scholarly journals Application of Fuzzy Logic for Monitoring of Appearance of Heat Waves in Large Towns

MENDEL ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 165-172
Author(s):  
Jiri Bila ◽  
Jakub Jura ◽  
Martin Novak
Keyword(s):  
Heat Waves ◽  
Maximum Temperature ◽  
System Function ◽  
Knowledge Based System ◽  
Fuzzy Models ◽  
Knowledge Based ◽  
Relevant Variables ◽  
Large Town ◽  
The City ◽  
Selection Of

In the paper are introduced some results of the influence of cooling effect of vegetation on the climate in large towns. The results have been acquired from measurement of some meteorological variables in selected parts of large town and from application of fuzzy models on the prediction of maximum day temperature. Great motivation of the paper is not only course of maximum temperature in standard days but especially the more dramatic situations as is appearance of Heat Waves. Besides the selection of relevant variables and the design of knowledge based system (with application) is performed an approximation operation for knowledge based systém function taking into account the conditions throughout the city.

scholarly journals CARBON FOOTPRINT OF THE LEGALIZATION OF ACTIVITIES AT THE CITY OF SEVILLE

10.6036/9885 ◽  
2021 ◽  
Vol 96 (1) ◽  
pp. 134-139
Author(s):  
ANTONIO MATIAS NAVARRO TORRES ◽  
ANGEL MENA NIETO ◽  
GABRIEL BRAVO ARANDA ◽  
FRANCISCO HERNANDEZ RODRIGUEZ
Keyword(s):  
Carbon Footprint ◽  
Energy Demand ◽  
Ghg Emissions ◽  
City Council ◽  
Economic Activities ◽  
Large Cities ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Commercial Activities ◽  
The City

The reduction of Greenhouse Gases (GHG) emission in cities is vital because cities generate 60% of global GHG emissions. By the middle of this century, two-thirds of the planet's population is expected to be concentrated in cities. For this reason, energy demand and GHG emissions in large cities will continue to increase, concentrating on urban centres, productive, transport and commercial activities. This increase in economic activities in cities leads to an increase in the number of legalization procedures that are processed by municipalities to authorize and control their implementation. In response to the problems raised, it is presented the results of an investigation undertaken to demonstrate that the application of a Knowledge-Based System (KBS) can significantly reduce the carbon footprint that is currently generated in the Licensing Service of the city council of Seville, as a consequence of the current high failure rate in the subsequent control after the start-up of activities by responsible declaration. The implementation of the SBC would reduce the carbon footprint by 78%, considering an average establishment with 300 m2 of built area. This proposal can be applied in any city council of the more than 8000 that exist in Spain, which would have an enormous impact on reducing the carbon footprint of cities and reducing costs for public coffers, and all this without the need to invest in renewing the fleet of vehicles with others that produce fewer emissions, and facilitating the task of promoters of economic activities, with the help of knowledge management. Keywords: Carbon footprint, Greenhouse Gas Emissions, Local administration, Knowledge-based system, Compliance.

scholarly journals Selection of Welding Process for Repairing Shredder Hammer by Integrated Data Envelopment Analysis (DEA) and P-robust Technique

2019 ◽  
Vol 269 ◽  
pp. 04002
Author(s):  
Rahmad Wisnu Wardana ◽  
Eakkachai Warinsiriruk ◽  
Sutep Joy-A-Ka
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Arc Welding ◽  
Welding Process ◽  
Data Envelopment ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Metal Arc Welding ◽  
Welding Processes ◽  
Selection Of

The Selection of the welding process is one of the most significant decision-making problems, and it involves a wide range of information following the type of product. Hence, the automation of knowledge through a knowledge-based system will significantly enhance the decision-making process and simplify for identifying the most appropriate welding processes. The aims of this paper for explicates a knowledge-based system developed for recognising the most suitable welding processes for repairing shredder hammer by using data envelopment analysis (DEA) and p-robust technique. The proposed approach is used for ranking six welding processes which are commonly used, namely shielded metal arc welding (SMAW), flux cored arc welding (FCAW), submerged arc welding (SAW), oxyacetylene gas welding (OAW), gas tungsten arc welding (GTAW), and gas metal arc welding (GMAW). In order to determine the best welding process among competitive welding processes for repairing of shredder hammer, ten parameters are used, namely the availability of consumable, welding process type (manual and automatic), flexibility of welding position, weld-ability on base metal, initial preparation required, welding procedures, post-weld cleaning, capital cost, operating factor, and deposition rate. Furthermore, the sensitivity analysis of regret value (p) is investigated in three cases proposed.

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