A decision support system for EEG signals based on adaptive fuzzy inference neural networks

2011 ◽  
Vol 11 (4) ◽  
pp. 209-225 ◽  
Author(s):  
P. Jahankhani ◽  
V.S. Kodogiannis ◽  
J.N. Lygouras ◽  
I.P. Petrounias
Keyword(s):  
Neural Networks ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference ◽  
Eeg Signals ◽  
Adaptive Fuzzy

Applying Fuzzy Logic and Neural Network to Rheumatism Treatment in Oriental Medicine

2007 ◽  
Vol 11 (1) ◽  
pp. 4-10 ◽  
Author(s):  
Cao Thang ◽  
◽  
Eric W. Cooper ◽  
Yukinobu Hoshino ◽  
Katsuari Kamei ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference ◽  
Training Data ◽  
Oriental Medicine ◽  
The Neural Networks

In this paper, we present an application of soft computing into a decision support system RETS: Rheumatic Evaluation and Treatment System in Oriental Medicine (OM). Inputs of the system are severities of observed symptoms on patients and outputs are a diagnosis of rheumatic states, its explanations and herbal prescriptions. First, an outline of the proposed decision support system is described after considering rheumatic diagnoses and prescriptions by OM doctors. Next, diagnosis by fuzzy inference and prescription by neural networks are described. By fuzzy inference, RETS diagnoses the most appropriate rheumatic state in which the patient appears to be infected, then it gives a prescription written in suitable herbs with reasonable amounts based on neural networks. Training data for the neural networks is collected from experienced OM physicians and OM text books. Finally, we describe evaluations and restrictions of RETS.

A Predictive Fuzzy Expert System for Crop Disease Diagnostic and Decision Support

2020 ◽  
pp. 175-194 ◽  
Author(s):  
Prateek Pandey ◽  
Ratnesh Litoriya
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference ◽  
Disease Treatment ◽  
Soybean Crop ◽  
Oilseed Production ◽  
Crop Disease ◽  
Extent Of Disease

Soybean accounts for 38% of the total oilseed production in India, and around 50% of the total oilseed production in Kharif season. This crop has shown tremendous growth over the last four decades with an average national yield of 1264 kg/hectare. Currently, soybean is severely attacked by more than 10 major diseases. Yield losses due to different diseases ranges from 20 to 100%. Timely detection of soybean crop disease would help farmers save their money, effort, and crop from being destroyed. This chapter presents a case study on the development of a decision support system for prediction of soybean crop disease severity. The outcome of this system will aid farmers to decide the extent of disease treatment to be employed. Such predictions make use of human involvement, and thus are a source of ambiguities. To deal with such ambiguities in decision making, this decision support system uses fuzzy inference method based on triangular fuzzy sets.

scholarly journals Neuro-fuzzy inference systems approach to decision support system for economic order quantity

2019 ◽  
Vol 32 (1) ◽  
pp. 1114-1137 ◽  
Author(s):  
Siniša Sremac ◽  
Edmundas Kazimieras Zavadskas ◽  
Bojan Matić ◽  
Miloš Kopić ◽  
Željko Stević
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Systems Approach ◽  
Fuzzy Inference ◽  
Economic Order Quantity ◽  
Order Quantity ◽  
Fuzzy Inference Systems ◽  
Neuro Fuzzy ◽  
Inference Systems

Simultaneous Customers and Supplier’s Prioritization: An AHP-Based Fuzzy Inference Decision Support System (AHP-FIDSS)

2020 ◽  
Vol 22 (8) ◽  
pp. 2625-2651
Author(s):  
Muhammad Imran ◽  
Mujtaba Hassan Agha ◽  
Waqas Ahmed ◽  
Biswajit Sarkar ◽  
Muhammad Babar Ramzan
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference
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