Performance Measurement Model for Wind Power Project Using Mamdani Fuzzy Inference System

Author(s):  
Debasish Majumder ◽  
Mrinmoy Dam ◽  
Rupak Bhattacharjee ◽  
Shyam Sundar Santra ◽  
Rishiraj Saha ◽  
...  
2020 ◽  
Vol 8 (2) ◽  
pp. 84-88
Author(s):  
Herryawan Pujiharsono ◽  
Danny Kurnianto

The government has launched a program to increase the production of catfish by using biofloc ponds. The biofloc ponds can maintain the quality of water biologically to maximize the growth of fish. However, the level of water quality monitoring is generally only divided into good or bad categories so that it cannot represent the condition of fish growth. Therefore, this study aims to get the level of water quality (0–100 %) using the Mamdani fuzzy inference system (FIS) algorithm based on pH, temperature, and dissolved oxygen (DO). The level of water quality was correlated based on catfish growth conditions. The results showed that the range of values of the water quality level for each condition of catfish growth was 100 % for normal-living fish, 83–99 % for stunted fish growth, and < 83% for threatened fish. The FIS algorithm had 89.92 % of accuracy.


Author(s):  
Krasimir Slavyanov ◽  
Chavdar Minchev

This article offers an original ISAR image classification procedure based on Mamdani fuzzy inference system (FIS) dedicated to compute multiple results each from different type of analyzing criteria. The modeling and information analysis of the FIS are developed to draw a general conclusion from several results each produced by classification from neural network. Simulation experiments are carried out in MATLAB environment.


2022 ◽  
Vol 71 (2) ◽  
pp. 3019-3033
Author(s):  
Tahir Alyas ◽  
Iqra Javed ◽  
Abdallah Namoun ◽  
Ali Tufail ◽  
Sami Alshmrany ◽  
...  

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