Sharif Digital Repository

In the field of supply chain, management constantly seeks to adopt strategies for realizing its targeted objectives. The supply chain, therefore, includes integrated production-distribution processes with all effective parts where proper management requires a comprehensive and dynamic approach. It is necessary to meet required items at required time. This becomes more important with the supply systems providing items. On the other hand, the difficulty of supply chain management, decisions, and policy-making can be increased by a wide range of conditions such as changes in demand. Thus, a comprehensive approach is needed to take the present dynamics into account. The current paper develops a... 

Human as an important part of the natural environment and can exert their positive or negative effects in the form of long-term and short-term on a natural environment. Human impacts on the natural system are very complex and consist of various components. The most considerable among them from past to now are maybe land use and land cover change, although, the impact of dam construction, water pollution, air pollution and etc, can not be neglected. To quantify the impact of these changes, many researchers have studied meteorological and climatic parameters using statistical relationships, but one major problem always existed, the low spatial accuracy of meteorological data. In recent years,... 

Support vector regression (SVR) in the field of machine learning attracted much attention because of its attractive features and high efficiency for high-dimensional and nonlinear data. Although support vector regression has shown to be very effective for prediction problems, it is necessary to adjust the parameters contained therein to obtain the desired output with error rates. In the past, this was done manually, by trial and error. Over time and by development of optimization algorithms, one of the newest methods to solve such problems is the meta-heuristic optimization algorithms. Therefore, in this thesis, we use the firefly optimization algorithm, which is a population-based... 

One of the most surprising lessons of dynamical systems theory is that the phase spaces of simple nonlinear systems may contain strange attractors. For certain simple systems, such as pendulum, direct observations of the phase space and finding strange attractors are possible. But physical systems in which all the relevant dynamical variables can be simultaneously monitored are relatively scarce. Takens’ theory shows how a time-series of measurements of a single observable state can be often used to reconstruct qualitative features of the phase space of the system. In this research, using the time-series of one measurable state, an algorithm is proposed to control chaos. The approach... 

Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuroimaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. To obtain these goals the analysis of fMRI is the first condition which should be met. First methods were linear and assumed the... 

Studies in recent years have shown formation of strongly functionally linked sub-networks during rest, networks that are often referred to as resting-state networks. RSNs not only have basic information about the brain but also play a key role in detecting brain disorders, such as Alzheimer and Autism; Consequently, they have been remarkably noticed by neuroscientists. Numerous methods have been used in order to extract RSNs using resting-states fMRI time series. Independent component analysis (ICA) is the most common method, whi have been reported to show a high level of consistency neurophysiology; however, its results is unstable in subject-level. is weakness restricted the ICA... 

Chaotic time series analysis, study of statistical behavior of chaotic maps and eventually an attempt to reconstruction and prediction of dynamical and statistical properties of output data of chaotic systems using stochastic models such as Markov models and autoregressive-moving average models are the main purposes of the present research. Examples of chaotic time series abound in the output of economics, engineering systems, the natural sciences (especially geophysics and meteorology) and social sciences. An intrinsic feature of an output time series of a dynamic system is that, adjacent observations are dependent. Time series analysis is concerned with techniques for the analysis of this...