Aquifer vulnerability assessment using GIS and fuzzy system: a case study in Tehran–Karaj aquifer, Iran

2008 ◽  
Vol 58 (2) ◽  
pp. 437-446 ◽  
Author(s):  
Kourosh Mohammadi ◽  
Ramin Niknam ◽  
Vahid J. Majd
2020 ◽  
Vol 34 (2) ◽  
pp. 819-834 ◽  
Author(s):  
Vittorio Catani ◽  
Daniela Zuzolo ◽  
Libera Esposito ◽  
Stefano Albanese ◽  
Mauro Pagnozzi ◽  
...  

Author(s):  
REZIE BOROUN ◽  
YASER TAHMASBI BIRGANI ◽  
ZEINAB MOSAVIANASL ◽  
GHOLAM ABBAS SHIRALI

Numerous studies have been conducted to assess the role of human errors in accidents in different industries. Human reliability analysis (HRA) has drawn a great deal of attention among safety engineers and risk assessment analyzers. Despite all technical advances and the development of processes, damaging and catastrophic accidents still happen in many industries. Human Error Assessment and Reduction Technique (HEART) and Cognitive Reliability and Error Analysis Method (CREAM) methods were compared with the hierarchical fuzzy system in a steel industry to investigate the human error. This study was carried out in a rolling unit of the steel industry, which has four control rooms, three shifts, and a total of 46 technicians and operators. After observing the work process, reviewing the documents, and interviewing each of the operators, the worksheets of each research method were completed. CREAM and HEART methods were defined in the hierarchical fuzzy system and the necessary rules were analyzed. The findings of the study indicated that CREAM was more successful than HEART in showing a better capability to capture task interactions and dependencies as well as logical estimation of the HEP in the plant studied. Given the nature of the tasks in the studied plant and interactions and dependencies among tasks, it seems that CREAM is a better method in comparison with the HEART method to identify errors and calculate the HEP.  


DYNA ◽  
2015 ◽  
Vol 82 (190) ◽  
pp. 38-45 ◽  
Author(s):  
Hector Valdes-Gonzalez ◽  
Lorenzo Reyes-Bozo ◽  
Eduardo Vyhmeister ◽  
José Luis Salazar ◽  
Juan Pedro Sepúlveda ◽  
...  

This article presents an intelligent system for container stacking based on fuzzy logic. The method establishes a defined criterion for accepting or rejecting in real time an entry request to the stacking areas of the port in Valparaiso, Chile. A case study based on expert knowledge illustrates the proposed method with real data. First, the optimum solution is determined for a problem of maximization of entries, based on historical records from the traffic and information center of Valparaiso Port. Second, this solution is used to establish a strategy for making “the best possible decisions.” The combination of the optimization and the fuzzy results (which consider the type of cargo, prices, and capacity) is performed at two levels. First, the optimization results are used as feed for the fuzzy system to determinate a ratio of future acceptances. Second, the optimization results are compared to the fuzzy system results in order to estimate a parameter to establish the minimal percentage value for accepting a request. As a result, a proper use of the stacking area is achieved, which results in an increase of profits and revenue management.


2011 ◽  
Vol 02 (03) ◽  
pp. 427-437
Author(s):  
Jalil Khodaparast Shirazi ◽  
Mehrzad Ebrahimi ◽  
Mazda Moatari

2019 ◽  
Vol 10 (11) ◽  
pp. 1131-1135
Author(s):  
Tomas Hambili Paulo Sanjuluca ◽  
◽  
Ricardo Correia ◽  
Anabela Antunes de Almeida ◽  
Ana Gloria Diaz Martinez ◽  
...  

Introduction: In order to have a good assessment of the quality of maternal and child health care, it is essential that there is up-to-date and reliable information. Objective: To evaluate the impact of the implementation of a computerized database of clinical processes in the admission, archive and medical statistics section, of Maternity hospital Irene Neto/Lubango-Angola. Methodology: A descriptive study with a quantitative and qualitative approach to carry out a retrospective case study deliveries and newborns, records from 2014 to 2017. Final considerations: The implementation of this project may contribute to the improvement of clinical management support management of the hospital as well as facilitating access to information for research and scientific production.


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