TSK Fuzzy Neural Network Use for COVID-19 Classification
نویسندگان
چکیده
It is considered t the Takagi-Sugeno-Kang fuzzy neural network and its modern variations. The use of regularization, random exclusion rules from rule base allows solving problem excessive similarity in base. batch normalization to increase generalizing properties accuracy model, while maintaining possibility interpreting results, which characteristic networks. proposed an ensemble networks capabilities network. Studies for task diagnosing coronavirus disease show that model works well improve result.
منابع مشابه
A TSK-Type Quantum Neural Fuzzy Network for Temperature Control
In this paper, a TSK-type quantum neural fuzzy network (TQNFN) for temperature control is proposed. The TQNFN model is a five-layer structure, which combines the traditional Takagi-Sugeno-Kang (TSK). Layer 2 of the TQNFN model contains quantum membership functions, which are multilevel activation functions. Each quantum membership function is composed of the sum of sigmoid functions shifted by ...
متن کاملA TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms
In this paper, a TSK-type recurrent fuzzy network (TRFN) structure is proposed. The proposal calls for a design of TRFN by either neural network or genetic algorithms depending on the learning environment. Set forth first is a recurrent fuzzy network which develops from a series of recurrent fuzzy if–then rules with TSK-type consequent parts. The recurrent property comes from feeding the intern...
متن کاملAn Improved Fuzzy Neural Network for Solving Uncertainty in Pattern Classification and Identification
Dealing with uncertainty is one of the most critical problems in complicatedpattern recognition subjects. In this paper, we modify the structure of a useful UnsupervisedFuzzy Neural Network (UFNN) of Kwan and Cai, and compose a new FNN with 6 types offuzzy neurons and its associated self organizing supervised learning algorithm. Thisimproved five-layer feed forward Supervised Fuzzy Neural Netwo...
متن کاملAutomatic Counting Cancer Cell Colonies using GIEA for TSK-type Neural Fuzzy Network
This paper proposes a TSK-type neural fuzzy network (TNFN) with a group interaction-based evolutionary algorithm (GIEA) for constructing the cancer cell colonies diagnosis system (CCCDS). The proposed GIEA is designed on the basis of symbiotic evolution which each chromosome in the population represents only partial solution. The whole solution consists of several chromosomes. The GIEA is diffe...
متن کاملMicroRNA-mRNA interaction network using TSK-type recurrent neural fuzzy network.
MicroRNAs are short non-coding RNAs that can regulate gene expression during various crucial cell processes such as differentiation, proliferation and apoptosis. Changes in expression profiles of miRNA play an important role in the development of many cancers, including CRC. Therefore, the identification of cancer related miRNAs and their target genes are important for cancer biology research. ...
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: Elektronìka ta sistemi upravlìnnâ
سال: 2022
ISSN: ['1990-5548']
DOI: https://doi.org/10.18372/1990-5548.71.16825