توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقالههای نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده میشوند.
اطلاعات انتشار: Iranian Economic Review، بيستم،شماره۴۴، ۲۰۱۶، سال ۰
تعداد صفحات: ۲۲
This paper attempts to re–investigate the catching–up (stochastic convergence) hypothesis among the selected 16 OECD countries applying the time series approach of convergence hypothesis with annual data over one century. To reach this aim, we propose a model which specifies a trend function, incorporating both types of structural breaks – that is, sharp breaks and smooth shifts using dummy variables and Fourier function respectively. In order to detect the sharp breaks, we apply the multiple structural break models (Bai & Perron, 1998) and the Fourier function proposed in Becker et al. (2004) to capture the smooth shifts. Our results show that most divergence process occurred over World War I (WWI) and World War II (WWII). Among the 69 estimated break points occurred over the period 1870–2010, 75 % of those break points result in catching–up and the remainder results in divergence.
۲A strategy for forecasting option price using fuzzy time series and least square support vector regression with a bootstrap model
اطلاعات انتشار: Scientia Iranica، بيست و يكم،شماره۳، ۲۰۱۴، سال ۰
تعداد صفحات: ۱۱
Recently, the strategy for forecasting option price has become a popular financial topic because options are important tools on risk management in financial investments. The well–known Black–Scholes model (B–S model) is widely used for option pricing. In B–S model, the normal distribution assumption is important. However, the financial data in real life may not follow the normal distribution assumption. For this reason, this paper proposes a novel hybrid model, which is a nonlinear prediction model without normal distribution assumptions to forecast the option prices. The proposed model is composed of a fuzzy time series (FTS) model, a least square support vector regression (LSSVR), and a bootstrap method. In the proposed model, FTS model is firstly used to fuzzify dataset and to build historical database. Subsequently, the proposed method uses the remainder contractual time to search similar historical trends as training samples. Finally, we use the bootstrap method on LSSVR to enhance the prediction accuracy. The experiment results show that the proposed model outperforms traditional time series models and several hybrid models in terms of the root mean square error (RMSE), the mean absolute error (MAE) and the correlation coefficient (r) of actual and forecasted option price.
اطلاعات انتشار: Scientia Iranica، بيست و دوم،شماره۲، ۲۰۱۵، سال ۰
تعداد صفحات: ۱۴
Radio frequency identification (RFID) technology is emerging as an important technology for improving management efficiency. Web–based systems (WBS) are particularly useful for managing operations spread over multiple locations. Artificial intelligence (AI) can be used to process uncertain and incomplete information which inevitably occurs in the real world. This study aims to enhance managerial efficiency through the integration of RFID, web–based technologies, and artificial intelligence. RFID is primarily used to identify managerial objects while; web–based technology is used for data management; and AI is used to analyze the collected data. A real case is used to validate the applicability of the proposed method. Experimental results show that the integration of RFID, web–based systems, and AI can be effectively applied in a practical environment. The proposed method can improve managerial efficiency, data transfer, data quality, and service process time. This study is one of the first to investigate the integration of RFID technology with web–based technology and AI.
۴Efficient Packet Replication Control for a Geographical Routing Protocol in Sparse Vehicular Delay Tolerant Networks
اطلاعات انتشار: Scientia Iranica، بيست و دوم،شماره۴، ۲۰۱۵، سال ۰
تعداد صفحات: ۱۷
To date, many vehicular ad hoc network unicast routing protocols have been proposed to support efficient packet transmission between vehicles in urban environments. However, when there is insufficient vehicle density during non–rush hour times, the vehicular ad hoc network is often intermittently connected. These unicast routing protocols therefore perform poorly when forwarding packets over this vehicular disruption tolerant network. This paper adopts the controlled replication approach in a proposed IG–Ferry routing protocol to spray a limited number of packet copies, denoted by the packet token values, to relay vehicles in a vehicular disruption tolerant network. We then identify three kinds of relay vehicles, i.e., direct buses, non–direct buses and private cars, according to their travel itineraries. Based on the proposed delay evaluation function for the three types of intermediate vehicles, the IG–Ferry packet spraying mechanism, instead of the traditional binary spraying one, can efficiently spray appropriate packet tokens to vehicles. Finally, intensive NS2 simulations are conducted using the realistic Shanghai city vehicle traffic trace, IEEE 802.11p protocol with EDCA and Nakagami radio propagation model to show that IG–Ferry outperforms three well–known VDTN routing protocols, in terms of average packet delivery ratios, end–to–end transmission delays and packet replication overheads with respect to various combinations of five communication parameters.
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