Ideal of Fuzzy Inference System and Manifold Deterioration Using Genetic Algorithm and Particle Swarm Optimization
نویسنده
چکیده
Ideal of Fuzzy Inference System and Manifold Deterioration Using Genetic Algorithm and Particle Swarm Optimization is presented. Hypoglycaemia or low blood glucose often occurs with patients that take insulin therapy for diabetes. Hypoglycaemia is serious and causes unconsciousness, seizures or even death. The proposed system uses ECG signal for the detection of hypoglycemia. To find the presence of the hypoglycaemic episodes the system uses heart rate (HR), corrected QT interval, change of HR and change of corrected QT interval of the ECG signal. The system is developed using multiple regression with fuzzy inference system (FIS). Genetic algorithm and particle swarm optimization is used to optimize the parameters of FIS and multiple regressions. Fuzzy Inference System is used to estimate the hypo level based on the physiological parameters. The physiological parameters are heart rate and corrected QT interval. Multiple regressions are used to fine tune the performance of the hypoglycemic detection based on the estimated hypo level and the change of the HR and corrected QT interval. Thus estimate the presence of hypoglycemia using the FIS and multiple regressions with genetic algorithm and also with particle swarm optimation and finally comparing the performance of both
منابع مشابه
ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM OPTIMIZATION USING PSO FOR PREDICTING SEDIMENT TRANSPORT IN SEWERS
The flow in sewers is a complete three phase flow (air, water and sediment). The mechanism of sediment transport in sewers is very important. In other words, the passing flow must able to wash deposited sediments and the design should be done in an economic and optimized way. In this study, the sediment transport process in sewers is simulated using a hybrid model. In other words, using the Ada...
متن کاملFraud Detection of Credit Cards Using Neuro-fuzzy Approach Based on TLBO and PSO Algorithms
The aim of this paper is to detect bank credit cards related frauds. The large amount of data and their similarity lead to a time consuming and low accurate separation of healthy and unhealthy samples behavior, by using traditional classifications. Therefore in this study, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used in order to reach a more efficient and accurate algorithm. By com...
متن کاملFrequency Control of Isolated Hybrid Power Network Using Genetic Algorithm and Particle Swarm Optimization
This paper, presents a suitable control system to manage energy in distributed power generation system with a Battery Energy Storage Station and fuel cell. First, proper Dynamic Shape Modeling is prepared. Second, control system is proposed which is based on Classic Controller. This model is educated with Genetic Algorithm and particle swarm optimization. The proposed strategy is compared with ...
متن کاملOptimization and design of Adaptive Neuro-Fuzzy Inference System using Particle Swarm Optimization and Fuzzy C-Means Clustering to predict the scour after bucket spillway
Additionally, if the materials at downstream of bucket spillway are erodible, the ogee spillway is likely to overturn by the time. Therefore, the prediction of the scour after bucket spillway is pretty important. In this study, the scour depths at downstream of bucket spillway are modeled using a new meta-heuristic model. This model is developed by combination of the Adaptive Neuro-Fuzzy Infere...
متن کاملFuzzy Particle Swarm Optimization Algorithm for a Supplier Clustering Problem
This paper presents a fuzzy decision-making approach to deal with a clustering supplier problem in a supply chain system. During recent years, determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions is usually complex and unstructured. In general, many quantitative and qualitative factors, such as quality, price, and fl...
متن کامل