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Hassani H.,Bournemouth University | Hassani H.,Institute for International Energy Studies IIES | Leonenko N.,University of Cardiff | Patterson K.,University of Reading
Physica A: Statistical Mechanics and its Applications | Year: 2012

The detection of long-range dependence in time series analysis is an important task to which this paper contributes by showing that whilst the theoretical definition of a long-memory (or long-range dependent) process is based on the autocorrelation function, it is not possible for long memory to be identified using the sum of the sample autocorrelations, as usually defined. The reason for this is that the sample sum is a predetermined constant for any stationary time series; a result that is independent of the sample size. Diagnostic or estimation procedures, such as those in the frequency domain, that embed this sum are equally open to this criticism. We develop this result in the context of long memory, extending it to the implications for the spectral density function and the variance of partial sums of a stationary stochastic process. The results are further extended to higher order sample autocorrelations and the bispectral density. The corresponding result is that the sum of the third order sample (auto) bicorrelations at lags h,k<1, is also a predetermined constant, different from that in the second order case, for any stationary time series of arbitrary length. © 2012 Elsevier B.V. All rights reserved.

Shafiei E.,Institute for International Energy Studies IIES
Energy Systems | Year: 2011

In this study, a comprehensive analytical tool for assessment of energy technologies and R&D resource allocation is developed taking into account the specific conditions of technology follower countries. The analytical instrument includes two interlinked models: technology assessment and optimal R&D resource allocation. Energy technology assessment and prioritization of new energy technologies are provided by a dynamic systems engineering optimization model of energy supply system. Then based on the economic and environmental impacts of technologies, optimal allocation of R&D resources for new technologies is estimated with the help of the R&D resource allocation model. This model is formulated as an optimal control problem and it considers the R&D activities and knowledge stock as the main control and state variables. This model maximizes the total net present value of resulting R&D benefits taking into account the dynamics of technological progress, knowledge and experience spillovers from advanced regions, technology adoption and R&D constraints. In this model, the role of degree of spillover, follower country's innovation capacity, knowledge complexity and absorption capacity is highlighted in the modeling of knowledge accumulation in follower countries. In this paper the mathematical formulation of the R&D resource allocation model and its linkage with the energy supply model will be described. Thereafter, the application of the interlinked models will be explained through a test case and the applicability of the energy R&D resource allocation model and its contribution to the profession of energy modeling will be concluded. © The Author(s) 2011.

Hassani H.,Bournemouth University | Hassani H.,Institute for International Energy Studies IIES | Mahmoudvand R.,Shahid Beheshti University | Zokaei M.,Shahid Beheshti University | Ghodsi M.,University of Cardiff
Fluctuation and Noise Letters | Year: 2012

The optimal value of the window length in singular spectrum analysis (SSA) is considered with respect to the concept of separability between signal and noise component, from the theoretical and practical perspective. The theoretical results confirm that for a wide class of time series of length N, the suitable value of this parameter is median {1, ..., N}. The results of both simulated and real data verify the effectiveness of the theoretical results. The theoretical results obtained here coincide with those obtained previously from the empirical point of view. © 2012 World Scientific Publishing Company.

Hassani H.,Bournemouth University | Hassani H.,Institute for International Energy Studies IIES | Mahmoudvand R.,Bu - Ali Sina University | Omer H.N.,Salahaddin University Erbil | Silva E.S.,Bournemouth University
Fluctuation and Noise Letters | Year: 2014

The aim of this paper is to study the effect of outliers on different parts of singular spectrum analysis (SSA) from both theoretical and practical points of view. The rank of the trajectory matrix, the magnitude of eigenvalues, reconstruction, and forecasting results are evaluated using simulated and real data sets. The performance of both recurrent and vector forecasting procedures are assessed in the presence of outliers. We find that the existence of outliers affect the rank of the matrix and increases the linear recurrent dimensions whilst also having a significant impact on SSA reconstruction and forecasting processes. There is also evidence to suggest that in the presence of outliers, the vector SSA forecasts are more robust in comparison to the recurrent SSA forecasts. These results indicate that the identification and removal of the outliers are mandatory to achieve optimal SSA decomposition and forecasting results. © World Scientific Publishing Company.

Majidpour M.,Institute for International Energy Studies IIES
Energy Policy | Year: 2012

This paper for the first time systematically examines the heavy duty gas turbine (HDGT) industry in the context of developing countries. It provides a comparative analysis of the HDGT industries in Iran, India and China. It contrasts their national strategies, the historical development of their technological capabilities, the similarities and differences in approach, the varying evolutionary paths and policy drivers and the reasons for their differing outcomes. This paper argues that a high level of state involvement is a prominent feature of HDGT industries in developing countries. It also argues that the development and evolution of the HDGT industries in these countries is closely interrelated with the countries' national energy policies. It clarifies why such an advanced and sophisticated industry is a strategic choice in one country, while it is seen as an inferior choice in another. © 2011 Elsevier Ltd.

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