scholarly journals GLSCH: OBSERVATION SCHEDULER FOR THE GLORIA TELESCOPE NETWORK

2019 ◽  
Vol 51 ◽  
pp. 111-115
Author(s):  
C. López-Casado ◽  
C. J. Pérez del Pulgar ◽  
E. Fernández ◽  
V. F. Muñoz ◽  
A. Castro-Tirado
Keyword(s):  
Fuzzy Logic ◽  
Weather Forecast ◽  
Design And Development ◽  
Decision Algorithm ◽  
Decision Algorithms

This paper proposes the design and development of a scheduler for the GLORIA telescope network. This network, which main objective is to make astronomy closer to citizens in general, is formed by 18 telescopes spread over four continents and both hemispheres. Part of the management of this network is made by the network scheduler. It receives the observation requests made by the GLORIA users and then sends it to the most suitable telescope. A key module of the network scheduler is the telescope decision algorithm that makes possible to choose the best telescope, and thus avoiding offering an observation to a telescope that cannot execute it. This paper shows two different telescope decision algorithms: the first one is only based on weather forecast, meanwhile the second one uses fuzzy logic and information from each network telescope. Both algorithms were deployed in the GLORIA network. The achieved results coupled with a comparative of their performance is shown. Moreover, the network scheduler architecture, based on a hybrid distributed-centralized schema, is detailed.

scholarly journals The Mamdani Fuzzy Logic Engineering Analysis for Determining Weather Forecast

2021 ◽  
Vol 1783 (1) ◽  
pp. 012039
Author(s):  
Aris Munandar Harahap ◽  
Saib Suwilo ◽  
Rahmat Widia Sembiring
Keyword(s):  
Fuzzy Logic ◽  
Weather Forecast ◽  
Engineering Analysis

Designing Layers in Hierarchical Fuzzy Logic Systems Using Genetic Algorithms

2011 ◽  
pp. 76-87
Author(s):  
Masoud Mohammadian ◽  
Russel Stonier
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Interest Rate ◽  
Fuzzy Logic System ◽  
Good Prediction ◽  
Design And Development ◽  
Fuzzy Logic Systems ◽  
Financial Modelling ◽  
Logic Systems ◽  
Logic System

In this paper the design and development of hierarchical fuzzy logic systems is investigated using genetic algorithms. This research study is unique in the way the proposed method is applied to the design and development of hierarchical fuzzy logic systems. The new method proposed determines the number of layers in the hierarchical fuzzy logic system. The proposed method is then applied to financial modelling and prediction. A hierarchical fuzzy logic system is developed to predict quarterly interest rates in Australia. The advantages and disadvantages of using hierarchical fuzzy logic systems for financial modelling is also considered. Good prediction of quarterly interest rate in Australia is obtained using the above method. The number of fuzzy rules used is reduced dramatically and prediction of interest rate is improved.

scholarly journals Design and Development of Fuzzy Logic Application Tsukamoto Method in Predicting the Number of Covid-19 Positive Cases in West Java

2020 ◽  
Vol 1 (2) ◽  
pp. 85-95
Author(s):  
Alwi Dahlan Permana
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Incubation Period ◽  
Error Rate ◽  
Percentage Increase ◽  
Design And Development ◽  
West Java

The increase in covid-19 positive patients in Indonesia, especially in West Java, is unpredictable, resulting in unpreparedness in dealing with covid-19 cases. People in monitoring and patients under supervision are the category that is breast-positive patients after passing the incubation period for 14 days. Fuzzy logic is one derivative of artificial intelligence that is able to predict a thing.The study used the fuzzy logic of the Tsukamoto method to predict the percentage increase in positive cases of covid-19 with measures performed are fuzzification, rule formation, inference, and defuzzification. The results showed a 4.5% error rate indicating that predicting covid-19 using the fuzzy logic of the Tsukamoto method was successful.

Modelling, Control and Prediction using Hierarchical Fuzzy Logic Systems

2020 ◽  
pp. 187-207 ◽  
Author(s):  
Masoud Mohammadian
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Methodological Approach ◽  
Research Work ◽  
Fuzzy Logic System ◽  
Robotic Control ◽  
Design And Development ◽  
Fuzzy Logic Systems ◽  
Learning Speed ◽  
Logic Systems

Hierarchical fuzzy logic systems are increasingly applied to solve complex problems. There is a need for a structured and methodological approach for the design and development of hierarchical fuzzy logic systems. In this paper a review of a method developed by the author for design and development of hierarchical fuzzy logic systems is considered. The proposed method is based on the integration of genetic algorithms and fuzzy logic to provide an integrated knowledge base for modelling, control and prediction. Issues related to the design and construction of hierarchical fuzzy logic systems using several applications are considered and methods for the decomposition of complex systems into hierarchical fuzzy logic systems are proposed. Decomposition and conversion of systems into hierarchical fuzzy logic systems reduces the number of fuzzy rules and improves the learning speed for such systems. Application areas considered are: the prediction of interest rate and hierarchical robotic control. The aim of this manuscript is to review and highlight the research work completed in the area of hierarchical fuzzy logic system by the author. The paper can benefit researchers interested in the application of hierarchical fuzzy logic systems in modelling, control and prediction.

Design and development of portable fuzzy logic based traffic optimizer

2013 ◽  
Author(s):  
Kenneteh Tze Kin Teo ◽  
Kiam Beng Yeo ◽  
Shee Eng Tan ◽  
Zhan Wei Siew ◽  
Kit Guan Lim
Keyword(s):  
Fuzzy Logic ◽  
Design And Development
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