. Simulation results show that the proposed methods are highly efficient while reducing system’s complexity.
https://jscit.nit.ac.ir/article_51664.html
https://jscit.nit.ac.ir/article_51664_58bef9282597874c92c4e6dd24214e6e.pdf
دانشگاه صنعتی نوشیروانی بابل
مجله علمی رایانش نرم و فناوری اطلاعات
2383-1006
2588-4913
3
4
2014
12
22
Optimal Placement and Sizing of DG in Capacitor Compensated Distribution Networks Using Binary Particle Swarm Optimization
29
37
FA
رضا
باغی پور
دانشکده مهندسی برق و کامپیوتر دانشگاه صنعتی نوشیروانی بابل
r.baghipoor@stu.nit.ac.ir
سید مهدی
حسینی
استادیار دانشکده مهندسی برق و کامپیوتر دانشگاه صنعتی نوشیروانی بابل
mehdi.hosseini@nit.ac.ir
This paper presents a binary particle swarm optimization for optimally determining the size and location of distributed generation (DG) and capacitor in distribution systems. The main innovation of this paper is using both of DG and capacitor for the reliability improvement and power loss reduction. For this purpose an objective function consisting of reliability cost, power loss cost and also DG's and capacitor's investment cost are considered. The effectiveness of the proposed method is examined in the 10 and 33 bus test systems and compared with genetic algorithm method. The results obtained show appreciable reliability improvement and loss reduction while simultaneously using DG and capacitor.
distributed generation,Capacitor bank,Loss reduction,Reliability improvement,Binary particle swarm optimization
https://jscit.nit.ac.ir/article_52003.html
https://jscit.nit.ac.ir/article_52003_0f492e8fce8c041b7558eee1fd6595c6.pdf
دانشگاه صنعتی نوشیروانی بابل
مجله علمی رایانش نرم و فناوری اطلاعات
2383-1006
2588-4913
3
4
2014
12
22
An Intelligent News Based Decision Support System for Trading Stocks in Tehran Stock Exchange
55
61
FA
Nima
Shayanfar
Electrical and Computer Engineering Department, Yazd University, Yazd, Iran
nsh20100@yahoo.com
Vali
Derhami
Electrical and Computer Engineering Department, Yazd University, Yazd, Iran
vderhami@yazd.ac.ir
Stock market is known as a stochastic, nonlinear, and uncertain environment. Hence, decision making in its trading is a challenging task. Indeed, stock markets are influenced by many parameters such as stock market indicators, micro-economic and macro-economic parameters and news articles. The latter is known as one of the effective parameters, attracting analysts’ attention in recent years. If news could be successfully analyzed, predicting the stock market’s reaction to the news would be achievable. This paper proposes a decision support system for trading stocks, based on news in Tehran Stock Exchange. Here, instead of predicting stock price, we predicted the trend of stock price. To this aim, text mining was used to extract several types of features from the news. Afterwards, the most effective features were selected and then provided for Support Vector Machine (SVM) in order to be classified as a positive or negative trend. Based on comparison of several types of features we concluded that the word combination is the best solution for Farsi. The simulation results depicted that stock trend prediction is successful and profitable in many cases. Moreover, due to linguistic similarities between Farsi, Arabic and Urdu, having some powerful stock markets of the world, our proposed algorithm could pave the way for data analysis in those languages.
https://jscit.nit.ac.ir/article_66339.html
https://jscit.nit.ac.ir/article_66339_d54b96bcb7cd40543fc7690f830ed9e0.pdf