A Genetic Algorithm Based Fuzzy Inference System for Pattern Classification and Rule Extraction
نویسندگان
چکیده
منابع مشابه
Genetic Algorithm based Rule Extraction from Pruned Modified Fuzzy Hyperline Segment Neural Network for Pattern Classification
The Pruned modified fuzzy hyperline segment neural network (PMFHLSNN) is pruned extension of Fuzzy hyperline segment neural network (FHLSNN) with modification in the testing phase. In this paper, a genetic algorithm based rule extractor (GA-PMFHLSNN) is proposed to extract a small set of compact and comprehensible fuzzy if-then rules with high classification accuracy from the PMFHLSNN. After pr...
متن کاملAdaptive Network-based Fuzzy Inference System-Genetic Algorithm Models for Prediction Groundwater Quality Indices: a GIS-based Analysis
The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...
متن کاملNeuro-Fuzzy Networks for Pattern Classification and Rule Extraction
In this paper, an experimental evaluation of the neurofuzzy models NEFCLASS and FuNN is conducted in real world pattern recognition applications. The models are investigated with respect to classification performance and the number of rules generated and compared to the traditional MLP network trained with backpropagation. The models NEFCLASS and FuNN are examined in benchmarking problems from ...
متن کاملA Genetic Fuzzy Approach for Rule Extraction for Rule- Based Classification with Application to Medical Diagnosis
Rule extraction is an important task in knowledge discovery from imperfect training dataset in uncertain environments such as medical diagnosis. In a medical classification system for diagnosis, we cope with expensive or lack of expert knowledge in the design of the classifier. This paper presents an evolutionary fuzzy approach for tackling the problem of uncertainty in the process of rule extr...
متن کاملADAPTIVE NEURO FUZZY INFERENCE SYSTEM BASED ON FUZZY C–MEANS CLUSTERING ALGORITHM, A TECHNIQUE FOR ESTIMATION OF TBM PENETRATION RATE
The tunnel boring machine (TBM) penetration rate estimation is one of the crucial and complex tasks encountered frequently to excavate the mechanical tunnels. Estimating the machine penetration rate may reduce the risks related to high capital costs typical for excavation operation. Thus establishing a relationship between rock properties and TBM pe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Engineering & Technology
سال: 2018
ISSN: 2227-524X
DOI: 10.14419/ijet.v7i4.35.22762