Introduction to Nanotechnology

We present new spatio-temporal geostatistical modelling and interpolation capabilities of the R package gstat. Various spatio-temporal covariance models have been implemented, such as the separable, product-sum, metric and sum-metric models. In a real-world application we compare spatiotemporal interpolations using these models with a purely spatial kriging approach. The target variable of the application is the daily mean PM 10 concentration measured at rural air quality monitoring stations across Germany in 2005. R code for variogram fitting and interpolation is presented in this paper to illustrate the workflow of spatio-temporal interpolation using gstat. We conclude that the system works properly and that the extension of gstat facilitates and eases spatio-temporal geostatistical modelling and prediction for R users

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Spatio-Temporal Interpolation using gstat

In the structure of ANFIS, there are two different parameter groups: premise and consequence. Training ANFIS means determination of these parameters using an optimization algorithm. In the first ANFIS model developed by Jang, a hybrid learning approach was proposed for training. In this approach, while premise parameters are determined by using gradient descent (GD), consequence parameters are found out with least squares estimation (LSE) method. Since ANFIS has been developed, it is used in modelling and identification of numerous systems and successful results have been achieved. The selection of optimization method utilized in training is very important to get effective results with ANFIS. It is seen that derivate based (GD, LSE etc.) and non-derivative based (heuristic algorithms such us GA, PSO, ABC etc.) algorithms are used in ANFIS training. Nevertheless, it has been observed that there is a trend toward heuristic based ANFIS training algorithms for better performance recently. At the same time, it seems to be proposed in derivative and heuristic based hybrid algorithms. Within the scope of this study, the heuristic and hybrid approaches utilized in ANFIS training are examined in order to guide researchers in their study. In addition, the final status in ANFIS training is evaluated and it is aimed to shed light on further studies related to ANFIS training.

Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey

[서평]「Chaos and Fractals : New Frontiers of Science」

Fuzzy Relational Systems: Foundations and Principles

Due to the suburbanisation process, it is becoming more difficult to properly define rural and urban areas in the Czech Republic. This delimitation problem has been intensively studied in Europe, including the Czech Republic, for decades, but only so-called ‘crisp’ rules have been set for the categorisation of urban and rural. This is no longer satisfactory because of substantial population movements. Our research focuses on applying fuzzy set theory to the delimitation of rural and urban areas and on the subsequent advanced cartographic visualisation. We used the principles of fuzzy regulation, or fuzzy inference systems, on socio-economic data to show the transitional character of municipalities. The generated Main map is at scale of 1:500,000, whereas secondary maps are at scale of 1:2,500,000. Map visualisation of municipalities in the Czech Republic provides a very unique combination of geographical information science, cartography and modern geo-computational methods. Information perception via a ma...

https://www.tandfonline.com/doi/pdf/10.1080/17445647.2014.944942

Using a fuzzy inference system to delimit rural and urban municipalities in the Czech republic in 2010

Since 1965 when the fuzzy logic and fuzzy algebra were introduced by Lotfi Zadeh, the fuzzy theory successfully found its applications in the wide range of subject fields. This is mainly due to its ability to process various data, including vague or uncertain data, and provide results that are suitable for the decision making. This paper aims to provide comprehensive overview of literature on fuzzy control systems used for the management of the road traffic flow at road junctions. Several theoretical approaches from basic fuzzy models from the late 1970s to most recent combinations of real-time data with fuzzy inference system and genetic algorithms are mentioned and discussed throughout the paper. In most cases, fuzzy logic controllers provide considerable improvements in the efficiency of traffic junctions’ management.

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Fuzzy Logic in Traffic Engineering: A Review on Signal Control

/pdf/regular-use-of-entropy-for-studying-dissimilar-geographical-28lrj59xyu.pdf

Regular use of entropy for studying dissimilar geographical phenomena

Background
Visual analytics aims to connect the processing power of information technologies and the user’s ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution.

/pdf/using-geovisual-analytics-in-google-earth-to-understand-596i9te3dv.pdf

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

Geodetic measurements and monitoring are traditional methods of the observation of landslides, and slope movements processes in general. The precision of measurements is usually an important task, as well as the expended amount of time and money are important. It is not necessary to reach sub-centimetre precision in case of the regular monitoring of shallow landslide due to the effort to the evaluation of the whole landslide body. Unmanned aerial vehicles provide the great improvement in the efficiency of the process, and they also broaden possibilities in the visualization while the accuracy is still preserved on the suitable level. The contribution aims to present the current observation of shallow landslide, which has been monitored for 6 years using geodetic measurements. Recently, the conventional surveying activities are complemented by the photogrammetric methods (Drone Pixy or Hexacopter), which allows not only the monitoring of selected measuring points but also the complex monitoring and precise evaluation of the general shape of the landslide body.

Pavel Tuček

Papers

Using a fuzzy inference system to delimit rural and urban municipalities in the Czech republic in 2010

Fuzzy Logic in Traffic Engineering: A Review on Signal Control

Regular use of entropy for studying dissimilar geographical phenomena

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

Monitoring of the Shallow Landslide Using UAV Photogrammetry and Geodetic Measurements