Recent advances in neuro-fuzzy system: A survey
Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
Liquefaction potential assessment of soils using machine learning techniques: a state-of-the-art review from 1994–2021
Abstract Machine learning (ML) has emerged as a powerful tool for prediction of systems
behavior in many engineering disciplines. A few applications of ML techniques are available …
behavior in many engineering disciplines. A few applications of ML techniques are available …
[KSIĄŻKA][B] Support vector machines for pattern classification
S Abe - 2005 - Springer
Since the introduction of support vector machines, we have witnessed the huge
development in theory, models, and applications of what is so-called kernel-based methods …
development in theory, models, and applications of what is so-called kernel-based methods …
Least squares support vector machine (LS-SVM)-based chiller fault diagnosis using fault indicative features
H Han, X Cui, Y Fan, H Qing - Applied Thermal Engineering, 2019 - Elsevier
Fault detection and diagnosis (FDD) of chillers, generally the single most energy consuming
piece of building equipment, is an important but hard task where many parameters are …
piece of building equipment, is an important but hard task where many parameters are …
Short-term wind power prediction based on LSSVM–GSA model
X Yuan, C Chen, Y Yuan, Y Huang, Q Tan - Energy Conversion and …, 2015 - Elsevier
Wind power forecasting can improve the economical and technical integration of wind
energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to …
energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to …
Breast cancer diagnosis using least square support vector machine
The use of machine learning tools in medical diagnosis is increasing gradually. This is
mainly because the effectiveness of classification and recognition systems has improved in …
mainly because the effectiveness of classification and recognition systems has improved in …
A new fuzzy support vector machine to evaluate credit risk
Due to recent financial crises and regulatory concerns, financial intermediaries' credit risk
assessment is an area of renewed interest in both the academic world and the business …
assessment is an area of renewed interest in both the academic world and the business …
A cascade learning system for classification of diabetes disease: Generalized discriminant analysis and least square support vector machine
The aim of this study is to diagnosis of diabetes disease, which is one of the most important
diseases in medical field using Generalized Discriminant Analysis (GDA) and Least Square …
diseases in medical field using Generalized Discriminant Analysis (GDA) and Least Square …
Identification of drug–target interactions via fuzzy bipartite local model
With the emergence of large-scale experimental data on genes and proteins, drug discovery
and repositioning will be more difficult in the field of biomedical research. More and more …
and repositioning will be more difficult in the field of biomedical research. More and more …
Diagnostics and prognostics method for analog electronic circuits
Analog circuits play a vital role in ensuring the availability of industrial systems. Unexpected
circuit failures in such systems during field operation can have severe implications. To …
circuit failures in such systems during field operation can have severe implications. To …