161 research outputs found
Daily wind speed forecasting through hybrid AR-ANN and AR-KF models
No full textThe nonlinearity and the chaotic fluctuations in the wind speed pattern are the reasons of inaccurate wind speed forecasting results using a linear autoregressive integrated moving average (ARIMA) model. The inaccurate forecasting of ARIMA model is a problem that reflects the uncertainty of modelling process. This study aims to improve the accuracy of wind speed forecasting by suggesting more appropriate approaches. An artificial neural network (ANN) and Kalman filter (KF) will be used to handle nonlinearity and uncertainty problems. Once ARIMA model was used only for determining the inputs structures of KF and ANN approaches, using an autoregressive (AR) Instead of ARIMA may be resulted in more simplicity and more accurate forecasting. ANN and KF based on the AR model are called hybrid AR-ANN model and hybrid AR-KF model, respectively. In this study, hybrid AR-ANN and hybrid ARKF models are proposed to improve the wind speed forecasting. The performance of ARIMA, hybrid ARANN, and hybrid AR-KF models will be compared to determine which had the most accurate forecasts. A case study will be carried out that used daily wind speed data from Iraq and Malaysia. Hybrid AR-ANN and AR-KF models performed better than ARIMA model while the hybrid AR-KF model was the most
adequate and provided the most accurate forecasts. In conclusion, the hybrid AR-KF model will result in better wind speed forecasting accuracy than other approaches, while the performances of both hybrid models will be provided acceptable forecasts compared to ARIMA model that will provide ineffectual wind speed forecasts
Multi input intervention model for evaluating the impact of the Asian crisis and terrorist attacks on tourist arrivals
No full textThe objective of this research is to study the impact of the Asian financial crisis and terrorist attacks Bali on the number of tourist arrivals by using a multi input intervention model. The focus is on the development of a model that could be used to explain the magnitude and periodic impacts of the Asian financial crisis since July 1997 and terrorist attacks referring to the Bali bombings on October 12th 2002 and October 1st 2005, respectively. Monthly data comprising the number of tourist arrivals in Indonesia via Soekarno-Hatta airport are used as the data for this case study. The results show that the Asian financial crisis and Bali bombings yield negative impacts on the number of tourist arrivals to Indonesia via Soekarno-Hatta airport. Generally, the Asian financial crisis gives a negative permanent impact after seven month delay. The first and second Bali bombings also yield negative impacts which were temporary effect after six and twelve months delay respectively. In addition, this research also discusses how to assess the effect of an intervention in transformation data
Simulation of Routing Probability in Ad Hoc Networks / Ahmad Zia Ul-Saufie Mohamad Japeri, Muhammad Hisyam Lee and Shaharuddin Salleh
No full textAn ad hoc network is a group of wireless mobile hosts forming a temporary network without the aid of any established infrastructure or centralized administration. In such an environment, it may be necessary for one mobile
host to enlist the aid of other hosts in forwarding a packet to its destination due to the limited range of each mobile host's wireless transmissions. This paper presents the simulation and programming of a probability model for
route selection of an ad hoc network for mobile computing. The route selection is based on the probability that the route is still available when a packet has to be sent through it. It is also based on the knowledge at each node of the
geographic position of all the other nodes in the network and takes into account the mobility of the nodes and the dependencies between links in a computed route. We derive a simple closed from expression for the computation
of the availability of a route, which can then be selected as the best route to serve the purposes of a specific application. Microsoft Visual C+ + was used for the purposes of running the simulation
Dynamics of fluid in oscillatory flow: the z component
No full textIn an oscillatory flow, the resistance to flow, more appropriately defined as the
impedance to flow, is a function of oscillating frequency, which refers to the
harmonic composition of the driving pressure wave. Flow in an elastic tube may
be resisted in numerous ways such as the fluid viscosity, fluid inertia and tube
elasticity. The concept of impedance arises in the dynamics of the ResistanceInductance-Capacitance.
In oscillating flow, these represent the fluid viscosity,
inertia and tube elasticity. This paper describes the effects of impedance, or the
Z component as described in-text of an oscillating flow in a valveless
impedance pump using numerical simulation. A one-dimensional lumpedsystem
model is chosen to perform the analysis in this study. The simulation
domain is a mimic to known experimental model previously conducted by Lee
et.al. [18-21]. Impedance-induced flow has shown to be combined effects of
fluid viscosity, inertia and tube elasticity. Results presented are in reasonable
agreement with experimental results presented in Ref [21] with an estimate of
16% variance. This simple model has shown to predict results with significant
values, using simple approximation
Standardized residual as response function for order identification of multi input intervention analysis
No full textGenetic algorithm-based admission test forvehicle-to-grid electricity trade services
No full textThis paper designs and evaluates a vehicle-to-grid (V2G) electricity trader capable of
selecting an appropriate subset out of a large number of electric vehicles (EVs) which
want to sell their energy to a microgrid. A genetic algorithm, tailored for this trade
coordination, reduces the amount of unmet demand forecasted one day advance in
the microgrid. Each subset is encoded to an integer r vector whose element has either 1
or 0 according to whether the associated EV is included in the subset or not. The
evaluation function estimates the fitness of a feasible solution, employing a fast heuristicbased
unit scheduler. Its lightweight-ness allows the genetic algorithm to calculate the
fitness of the massive number of feasible subsets, each of which has a fixed number of
EVs. This admission test gives a chance for EVs to contact with other microgrids when
they are not accepted to the final trade schedule. The performance measurement result
obtained from a prototype implementation reveals that the proposed scheme achieves
up to 20.8 % performance improvement over the random selection scheme in terms of
unmet demand. Moreover, the proposed scheme can efficiently cope with overload
condition, that is, many EVs are concentrated in a single microgrid, judging from its
stable performance curve
Robust hand-drawn square-roi contour detector based on adaptive thresholding
No full textHand-drawn square-ROI detector was developed as one of the vital components in RealTime
Pre-Placed Markerless Square-ROI (RPMS) recognition technique. It aims to1. To verify hand-drawn Square-ROI (Region of Interest) as a square, and 2. To create a robust and flexible square-ROI detector technique which can be applied in uneven lighting condition. In this paper, we aim to detect only the desired ROI and handle the uneven lighting condition which is one of the primary disturbance sources that may generate false results. This may lead to error in registration in Augmented Reality application due to inability to correctly define a marker. As a solution, our technique applies adaptive thresholding in order to address this issue and to create a robust and flexible technique. To verify our proposed technique, two kinds of square is used in the testing and evaluation phase. In this experiment, two influencing factorsviewing distance, and detection
accuracy were used to validate our aim. The results of the experiments show that the proposed technique efficiently detects and defines the desired square-ROI and also robust to illumination changes
Leadership styles and organisational citizenship behaviour: role ambiguity as a mediating construct
No full textElectric vehicle charger management system for interoperable charging facilities
No full textThis paper designs and develops a real-time charger management system which keeps
collecting the status information from chargers and converts control messages from the
total operation center to a command predefined for charger control. RF cards complete
the service chain from electric vehicles to the operation center, making the information
flow bidirectional. The extended coverage of the operation control over the charging
infrastructure allows an easy payment for the charging fee, based on the membership
management and personalized services. A web application is implemented on the digital
map of the target city for users to retrieve necessary information from the system and find
the best service and chargers. The massive amount of real-time charger monitoring data
is being accumulated in the database, and big data analysis will allow us to make
intelligent plans for future smart grid city services
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