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With the development of the country, the number of private car is increased rapidly, so as to the traffic problem. During the traffic jam, the bus-cluster phenomenon that the same number of bus always come together. In this article, the algorithm of the bus-cluster phenomenon has been proposed, the proposed algorithm uses the traffic jam model and the bus arrival time predict model, it analyzes the...
Application of neural networks for direct prediction of lateral-directional force and moments coefficients from the measured flight data of the research aircraft is proposed in this paper. Proposed model of neural networks appears to be a suitable practical approach to develop relationship between flight variables. This relationship eliminates the need of aerodynamic model as well as thrust model...
In this paper it is shown that there are strong statistical evidences towards the presence of long memory components in three American macroeconomic time series (Output Gap, M1 Quantity of Money and Real Interest Rates). Moreover, in this paper is presented two Fractionally Integrated Vector Autoregression (FIVAR) models with the fractional difference coefficients estimated using two different procedures...
Spark has grown both in popularity and complexity in recent years. In order to use available resources in an efficient way, users need to understand how the behavior of their applications is affected by the size of the datasets and various configuration settings. Indeed, Spark allows users to specify many configuration parameters and understanding the impact of these choices with respect to the application...
We present a two-parameter Solar Radiation Pressure model for GNSS autonomous orbit prediction, in which the parameters vary with the daily and seasonal variations in the angle between the Sun and the satellite's orbital plane. The estimator for this model's parameters is described. We present the test results of orbit prediction with this model for GPS satellites using initial orbit states based...
Resting-state functional Magnetic Resonance Imaging (rs-fMRI) holds the promise of easy-to-acquire and widespectrum biomarkers. However, there are few predictivemodeling studies on resting state, and processing pipelines all vary. Here, we systematically study resting state functionalconnectivity (FC)-based prediction across three different cohorts. Analysis pipelines consist of four steps: Delineation...
The need for higher equipment availability and lower maintenance cost is driving the development and integration of prognostic and health management (PHM) systems. Taking advantage of advances in sensor technologies, PHM systems enable a predictive maintenance strategy through continuously monitoring the health of complex systems. The core of PHM technology is prognostic which is able to estimate...
The knowledge of Inter-vehicle link duration is an important parameter in Vehicular Ad hoc Networks (VANETs), as it is useful for vehicles to delay their information transmission if link breakage is anticipated before completing the transmission. In addition, it plays a pivotal role in routing, as it allows proactive construction of long-life paths, and optimizing next-hop selection in position-based...
The user satisfaction measurement has gained high attention from Network Operators (NOs) and Service Providers (SPs) because their businesses are highly dependent on the user's satisfaction. Generally, the traditional strategies to measure the user's perception are based on Quality of Service (QoS), which is not sufficient to reflect the real user's perceived quality. Therefore, NOs and SPs start...
Spectrum occupancy prediction provides cognitive radio secondary users with proactive ability to exploit spectrum opportunities. When feasible, spectrum sensing outcome can be further analysed to assist secondary users to pre-emptively avoid interfering with primary users. Where applicable, cooperative spectrum prediction in multi-user environment has the potential to overcome limitations of local...
We propose a parametric model approach to photovoltaic generation forecasting. The problem is addressed in the common scenario where measurements of meteorological variables (i.e. solar irradiance and temperature) at the plant site are not available. The proposed method exploits cloud cover data provided by a meteorological service as well as power generation measurements, and is characterized by...
Radiation-induced soft errors are a major reliability concern in circuits fabricated at advanced technology nodes. Online soft-error vulnerability estimation offers the flexibility of exploiting dynamic fault-tolerant mechanisms for cost-effective reliability enhancement. We propose a generic run-time method with low area and power overhead to predict the soft-error vulnerability of on-chip memory...
Depth-averaged ocean current plays a significant role in marine scientific research, in particular, which is valuable for the navigation of underwater gliders. In this paper, we study the estimation and forecast of depth-averaged ocean current using underwater gliders. By considering three factors: the seawater density difference, the pressure hull compression deformation and the unstable depth intervals...
Software Analytics is gaining momentum as aresult of involved empirical research in enhancing quality andproductivity of software engineering activities. There have beenrigorous research efforts in the areas of bug prediction and testingeffort prediction by making use of historical data. The problemof predicting bug fix times is an interesting problem with lotsof advantages to industry but there have...
The estimation of experienced travel time in road networks stands for an important feature in Advanced Traveler Information Systems (ATIS). In the era of data availability, the dissemination of accurate traffic information to travelers could have a huge impact on their trip choices and thus in systems' performance. The scope of this paper is time travel modeling and prediction based on alternative...
Design Space Exploration (DSE) is a critical step in the chip design. The tradeoffs and interactions among parameters are traditionally evaluated by simulating or synthesizing a variety of designs which is intractable. The predictive modeling techniques have been applied to predict the design performance for DSE. For the system-on-a-chip (SoC) DSE cases, however, it is difficult to achieve high accuracy...
To ensure reliable communication and improve performance of a wireless communication system, it is required for the transmitter and receiver to have fair knowledge about the channel state information (CSI). Analysis of the basic channel prediction schemes like Parametric Radio channel model, Autoregressive model based prediction and Bandlimited basis expansion is done in this paper. Subspace based...
We construct a technique of time-series prediction for power consumption in small-sized systems via the mean-field theory (MFT) which approximates Bayesian inference using the expected a posterior (EAP) estimation. Here, we estimate the power consumption as an expectation of an Ising spin averaged over the Boltzmann factor of the Ising model under random fields. Here, we forecast time evolution of...
In this paper we propose a method for estimating depth from a single image using a coarse to fine approach. We argue that modeling the fine depth details is easier after a coarse depth map has been computed. We express a global (coarse) depth map of an image as a linear combination of a depth basis learned from training examples. The depth basis captures spatial and statistical regularities and reduces...
Software effort estimation consists of those procedures and activities which help to predict most accurate development effort as well as cost of a software product. After analyzing various proposed concept and theories regarding this we tried to give a new concept which works over partition of a data set. The partition procedure depends over the correlation of input features as well as output features...
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