Optimization algorithms as training approaches for prediction of reference evapotranspiration using adaptive neuro fuzzy inference system

DK Roy, A Lal, KK Sarker, KK Saha, B Datta - Agricultural Water …, 2021 - Elsevier
… Another contribution of this work is the selection of best ANFIS model utilizing decision …
The historical daily weather data were obtained from an automatic weather station located in …

New daily global solar irradiation estimation model based on automatic selection of input parameters using evolutionary artificial neural networks

M Marzouq, Z Bounoua, H El Fadili… - Journal of cleaner …, 2019 - Elsevier
… an automatic selection of ANN inputs from available parameters set for the estimation of
horizontal daily global solar irradiation in the city of Fez (Morocco). This selection is … selection, …

Neuroevolutionary based convolutional neural network with adaptive activation functions

R ZahediNasab, H Mohseni - Neurocomputing, 2020 - Elsevier
… In this paper, the evolutionary method is used to select the best values for some parameters
… of adaptive activation function, hyper-parameters used in these functions are initialized as α …

An adaptive neuro-fuzzy system with integrated feature selection and rule extraction for high-dimensional classification problems

G Xue, Q Chang, J Wang, K Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
… which automatically determined the architecture of the network model during the feature
selection process… The system parameters are also initialized as we explained earlier. The λs are …

New mixed-coding PSO algorithm for a self-adaptive and automatic learning of Mamdani fuzzy rules

MA Kacimi, O Guenounou, L Brikh, F Yahiaoui… - … Applications of Artificial …, 2020 - Elsevier
… learning process, completely automatic and not sensitive to the initialization. Against other …
tuning the MFs parameters and the second one is the changing of the selected conclusion for …

An automated breast cancer diagnosis using feature selection and parameter optimization in ANN

S Punitha, F Al-Turjman, T Stephan - Computers & Electrical Engineering, 2021 - Elsevier
… The core objective of the proposed IAIS-ABC-CDS technique focuses on the implementation
of an automatic IAIS-ABC inspired feature selection and hidden node size optimization …

A hybrid optimized model of adaptive neuro-fuzzy inference system, recurrent Kalman filter and neuro-wavelet for wind power forecasting driven by DFIG

HHH Aly - Energy, 2022 - Elsevier
… on the input variables x and y … values for some selected of different runs using either ANN
or WNN with different number of neurons and hidden layers to choose the optimal parameters

An incremental construction of deep neuro fuzzy system for continual learning of nonstationary data streams

M Pratama, W Pedrycz, GI Webb - IEEE Transactions on Fuzzy …, 2019 - ieeexplore.ieee.org
… It is equipped by an automatic feature selection method, which controls activation and
deactivation of input attributes to induce varying subsets of input features. A deep network …

An adaptive reference vector-guided evolutionary algorithm using growing neural gas for many-objective optimization of irregular problems

Q Liu, Y Jin, M Heiderich… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
… GNG) network to achieve automatic yet stable adaptation. To this end, … selection which is
the same as that in RVEA [12]. Here, we only select the solutions in the first PF for APD selection

… Adaptive Neural-Fuzzy Algorithms Based on Adaptive Resonant Theory with Adaptive Clustering Algorithms for Classification, Prediction, Tracking and Adaptive …

VA Akpan, JB Agbogun - American Journal of Intelligent …, 2022 - eprints.gouni.edu.ng
… the type of initialization, training and adaptation algorithms used to … Furthermore, two types
of different adaptive neuro-fuzzy … The parameters can be automatically adjusted depending on …