Many cities in the Global South are structurally different from Northern, particularly American, on which much of urban sociology’s conceptual apparatus has been based. Thus, depicting them terms a standard vocabulary risks imposing an inappropriate way seeing. We need that is able to accommodate their experience. This special issue contributes work building vocabulary. select five keywords soc...

a r t i c l e i n f o Keywords: Subtractive clustering Adaptive network-based fuzzy inference system Technical indicators Adaptive learning Genetic algorithm Technical analysis is one of the useful forecasting methods to predict the future stock prices. For professional stock analysts and fund managers, how to select necessary technical indicators to forecast stock trends is important. Traditio...

In the exponential smoothing approach to forecasting, restrictions are often imposed on the smoothing parameters which ensure that certain components are exponentially weighted averages. In this paper, a new general restriction is derived on the basis that the one-step ahead prediction error can be decomposed into permanent and transient components. It is found that this general restriction red...

This paper gives a methodology for decompositions of a very wide class of time series, including normal and non-normal time series, which are represented in state-space form. In particular the linked signals generated from dynamic generalized linear models are decomposed into a suitable sum of noise-free dynamic linear models. A number of relevant general results are given and two important cas...

An approach to exponential smoothing that relies on a linear single source of error state space model is outlined. A maximum likelihood method for the estimation of associated smoothing parameters is developed. Commonly used restrictions on the smoothing parameters are rationalised. Issues surrounding model identi…cation and selection are also considered. It is argued that the proposed revised ...

Discrete choice model is the most used methodology for studying traveler’s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. In this study, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, d...

⎯Due to the lack of a structure way in determining the free parameters of support vector machines (SVMs), this study uses genetic algorithms (GAs) to select parameters of SVMs. In addition, the developed SVMG (support vector machine with genetic algorithms) model is applied to reliability prediction. Two numerical examples in the literature are employed to illustrate the performances of various...

Numerous methods exist and were developed for global radiation forecasting. The two most popular types are the numerical weather predictions (NWP) and the predictions using stochastic approaches. This article presents a methodology for determining the best method to use, according to a rule related to the spatial resolution, temporal step and location. We propose to compute a parameter noted  ...

Recently, HPC (High Performance Computing) systems have gone from supercomputers to clusters. The clusters are used in all tasks that require very high computing power such as weather forecasting, climate research, molecular modeling, physical simulations, cryptanalysis, etc. The use of clusters is increasingly important in the scientific community, where the need for high performance computing...

Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine i...