Improving forecasting accuracy of crude oil price using decomposition ensemble model with reconstruction of IMFs based on ARIMA model

The accuracy of crude oil price forecasting is more important especially for economic development and considered as the lifeblood of the industry. Hence, in this paper, a decomposition-ensemble model with the reconstruction of intrinsic mode functions (IMFs) is proposed for forecasting the crude oil prices based on the well-known autoregressive moving average (ARIMA) model. Essentially, the reconstruction of IMFs enhances the forecasting accuracy of the existing decomposition ensemble models. The proposed methodology works in four steps: decomposition of the complex data into several IMFs using EEMD, reconstruction of IMFs based on order of ARIMA model, prediction of every reconstructed IMF, and finally ensemble the prediction of every IMF for the final output. A case study was carried out using two crude oil prices time series (i.e. Brent and West Texas Intermediate (WTI)). The empirical results exhibited that the reconstruction of IMFs based on order of ARIMA model was adequate and provided the best forecast. In order to check the correctness, robustness and generalizability, simulations were carried out

Crude oil price forecasting based on the reconstruction of imfs of decomposition ensemble model with arima and ffnn models

The development of economic and industry depend upon how well the accuracy of crude oil price forecasting is managed. The study aims to reduce computation complexity and enhance forecasting accuracy of decomposition ensemble model. The propose model comprises four steps which are (i) decomposing the complex data into several IMFs using ensemble empirical mode decomposition (EEMD) method, (ii) reconstructing the decomposed IMFs through autocorrelation into stochastic and deterministic components, (iii) forecasting every reconstructed component, and (iv) ensemble all forecasted components for the final output. IMFs in the stochastic component are analysed separately. The findings confirm that the stochastic component contributed more variation as compared to deterministic component. For verification and illustration, Brent, West Texas Intermediate (WTI) daily, weekly, monthly and yearly, and Pakistan monthly spot crude oil prices were used as sample study. The empirical results indicated that the proposed model statistically outperformed all the considered benchmark models including the most popular auto-regressive integrated moving average (ARIMA) model, feed forward neural network (FFNN) model, decomposition ensemble model (EEMD-ARIMA and EEMD-FFNN), reconstruction decomposition ensemble model with stochastic and deterministic components (EEMD-(S+D)-ARIMA and EEMD- (S+D)-FFNN) and Rios and De Mello (RD) reconstruction decomposition ensemble model with stochastic and deterministic components (EEMD-RD-ARIMA and EEMD-RD-FFNN). To determine the performance, two descriptive statistical measures were applied, including the root mean square error (RMSE) and mean absolute percentage error (MAPE). The MAPE of the proposed EEMD-individual stochastic and deterministic (ISD)-FFNN model for daily and weekly data of Brent and WTI are <1%, however, for monthly Brent, WTI and Pakistan data are <5% shows a good fit produce by EEMD-ISD-FFNN. The MAPE of the model EEMDISD- FFNN for yearly Brent data is <30% indicate a reasonable fit and for WTI <20% implies a good fit. Whereas the MAPE of the EEMD-(S+D)-FFNN model for Brent yearly data <20% display a good fit and for WTI data <10% indicate excellent fit. In nutshell, the recommended model for yearly data is EEMD-(S+D)-FFNN. In conclusion, the proposed method of reconstruction of IMFs based on autocorrelation enhanced the forecasting accuracy of the EEMD model

Optimal design of Remote Terminal Unit (RTU) for power system operation in smart cities

The concept of smart cities involves specifically modified infrastructure for its physical, economic and social systems which is mandatory to provide improved facilities to citizens at various levels. The major infrastructure is energy which is mainly distributed in the form of Electricity. Therefore power system operation must be optimized by making it intelligent and environmental friendly by including renewable resources and green ICT systems to achieve greater energy efficiency. In the Europe, the EU has taken an initiative by launching a concrete policy framework to make their cities capable of more energy efficient, reduction of relying on fossil fuels achieving reduction Carbon Dioxide emissions, improved impact by adding renewable energy resources to power grid. The implementation of this significant policy framework would also result in climate improvement. The EU is targeting year 2020 to accomplish such implementations. There are several ways to ensure sustainability but the addition of renewable energy resources with existing grid capacity in an intelligent manner can be an effective solution. In such addition, an optimal generation policy may be developed incorporating power flow model, contingency analysis and determination of good locations. Such generation policy can be implemented using a High Scale SCADA System. In general, the SNMP (Simple Network Management Protocol) based RTUs (Remote Terminal Units) are essential part of SCADA system so an optimal design of RTU for Energy Management System (EMS) is of high interest. This talk will describe contingency analysis with its outcome, Model of Optimized EMS and having focus on Optimal RTU Design including Optimization of RF Communication Link for RTU.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. I

Estimating Reliability of Telecommunication and Electronic Devices

This talk mainly focused on understanding of reliability parameters such as Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR). These parameters are further explored for estimation of reliability with special reference to Telecommunication and electronic devices. This talk is being augmented by adding few practical analyses of interest. Moreover, the topic is also linked with electronic design automation considering concept of Built In Self Test (BIST) for electronic chips and circuits based systems containing Telecommunication and electronic devices.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Sustainable framework form smart transportation system: a case study of Karachi

In this talk, a framework of smart transportation system is proposed, aiming to address the transportation problem in Karachi city. In modern day world, the mega cities and urban areas are on the edge of transformation into smart cities. With the advancement of engineering and technology, smart cities are designed to integrate and utilize these scientific innovations to provide smart solutions and social innovations for sustainable infrastructure, thus they are able to provide its resident highest quality of life by utilizing its resources effectively. One of the major application of smart cities is the Smart Transportation System, which provides safer, quick, environment friendly service to the residents. Thus, this study highlights the current traffic situation of Karachi and propose a framework to transform it into a smart transportation system. In order to have a smart transportation system, it is necessary to have in-depth knowledge and information about the city dynamics and its traffic related issues. Therefore, this study also highlights current traffic situation of Karachi, its road conditions and capacity, vehicles condition, alternate mean of transport (other than road-based system) and its present condition, and finally proposes a framework to develop a smart transportation system while keeping in mind the aforesaid traffic problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Nano-Fertilizers for Sustainable Crop Production under Changing Climate: A Global Perspective

Since green revolution, chemical fertilizers are deemed an indispensable input of modern crop production systems, but these have associated environmental and ecological consequences. Loss of nutrients from agricultural fields in the form of leaching and gaseous emissions has been the leading cause of environmental pollution and climate change. Ensuring the sustainability of crop production necessitates exploring other sources of nutrients and modifying prevalent nutrient sources. Nanotechnology, which utilizes nanomaterials of less than 100 nm size, may offer an unprecedented opportunity to develop concentrated sources of plant nutrients having higher-absorption rate, utilization efficacy, and minimum losses. Nanofertilizers are being prepared by encapsulating plant nutrients into nanomaterials, employing thin coating of nanomaterials on plant nutrients, and delivering in the form of nano-sized emulsions. Nano-pores and stomatal openings in plant leaves facilitate nanomaterial uptake and their penetration deep inside leaves leading to higher nutrient use efficiency (NUE). Nanofertilizers have higher transport and delivery of nutrients through plasmodesmata, which are nanosized (50–60 nm) channels between cells. The higher NUE and significantly lesser nutrient losses of nanofertilizers lead to higher productivity (6–17%) and nutritional quality of field crops. However, production and availability, their sufficient effective legislation, and associated risk management are the prime limiting factors in their general adoption as plant nutrient sources